The Ninth IEEE International Workshop on Signal Processing Advances in Wireless Communications Program

In this paper, we consider a multiple antenna broadcast scenario with multiple non-cooperative users under the assumption of imperfect channel state information. Under an instantaneous transmit power constraint, vector perturbation precoding requires that the users be continuously informed about the adaptive power scaling factor used at the transmit side. To overcome this limitation, we propose a new precoding scheme that uses a fixed power scaling and avoids transmitting when the available power is not sufficient to perform channel equalization at the transmit side, an event referred to as outage. We present a performance analysis and optimization of this scheme and provide numerical comparisons with classical vector perturbation.

Reduced-rank MMSE CDMA receivers have received a lot of attention recently. The output SINR provided by a reduced-rank receiver depends on the filter rank and is confined between the SINRs of the Single User Matched Filter (SUMF) and the Minimum Mean Squared Error (MMSE) receiver. In Packet CDMA data networks like HSDPA, the measure of performance is the throughput. Thus, previous results on reduced-rank MMSE receivers SINR cannot be used directly. In this paper, we study the throughput of CDMA Data networks using reduced-rank MMSE receivers, Automatic retransmission request (ARQ) and Packet Combining.We derive the expression of the system throughput as the function of the filter rank, the coding rate and the number of retransmissions. We present simulation results to highlight the behavior of the maximum throughput as a function of the filter rank and the coding rate. We then conclude on coding strategies to adopt depending on the signal to noise ratio and the receiver rank in order to maximize the system throughput.

We present a general framework for the minimization of a function which is parametrized by a set of covariance matrices over a constraint set. Since all covariance matrices have to obey the property of being positive semidefinite, this characteristic has to be reflected in the constraint set. In addition, the sum of all traces of the covariance matrices shall be upper bounded. Using a preconditioned gradient descent algorithm, we derive an orthogonal projection onto this constraint set in an easy to follow monolithic way such that it directly results from the definition of the projection. Interestingly, this projection allows for a descriptive water-spilling interpretation in the style of the well-known water-filling algorithm. Two possible applications are investigated: the sum mean-square-error minimization and the weighted sum-rate maximization for the MIMO broadcast channel. Simulations finally reveal the excellent performance of the proposed framework.

Transmission techniques for the wireless multi-antenna broadcast channel often require that the receivers feed back their channel state information (CSI) to the transmitter. In this paper, we propose a limited feedback method to approximate zero-forcing beamforming. Each user feeds back quantized information about channel direction and a deterministic lower bound on its signal-to-interference-plus-noise ratio (SINR), which require no more than an integer and a real number. With this information, the Base Station performs user scheduling, beamforming and rate adaptation. In this method, the information from both receiver and transmitter sides are taken into account to arrive at a tight lower bound on the supported rate of each user. Since a lower bound on the SINR is fed back, the proposed method avoids outage. We discuss the feedback load of the method, and show numerical results of the relationship between sum-rate and feedback load, SNR and number of users, as well as a comparison with similar methods.

Time and frequency offsets can cause severe degradation in the performance of any OFDM-based System. Therefore synchronization procedures are necessary for the proper function of a receiver. In OFDMA, where different users share the available subcarriers, synchronization becomes an arduous task. Synchronization errors as far as the uplink transmission is concerned may cause intolerable Multiple Access Interference (MAI) as the signals are produced by different mobile users and propagate through different channels with various Carrier Offsets and Doppler shifts. The receiver must estimate a number of parameters and compensate for the produced intercarrier (ICI) and intersymbol (ISI) interference. These tasks cause massive increase of the computational workload required by the receiver. However, with the use of proper filtering and multirate processing the receiver complexity can be contained with no significant performance degradation

In this paper, we propose a robust novel approach with closed-form estimator for object tracking based on a non-linear measurement model over time from a single sensor with arbitrary noise degradation. Relying on the widely-used dynamic motion model for arbitrary moving targets, tracking of moving objects can be formulated using Received Signal Strength (RSS) measurements. We provide a closed-form solution that integrates localization and filtering for both an ideal channel as well as noisy channel. We first derive an exact linear model from the non-linear system of equations provided by the RSS measurements. We subsequently present an iterative method to estimate the unknown parameters and the error covariance matrix. Moreover, we prove that the estimator gives more accuracy when the number of samples increases. The Cramer-Rao Bound (CRB) for the estimator are determined in Gaussian case. Computer simulation demonstrates that the proposed approach not only achieves more accuracy than traditional methods but also saves significant computation time.

An iterative joint decoding algorithm for data gathering wireless sensor networks is proposed in [1] and its performance is evaluated when sensors monitor a collection of correlated Gaussian sources. They consider the correlation between sensors’ data as a global code and concatenate it with an error correcting code applied at each sensor. Iterative decoding is performed at the fusion center by passing extrinsic information between the two decoders. We apply this algorithm for sensor networks with binary CEO model. In contrast to [1], in our model sensors observe different noisy versions of a single source, located away from sensors. However, since all sensors observe the same source, their data are still correlated and iterative joint decoding can be applied. We use the concept of iterative horizontalvertical decoding for concatenated block codes to formulate the update rules for L-values for the considered binary CEO model. Since the sensors’ observations are noisy, the distortion is bounded away from zero. The minimum achievable distortion is a function of the level of observation noises. We simulate the system using both separate decoding scheme and the iterative joint decoding scheme, when convolutional codes are applied as error correcting codes. Simulation results show that the joint decoding scheme substantially decreases the bit error rate and reaches the minimum achievable distortion for channels with significantly higher noise levels. [1] S. Howard and P. Flikkema, “Integrated source-channel decoding for correlated data-gathering sensor networks,” to appear 2008 IEEE Wireless Communications and Networking Conference (WCNC 2008).

Energy efficient transmission is of vital importance in the design of wireless sensor networks (WSN). Minimizing the sum of energy consumption of all sensor nodes in the network may lead to some nodes with non-rechargeable batteries running out of energy quickly. In this paper, we consider to maximize the time until the first node fails in the network, namely, the network lifetime. Transmission schemes in a WSN where multiple sensors observe a common physical phenomenon are investigated. We show that the optimal joint time and power control (JTPC) takes advantage of ``lazy scheduling" and ``opportunistic quantization". We then demonstrate that the JTPC can be implemented in a partially distributed manner. Numerical results show that significant lifetime gain can be achieved when compared with existing scheduling algorithms.

This paper analyzes the connectivity of wireless ad hoc networks in both a non-cooperative scheme and a cooperative scheme. Assuming that nodes are randomly distributed with a Poisson process, the probability of full connectivity in a system can be raised by increasing the number of connectional trials at each node. Even though an infinite number of trials guarantee full connectivity in a system, it is not of practical concern because it may require infinite power and infinite delay. Instead, this paper analyzes the required number of connection trials for full connectivity mathematically and experimentally. In addition, this paper proposes a cooperative scheme to maximize the benefit from collaboration among nodes and simulates its results.

We consider a new source coding problem motivated by the following distributed estimation task in a clustered sensor network. Suppose there are multiple uncorrelated signal sources in the field that we are interested in, however, these sources cannot be directly observed by the sensors. Sensors within each cluster communicate directly with their corresponding cluster-head (CH) to report their observations, which are mixtures of all signal sources in the field, corrupted by noise. Based on the collected data, the CHs estimate the sources and collaborate to improve these initial estimates. Under stringent energy constraint, which prohibits the sensors within a cluster to jointly encode their correlated observations, we propose to employ distributed source coding (DSC) to encode sensors' correlated data. In particular, we propose a practically simple, and yet effective, encoding algorithm for sensors, a data reconstruction scheme for CHs, and the corresponding rate allocation policy. We investigate the trade off between rate and mean square error (MSE) performance for the proposed algorithms. Numerical evaluations testify the effectiveness of the proposed methods.

Recently, distributed space-time coding over half duplex wireless relay networks has been proposed to achieve higher diversity at the receiver. The use of orthogonal and quasi-orthogonal designs in such relay networks has the advantage of providing maximum diversity at a low decoding complexity. However, similar to their originating space-time codes, these designs are restricted in terms of rate and number of relays. In order to alleviate such restrictions, we propose an extension of group-coherent codes (GCCs) to wireless relay networks. As will be shown, with a very limited amount of feedback from receiver to the relays, it is possible to achieve a distributed code that is applicable for any number of relays without an additional rate loss. In addition, our approach offers the advantages of linear ML decoding complexity, maximum diversity, lower delay, and increased power gain. We further show that it is possible to improve the performance at the price of a higher feedback rate. Finally, the robustness of our scheme against node failures is verified.

In this paper, a low complexity blind synchronization algorithm is proposed for Ultra Wideband (UWB) communication systems in the multipath environment. Using the first order statistics of the received signal, the proposed algorithm is carried out without aided data. The synchronization parameter and nuisance ones are separated from each other on account of the structure of the Vandermonde matrix, and their estimates are obtained by one-dimensional searching according to the orthogonality among vectors. During the searching process, relative path delays and attenuations come out as by-products. Most importantly, the proposed algorithm has a very low complexity, because the computational requirements are determined mainly by simple additions and inner products among vectors. Simulations and comparisons are performed to illustrate the promising performance of the proposed algorithm.

We consider carrier frequency offset (CFO) estimation for single-carrier and single-user transmission over a frequency-selective channel. When training is solely devoted to frequency synchronization, it is important to design the training to optimize CFO estimation performance. In this paper we exhibit the training sequence that minimizes the Cramer-Rao bound associated with the carrier frequency offset and averaged over the channel statistics following a correlated Ricean fading channel model. Simulations show significant improvements compared to the standard pseudo-random white training sequence.

In this paper, we present a new algorithm of blind frame synchronization and phase offset estimation that can be applied to any digital transmission scheme using a channel coding with a Binary Phase Shift Keying (BPSK) modulation. The estimator is based on the calculation of the syndrome elements of a received codeword obtained using the parity check matrix of the code. After presenting the proposed method, we evaluate its performance by applying it to some Low Density Parity Check (LDPC) codes and convolutional codes. This performance is measured by plotting the probability of false frame synchronization and the Mean Squared Estimation Error (MSEE) versus the Signal to Noise Ratio ($E_b/N_0$).

In this paper, we propose a Decoupled root-MUSIC algorithm called root-DMUSIC, adapted to Multidimensional Harmonic Retrieval. The optimization criterion of the proposed algorithm is based on multidimensional orthogonal condition testings between a tensor steering manifold parameterized by the parameters of interest and a set of orthogonal projectors associated with each dimension. This criterion can be viewed as a set of decoupled estimation subproblems and allows the use of fast polynomial rooting techniques. In consequence, the proposed algorithm is highly scalable, parallelizable and avoids costly enumerative-based search. However, decoupling property implies to correctly pair the estimated model parameters. So, we propose a fast automatic pairing procedure based on the exploitation of the Vandermonde-structure preserving property of the Alternating Least Squares Candecomp/Parafac (ALS-CP) algorithm. In addition, we study in a first time the case of a single snapshot and we generalize our algorithm to the multiple snapshots scenario. Finally, by means of numerical simulations, we show that the proposed scheme is efficient with respect to other standard algorithms for a complexity cost one order of magnitude less.

In this work several methods for the location of legacy GSM handsets are compared. These methods use data available in the mobile station measurement report - communication channel server identity, received power levels from the serving and neighbor cells, received signal quality - and time alignment with the server. It is discussed how these parameters can be used for mobile station positioning. A new approach for the cell identity plus time alignment method, using propagation modeling, is proposed. The efficiency of radio-frequency fingerprint correlation using coverage prediction maps of different resolutions is also analyzed. Field tests were conducted to evaluate the methods in real scenarios.

In certain OFDM-based communication systems for which data demodulation is not the final goal, it is often of interest to estimate the Signal-to-Noise power Ratio (SNR) from observed samples that are taken asynchronously. Examples include link quality monitoring in broadcast repeaters and spectrum sensing in cognitive radio systems. We examine the structure of the Maximum Likelihood estimate for this problem and propose an iterative method for its computation. The resulting estimate, based on the Karhunen-Loeve Transform (KLT) of the data vector, is well behaved and robust to multipath. The computationally intensive KLT can be substituted by the more efficient FFT, asymptotically achieving the same performance.

We propose a new simple and accurate approach to estimate the Doppler spread which is a key parameter in the context of wireless communication systems. This new approach stems from the well known fact that the crosscorrelation of the channel is a weighted summation of monochromatic plane waves (or inverse Fourier transform of its power spectral density). In the case of Doppler spread, these plane waves are locally distributed around a main frequency which is nothing but the carrier frequency offset (CFO). This special feature accounts for the Taylor series expansions that we use herein to develop a two-ray spectrum approximate model. The resulting approximation allows us to determine a new simple and accurate closed-form estimator of the the Doppler spread under the unique symmetry assumption on the channel's spectrum. Simulations illustrate the advantages of the proposed technique and its robustness to the CFO.

This work presents a new version, with reduced computational complexity, of the covariance-based direction-of-arrival (CB-DoA) algorithm. The new algorithm incorporates the concept of beamspace projection before performing the DoA estimation. Such modification reduces the dimensions of the matrices employed by the elementspace CB-DoA, simplifying the resulting computations while preserving the detectability of the original algorithm. The Beamspace CB-DoA algorithm is compared to the traditional algorithm Beamspace ESPRIT, as well as to elementspace CB-DoA.

The practical use of any equalization scheme that relies on pilot based channel estimates is often hindered by high computational requirements, especially in cases where a precise estimation criterion is crucial. The goal of this paper is to show that any pilot based scheme that is able to induce a Toeplitz structure in the channel correlation matrix, can make use of an existing class of so-called superfast algorithms for Toeplitz inverses which are specially suitable to pilot-based estimators. The key point behind such observation is that the required Toeplitz inverse inherent to common minimum mean-square error (MMSE) or least-squares (LS) criteria can not only be performed offline, but efficiently implemented via efficient FFT techniques. The most significant consequence of this fact is that, given a structure for the vector of pilots and an upper bound for the channel delay spread, say N, it is only necessary to store 2N coefficients per pilot structure in order to recover the entire channel. This is particularly useful in turbo equalization scenarios and DVB applications, especially for sparse channels. We shall illustrate the idea via a zero-padded (ZP) and standard cyclic prefix based block transmission schemes.

In this paper, we consider a receiver setup with fewer analog to digital convertors (ADC's) than antennas. An analog preprocessing network (APN) is placed before the ADC's to reduce power consumption in the receiver. A set of low resolution beamformers is used to design the APN and cancel contributions of interfering users. Simulation results show that introduction of such APN design algorithms for a narrowband channel with 3 to 4 interfering users, 6 antennas and 3 ADCs results in a reduction of the total consumed receiver power by 15%.

This paper presents a low-complexity reduced-rank approach to adaptive linearly constrained minimum variance (LCMV) beamforming. The proposed reduced-rank scheme is based on a constrained joint iterative optimization of adaptive filters according to the minimum variance criterion. The constrained joint iterative optimization procedure adjusts the parameters of a bank of full-rank adaptive filters that forms the projection matrix and an adaptive reduced-rank filter that operates at the output of the bank of filters. We describe LCMV expressions for the design of the projection matrix and the reduced-rank filter and low-complexity stochastic gradient adaptive algorithms for their efficient implementation. Simulations for a beamforming application show that the proposed scheme outperforms in convergence and tracking the state-of-the-art existing reduced-rank schemes with significantly lower complexity.

Spatial multiplexing is a common technique for Multiple-Input Multiple-Output (MIMO ) communications that independent information streams are sent over different antennas. The precoder design based on the channel state information (CSI) can process the transmitting symbol before transmission. However, the spatial multiplexing is still sensitive to the ill-conditioning of the channel matrix. The conventional beam directions in the precoder are designed via singular value decomposition (SVD) which diagonalize the MIMO channel matrix H into eigenmodes. In this paper, we present a different approach using LU decomposition (LUD) to obtain the beam directions. We show that the LUD yields better channel condition and hence better error performance. The LUD-based precoder also has less feedback channel bandwidth requirement and lower complexity than the conventional SVD-based precoder.

The design of channel quantization codebooks for correlated broadcast channels with limited feedback is addressed. A design criterion that effectively exploits the cell statistics is proposed, based on minimizing the average sum-rate distortion in a system with joint linear beamforming and multiuser scheduling. The proposed average distortion function is optimized by generating a set of quantization codebooks through random trials, keeping the codebook that yields the lowest distortion. Comparisons with limited feedback approaches relying on random codebooks are provided, highlighting the importance of matching the codebook design to the cell statistics. Numerical results show a performance gain in scenarios with non-uniform user distributions. Further, we propose a scheme that exploits the limited channel knowledge at the base station to reduce the computational complexity of determining the beamforming vectors and of finding the optimal user set.

This paper presents an enhanced permeable layer mechanism useful for reliable packetized multimedia transmission. Packet header recovery at various protocol layers using MAP estimation is the cornerstone of the proposed solution. The available intra-layer and inter-layer header correlation is used to define a reduced set of header configurations for further processing. The best candidate is then obtained through soft decoding based on CRC redundancy. Simulation results for WiFi transmission scheme using DBPSK modulated signals in AWGN channels show a substantial (4 to 12 dB) link budget improvement. A sub-optimal and hardware realizable version of the proposed algorithm is also presented.

The performance of the carrier sense multiple access / collision avoidance (CSMA/CA) protocol under the presence of carrier sensing errors is analyzed. Two types of carrier sensing errors, false alarm and miss detection, are considered, and their impact on system performance is analyzed using a new CSMA/CA model based on a Markov chain capturing the sensing errors at the physical layer. The throughput as a function of these sensing error probabilities as well as other CSMA/CA parameters is obtained. It is shown that the throughput loss by a poorly chosen sensing threshold is tolerable at intermediate values of the ratio of the packet size to the contention window size, whereas care should be taken in choosing the sensing threshold when the ratio is small or large.

A data-dependent sensor MAC protocol and a cross-layered fusion rule that exploits the MAC timing information are proposed for distributed detection in sensor networks. In this system, each sensor first makes a local decision at the beginning of each observation period and transmits the decision to the fusion over a random access channel. Based on the slotted ALOHA random access protocol, we derive a transmission control function that assigns a transmission probability to each sensor based on the reliability of its local decisions. By doing so, the packet arrival time at the fusion center may embed soft information regarding the sensors' observations and may be exploited to reduce the error probability at the fusion center. We consider two observation models: in Case I, each sensor makes a new observation in each time slot; while in Case II, only one observation is made at the beginning each observation period. We show, through numerical simulations, that the proposed schemes outperform those without cross-layered transmission and fusion strategies.

We address the problem of resource allocation on an OFDMA downlink under fairness constraints with limited Channel State Information (CSI). Target QoS corresponds to a minimum user data rate, a target bit-error rate and a maximum outage probability. The channel model includes pathloss, shadowing and fading. The only available CSI is the channel average gain of each user. This partial CSI cqn be viewed as a shadowed pathloss that yields a modified user distribution on which resource allocation is based. Under these constraints, we provide the optimal resource allocation that maximizes the user rate. Compared to full-CSI-based allocation schemes, our solution offers a significant complexity and feedback reduction as well as a good robustness to CSI estimation errors.

The study of random access protocols has recently regained attention due to new cross-layer schemes such as multipacket reception (MPR) systems and network diversity multiple access protocols (NDMA). Despite their relevance, these two systems have only been simultaneously studied employing finite user population models and considering perfect detection of the active users, which are assumptions only useful in scenarios with low numbers of users and high values of the SNR. The purpose of this paper is to introduce an infinite user population model, valid for scenarios with large numbers of users and finite traffic loads, which allows us to extend the available results on ALOHA MPR protocols to systems that use retransmission diversity (RD). Unlike existing approaches our model includes both the effects of packet decoding errors and the effects of imperfect detection of the active users, which considerably affect the performance of conventional NDMA systems in finite SNR environments. Additionally, the proposed model provides a better approximation to the queuing delay of NDMA protocols than the conventional formula of an M/G/1 queue with vacations. Finally, the proposed algorithm also represents an extension and generalization of contention binary tree algorithms assisted by signal processing tools such as SICTA (Successive Interference Cancellation Tree Algorithm) and other algorithms assisted by source separation. The benefits of the proposed model are assessed using simulation and analytic results.

In this paper we investigate the decoding of parallel turbo codes over the binary erasure channel suited for upper-layer error correction. The proposed algorithm performs "on-the-fly" decoding, i.e. it starts decoding as soon as first symbols are received. This algorithm compares with the iterative decoding of codes defined on graphs, in that it propagates in the trellises of the turbo code by removing transitions in the same way edges are removed in a bipartite graph under message-passing decoding. Performance comparison with LDPC codes for different coding rates is shown.

This paper presents a study about q-ary product turbo codes applied to FFH-CDMA systems. A method to implement the q-ary soft decoding is proposed. First, an adaptation of Chase decoding algorithm to satisfy q-ary symbols requirements is developed. The adaptation does not significantly increase decoding complexity when compared to the binary algorithm. Second, a modification of iterative (turbo) decoding allows appropriate feedback of decoded q-ary symbols and their reliabilities in each decoder iteration. Simulation results indicate a good performance/complexity trade-off of the q-ary turbo coded system when compared to other previous proposed systems.

In this work we study joint multiuser detection using factor graphs for an N frequency T user noisy multiple access channel. This channel may model a frequency hopped code division multiple access system. The system is separated in two parts: multiuser detector (MUD) and a code. We present a factor graph for the multiuser detector and obtain from it extrinsic information transfer (EXIT) curves. Paired with the EXIT curves of Low Density Parity Check (LDPC) and Repeat Accumulate (RA) codes, we obtain values for the signal to noise ratio (SNR) that bound the system’s performance. The EXIT curves for the codes are presented from the detectors perspective. The results show that rates close to the sum capacity are achievable.

We evaluate the performance of a Grouped Chip-Level iterated (CLi) Multiuser Detection (MUD) Technique that is based on Gaussian Forcing technique for overloaded synchronous Code-Division Multiple Access systems. We confirm that the new grouped CLi MUD can approach the performance of the more complex CLi MUD with brute-force search. Also, we show that the new Grouped CLi MUD can provide a greater flexibility in trading off the performance and complexity. Furthermore, by incorporating a dynamic user grouping, the performance of the new CLi MUD technique can be further improved. We show via computer simulation, at the system with 200% condition, the loss of approximately 0.3 dB compared to its brute-force counterpart is observed while reducing the complexity to more than half.

This paper provides a performance comparison of multiple-input multiple-output (MIMO) demodulators for bit-interleaved coded modulation (BICM) systems with non-iterative demodulation and decoding. We propose to use the capacity of an equivalent "modulation" channel as a performance measure that has the advantage of not depending on the outer error correcting code. Based on this approach, we conclude that a universal ranking of MIMO (soft and hard) demodulation algorithms is not possible. This result is confirmed via bit error rate simulations for a practical system involving low-density parity-check codes. Our approach also allows to derive practical guidelines for MIMO-BICM system design.

This paper studies the fluctuations of the post processing SNR at the output of the linear MMSE receiver in (receive) correlated multiple input multiple output (MIMO) systems. Although it is known that, asymptotically, the SNR behaves like a gaussian random variable, this approximation may yield to inaccurate estimates for small dimension. In order to circumvent this, we use Gamma and Generalized Gamma distributions to approximate the probability distribution of the SINR. The first three asymptotic moments of the SNR are computed and are used to adjust Gamma and Generalized Gamma distributions and to accurately approximate the Bit Error Rate (BER) and its outage probability. We provide simulations which strongly support the Gamma approximation, even for a small number or emitting/receive antennas.

Traditional information-theoretic approaches to study channel feedback assume that the information is sent from the receiver to the transmitter via an ideal (instantaneous high-rate and error-free) feedback link. This paper investigates the problem of reliable communication over non-ergodic memoryless (stationary) channels using non-errorfree feedback links. We first provide a coding theorem showing that the estimation-induced outage (EIO) capacity is achieved by using rate splitting and hierarchical encoding, where the codes of different layers are jointly designed to exploit the feedback information. The feedback encoder uses hierarchical quantization to compress the state information, allowing the forward encoder to obtain successive refinement of the feedback information during the transmission. The capacity is evaluated for a fading MIMO channel assuming a single-antenna fading feedback link and imperfect channel estimation at the receiver. Simulation results show the joint impact of: (i) successive refinement of quantized feedback, (ii) noisy feedback and (iii) imperfect channel estimation, on the EIO capacity.

Bit error rate (BER) prediction over channel realisations has emerged as an active research area. In this paper, we give analytical signal to interference and noise ratio (SINR) evaluation of MIMO-OFDM systems using an iterative receiver. Using this analytical SINR expression, we propose an accurate BER prediction method based on effective exponential SINR mapping (EESM) method. We show by simulations that our method is independent of the channel realisation and of the MIMO scheme. It is only dependent on the modulation and coding scheme.

Channel Division Multiple Access (ChDMA) is a promising multiple access scheme for Ultra-Wide Band (UWB) systems based on the use of the Channel Impulse Responses (CIR) as user signatures. In this work, we model the UWB-CIR as linear combinations of continuous impulses of finite duration randomly delayed. Two different channels are considered: the first one is very simplistic, and the multipaths are uniformly distributed over the time; the other one assumes a correlation between the delay and the energy of the multipaths. The capacity is investigated assuming no Channel State Information (CSI) at the transmitters and perfect CSI at the receiver. As results, we derive the asymptotic capacity assessment of the ChDMA scheme when the number of active users tends to infinity and the frequency resolution tends to zero in a constant ratio. As a consequence, we observe that the asymptotic capacity depends only on the system load, the noise variance and the impulse via its Fourier transform. The asymptotic results are compared with simulated channels.

In this paper we propose a novel M-ary biorthogonal pulse shape modulation scheme for an Impulse radio ultra wideband (IR-UWB) system transmitting over lognormal fading channels. Our proposed modulation scheme enables different transmission rates for a fixed number of orthogonal pulses M/2, while the symbol period T_s is constant. In our transmission scheme information bits are mapped into N pulses (N symbols), using M/2 orthogonal pulses and their negates. The N generated pulses are superimposed to form one pulse that will be transmitted over the channel. The transmission rate provided by this scheme is N (\log_2 M/N)/T_s and is maximized at N=M/4 (i.e., one bit per orthogonal pulse). We consider maximum ratio combing (MRC)-RAKE receiver to demodulate N symbols. For the proposed scheme we derive a closed-form expression for symbol error probability and an upper bound on symbol error rate, using Wilkinson's method. Given the same channel delay spread, our scheme provides a better error performance and higher throughput than that of pulse position modulation (PPM) scheme.

The majority of information-theoretic hyper-receiver cellular models preserve a fundamental assumption which has initially appeared in Wyner's model, namely the co-location of User Terminals (UTs). Although this assumption produces more tractable mathematical models, it is unrealistic with respect to current practical cellular systems. In this paper, we alleviate this assumption by assuming uniformly distributed UTs. The model under investigation is a GCMAC over a planar cellular array in the presence of power-law path loss and flat fading. In this context, we evaluate the effect of UT distribution on the optimal sum-rate capacity by considering a variable-density cellular system. Furthermore, we compare the sum-rate capacity produced by the planar and the linear cellular array. Finally, the analytical results are interpreted in the context of a typical macrocellular scenario.

Future mobile communications radio networks, e.g. 3GPP Long Term Evolution (LTE), will typically use an orthogonal frequency division multiplexing (OFDM) based air interface in the downlink. Furthermore, in order to avoid frequency planning, a frequency reuse factor of one is desirable. In this case, system capacity is limited by interference, which is particularly crucial for mobile terminals with a single receive antenna. For a high throughput, interference cancellation algorithms are required in the receiver. In this paper, a single antenna interference cancellation (SAIC) algorithm is introduced for amplitude--shift keying (ASK) modulation schemes used in coded OFDM transmission which achieves high gains in comparison to a conventional coded OFDM transmission employing quadrature amplitude modulation (QAM) in an interference limited scenario. Furthermore, an adaptive least--mean--square (LMS) and a recursive least--squares (RLS) SAIC receiver, respectively, are presented. We show that in particular the RLS solution enables a good tradeoff between performance and complexity and is robust even to multiple interferers and frequency synchronization errors.

We present the structure of a transceiver for a frequency selective channel that allows the introduction of reduced redundancy. The problem of finding the transceiver that optimizes the information rate is a difficult non-linear optimization problem. For that reason we present a simple algorithmic procedure in order to obtain suboptimal solutions. We also show that the structure proposed approaches capacity when the data block length gets large. We present simulation results that show that the proposed design outperforms other existing ones in the literature.

We consider vector perturbation precoding over a quasi-static MIMO channel under the assumption of imperfect channel state information (CSI). This is accomplished via a high SNR analysis, specifically targeting the overall system diversity order and the identification of typical errors. The effects of long-term and short-term power constraints, or power allocation policies, are investigated. Our results indicate that under realistic assumptions regarding the channel estimation error the system is mainly interference limited and as such, the particular power constraint does not significantly affect the asymptotic behavior of the error probability. This is in sharp contrast to the case of perfect CSI.

This paper describes a novel on-demand receive filter in an UMTS terminal. The receive filter is the first function after the Analog-to-Digital converter and is for that reason one of the most computation intensive parts in a receiver. The proposed filter architecture measures the out-of-band interference and calculates the required attenuation, which is used to select the appropriate filter. To assess the advantages of this on-demand receive filter, we have carried out field strength measurements in the UMTS FDD downlink band (2.1 GHz). These measurements were carried out in Amsterdam, a dense urban area with 5 active UMTS operators. Our measurement results show that in a live network configuration there is almost no out-of-band interference. Moreover, an on-demand filter would save in this case more than 68% power compared to a fixed conventional receive filter.

A new method for estimating nonlinear instantaneous channels in a multiuser Code Division Multiple Access (CDMA) environment is presented in this paper. This kind of nonlinear models has important applications in the field of telecommunications, e.g. to model uplink channels in Radio Over Fiber multiuser communication systems. The proposed technique is based on the decomposition of a tensor composed of covariances of the chip-rate sampled received signals, the transmitted signals being assumed to be Phase Shift Keying (PSK) modulated. The considered tensor-based approach allows a great flexibility on the number of antennas and the spreading factor, which is particularly desirable when identifying nonlinear systems. Two blind channel estimation algorithms are considered: the Alternating Least Squares (ALS) algorithm and a non-iterative algorithm based on Eigenvalue Decompositions (EVD). The performance of the proposed estimation algorithms is illustrated by means of computer simulations.

The purpose of this paper is to report on an unsuitable behavior of the constrained stochastic gradient (CSG) algorithm for adaptive beamforming in the combination of two events: one or more interference angles of arrival are close to the signal angle of arrival and the angle spreads of the involved signals are small. In this situation, the CSG algorithm stresses the co channel interference minimization more than the maximization of the power radiated to the in cell mobile terminal. We term this phenomenon unbalanced behavior and provide an analytical study to explain it.

Blind source separation methods resort to very weakly hypothesis concerning the source signals, as well as the mixing matrix. This paper verifies experimentally the performance improvement in two different source separation algorithms when some statistical knowledge about the mixing matrix is used. A natural way of inserting such information in source separation methods is to put them in a Bayesian framework. This approach presents immediate applications in digital communication systems and in speech signals processing, among many others.

We propose distributed compression for the uplink channel of a backhaul-constrained coordinated cellular network. In the network, N multiple-antenna base stations compress their received signals using a Distributed Wyner-Ziv code, and then send the compressed vectors to a central BS, which centralizes decoding. For a single-user network, the compression codes at the BSs are optimized in this paper, considering the user's achievable rate as the performance metric.

Multi-antenna systems provide advantages in terms of link quality and multiuser access capabilities, which can be achieved by using schemes as multibeam opportunistic beamforming. This scheme only requires partial channel state information at the transmitter (CSIT) in terms of the equivalent channel moduli. This paper deals with the problem of feeding back the CSI from the multiple receivers to the base station (BS) transmitter through limited capacity feedback links. This involves a quantization and a delay that produces errors in the CSIT. In this sense, the proposed scheme in this paper is based on a robust design that takes into account these errors. Additionally, a dynamic bit allocation in the feedback among the users is derived, and combined with differential quantization to minimize the transmit power. It considers both the users' sensitivities to the quantization errors and the Doppler frequencies due to the mobility. Simulation results show the benefits from using such schemes.

We propose a differential spatial multiplexing (SM) scheme based on complex square orthogonal designs, referred to as differential orthogonal spatial multiplexing (DOSM). The receiver of DOSM does not require estimation of channel fading coefficients, channel power, signal power, or noise power to decode the signal and the decision is based on the two consecutively received codewords. A constellation rotation strategy is introduced to enhance the transmission rate. The error bounds based on the “tightened” version of the Chernoff bound and the design criteria for DOSM are derived. We then use the design criteria to construct optimal DOSM. Simulation results show that the proposed DOSM outperforms the existing differential spatial multiplexing schemes in terms of error-rate performance over quasi-static and time-selective Rayleigh fading channels. Furthermore, it is estimated from the bound that DOSM is only 0.4 dB poorer than coherent SM in a two-input two-output system at high SNR regimes. The computational complexity of DOSM is medium among those differential SM systems.

We consider the broadcast phase of a three-node network, where a relay node with multiple antennas establishes a bidirectional communication between the two other nodes each equipped with a single antenna using a spectrally efficient two phase protocol. In the first phase, both nodes transmit a message to the relay node, which decodes the messages. In the second phase the relay broadcasts a re-encoded composition of them. In this work, we show that for two transmit antennas at the relay node beamforming is always an optimal transmit strategy. We show that if beamforming is optimal the beamforming vector is a linear combination of the two single-user optimal strategies. Further, we analyze the dependency of the capacity region on the correlation between the two channels.

For MISO multiuser downlink wireless communication system with precoding at the transmission, the channel state information at the transmitter can provide tremendous capacity gains. However, the amount of feedback data increases with the number of users in the cell and the number of transmit antennas. In this paper, we study the performance of different user selection algorithms at the receiver side through the noisy uplink channel. We evaluate the effect of the noisy channel on the classical norm criterion with a criterion based on the orthogonality between the user channels. Without cooperation between the users, we only allow users that are semi-orthogonal to feedback their channel information as analog and quantized information to the base station through the noisy uplink channel. We propose an algorithm to reduce the noise effect on the analog feedback for semi-orthogonal user selection algorithm. We show that the semi-orthogonal criterion with quantized feedback gives a better performance compared to the norm criterion for perfect and noisy uplink channels.

We propose a new signaling scheme for the Multiple Access Channel (MAC) based on low-rate Layered LDGM codes. The proposed scheme approaches the ergodic Rayleigh fading MAC capacity.

Distributed estimation and detection is of interest for those situations for which the sensor net must achieve an agreement by exchanging information without resorting to the use of an external fusion center. In this paper we deal with the distributed estimation of a static parameter which has been initially estimated by a set of sensors, and for which it is important to have similar estimates as accurate as possible. The cooperation is performed in a distributed way to guarantee scalability and robustness to failures, and it is designed to reduce the detrimental effects of the channel noise on the sensor exchanges. We pose a general framework to include the most relevant contributions dealing with this type of channel imperfection, so pros and cons can be discussed on common ground.

In this paper we analyze the impact of quantization on the performance of a discrete-time distributed algorithm aimed at computing the average of an initial set of values in a wireless sensor network. We modify a well-known consensus model and propose a simple scheme where the transmitted data is quantized due to bandwith and/or power constraints. Conversely to existing models that include quantization noise, a closed-form expression for the mean square error of the state can be derived for the proposed model. This expression depends on general network parameters and provides therefore, an a priori quantitative measure of the effects of quantization on the consensus, without requiring knowledge of the whole network topology.

An energy-efficient opportunistic collaborative beamformer with one-bit feedback is proposed for ad hoc sensor networks over Rayleigh fading channels. In contrast to conventional collaborative beamforming schemes in which each source node uses channel state information to correct its local carrier offset and channel phase, the proposed beamforming scheme opportunistically selects a subset of source nodes whose received signals combine in a quasi-coherent manner at the intended receiver. No local phase-precompensation is performed by the nodes in the opportunistic collaborative beamformer. As a result, each node requires only one bit of feedback from the destination in order to determine if it should or should not participate in the collaborative beamformer. Analytical results show that the received signal power obtained with the proposed beamforming scheme scales linearly with the number of available source nodes. Since the optimal node selection rule requires an exhaustive search over all possible subsets of source nodes, two low-complexity selection algorithms are developed. Simulation results confirm the effectiveness of opportunistic collaborative beamforming with the low-complexity selection algorithms.

In recent years node localization in Wireless Sensor Networks (WSN) has attracted much attention due to the increase of usage and applications of WSN. Many algorithms and techniques for locating sensor nodes have been proposed in the literature. A recent algorithm, which is based on a given set of pairwise distance estimates among nodes and the target, generates a map of node locations. This algorithm known as FastMap, requires three anchor nodes (for the case of 2D localization) to be located on the vertices of a right triangle. In this paper the performance analysis of the FastMap algorithm in terms of Mean Square Error (MSE) is carried out. Moreover a modified version of FastMap with better performance is proposed and analyzed. The analysis shows that the optimum anchor placement should be at the edge of the network.

In this paper we analyze the performance of wireless ad hoc networks with outage constraints. Using the performance metric aggregate information efficiency, we study the relationship among spectral efficiency, interference immunity, link activity and outage probability. We propose a numerical procedure to estimate the outage probability in a network as a function of several network parameters. Numerical results show that moderate modulation level and high coding rate maximize the network performance.

Average consensus algorithms have attracted popularity in the wireless sensor network scenario as a simple way to compute linear combinations of the observations gathered by the sensors, in a totally decentralized fashion, i.e., without a fusion center. However, average consensus techniques involve the iterated exchange of data among sensors. In a practical implementation, this interaction is affected by noise. The goal of this paper is to bring some common adaptive signal processing techniques into the sensor network context in order to robustify the iterative exchange of data against communication noise. In particular, we will compare the performance of two algorithms: a) a method, reminiscent of stochastic approximation algorithms, using a decreasing step size, with proper decaying law, and b) a relaxation method imposing that the consensus cannot be too distant from the initial measurements. We provide a theoretical analysis, validated by simulation results, of both methods to show how to derive the best tradeoff between the system parameters in order to get the minimum estimation variance, taking into account both observation and interaction noise.

Multi-carrier modulations such as orthogonal frequency division multiplexing (OFDM) are widely used in radio transmission systems. Among these modulations, OFDM/OQAM is an interesting alternative to the conventional cyclic-prefix, OFDM (CP-OFDM) modulation, as it does not require the use of any guard interval. This specificity allows a better spectral efficiency. In this paper we investigate on channel estimation for OFDM/OQAM modulations in the case of multiple-input multiple-output (MIMO) transmissions over radio channels. We focus on a two transmit antenna spatial data multiplexing (SDM) scheme and on the use of scattered pilots for the channel estimation. We propose a MIMO channel estimation method that copes with the intrinsic interference inherent to OFDM/OQAM and we compare this method to ideal channel estimation methods proposed in previous studies.

In this paper, we are interested in blind identification of single-input multiple-output (SIMO) systems. Using the sparsity property of impulse response, we propose an iterative method which minimizes a cost function based on the lp norm. This norm is considered as a good sparsity measure. The simulations show that the proposed method outperforms existing techniques in terms of estimation error and robustness to channel order overestimation.

In this paper, we propose a semi-blind state-space based receiver that jointly performs channel estimation and data detection in MIMO systems subject to fast frequency-selective fading. To accomplish these two tasks, we first define state equations representing the dynamics of channel and transmitted signals. Then, we obtain the state vector by concatenating the transmitted signals and the channel coefficients. This choice of state vector leads to a nonlinear observation equation and hence to the use of the Extended Kalman Filter (EKF) to estimate the states variables. We then develop the EKF and show that the proposed receiver is a generalization of many similar receivers for SISO channels. We also develop a reduced complexity version of the proposed algorithm. Simulation results show the performance gains of the proposed receiver when compared to other commonly used receivers.

In this paper, we consider the problem of identification of nonlinear communication channels using input-output measurements. The nonlinear channel is structured as a LTI-ZMNL-LTI one, i.e. a zero-memory nonlinearity (ZMNL) sandwiched between two linear time-invariant (LTI) subchannels. Considering Volterra kernels of order higher than two as tensors, we show that such a kernel associated with a LTI-ZMNL-LTI admits a PARAFAC decomposition with matrix factors in Toeplitz form. From a thir-order Volterra kernel, we show that the PARAFAC decomposition allows estimating directly the linear subchannels. In the case of a LTI-ZMNL channel, such a task is achieved by considering an eigenvalue decomposition of a given slice of such a tensor. Then, the nonlinear subsystem is estimated in the least squares sense. The proposed identification method is illustrated by means of simulation results.

OFDM/OQAM is a special type of multi-carrier modulation that can be considered as an alternative to conventional OFDM with cyclic prefix (CP) for transmission over multi-path fading channels. Indeed, as it requires no guard interval, it has the advantage of a theoretically higher spectral efficiency. Furthermore, efficient pulse shaping can also be easily implemented with OFDM/OQAM. However, the classical channel estimation methods used for OFDM cannot be directly applied to OFDM/OQAM. In this paper we present an analysis of this problem and we introduce a scattering channel estimation method. The performance results are obtained either by considering a multi-path channel model and regarding to the doppler spread. The proposed OFDM/OQAM channel estimation method is evaluated, in both scenarios, using different pulse shapings and taking conventional CP-OFDM as reference.

In this paper, pilot-assisted transmission over time-selective flat fading channels is studied. It is assumed that noncausal and causal Wiener filters are employed at the receiver to perform channel estimation with the aid of training symbols sent periodically by the transmitter. For both filters, the variances of estimate errors are obtained from the Doppler power spectrum of the channel. Subsequently, achievable rate expressions are provided. The training period, and data and training power allocations are jointly optimized by maximizing the achievable rate expressions. Numerical results are obtained by modeling the fading as a Gauss-Markov process. The achievable rates of causal and noncausal filtering approaches are compared. For the particular ranges of parameters considered in the paper, the performance loss incurred by using a causal filter as opposed to a noncausal filter is shown to be small. The impact of aliasing that occurs in the undersampled version of the channel Doppler spectrum due to fast fading is analyzed. Finally, energy-per-bit requirements are investigated in the presence of noncausal and causal Wiener filters.

In this paper we propose a blind maximum ratio combining (MRC) technique along with an initialization method to improve the performance of the blind adaptive channel shortening algorithm called Multicarrier Equalization by Restoration of Redundancy (MERRY) in the 1x2 SIMO channel context. We show through analysis and simulations that the blind MRC technique allow us to take advantage of the spatial diversity improving considerably the performance of the MERRY algorithm in the SIMO context.

Hybrid Automatic Repeat reQuest (HARQ) improves the throughput performance of ARQ by combining retransmission of packets with Forward Error Correction coding. In MIMO systems employing HARQ and equalization, optimal performance at the receiver is obtained when the signals corresponding to each transmission are combined before the equalizer. Performance can be exchanged for reduced receiver memory by first equalizing the signals after each individual reception and then combining them. For systems that use bit-level combining, post-equalization combining may be the only option for equalizer-based receiver implementation. In this paper the performance limit of post-equalization combining is derived for both linear and decision feedback equalizers used by receivers of HARQ MIMO systems. Moreover, pre-equalization combining and post-equalization combining architectures are compared in terms of the storage-performance tradeoff that they achieve.

We present a new precoding model for closed-loop multiple-antenna systems based a tensor signal modeling and transmit antenna selection. The precoder is modeled as a third-order tensor and decomposed as a function of i) an antenna selection matrix determining the allocation of data streams to transmit antennas and ii) an orthogonal code matrix that spreads the data streams across time-slots. A sub-optimum transmit antenna selection algorithm based on limited-feedback is proposed. Blind channel estimation and symbol detection is afforded at the receiver by exploiting the algebraic tensor structure of the received signal. The bit error rate of the closed-loop system is tested from computer simulations.

We study the problem of joint transmit and receive filters optimization in a frequency selective, multiple-input multiple-output environment. The information about the channel at the transmitter is imperfect and belongs to a specified uncertainty set, defined by bounding the norm of the error transfer function. The framework for a robust optimization of the system, with mean-square-error (MSE) as the performance measure, is derived. Robustness is defined in the worst-case sense, and a broad range of MSE-optimization problems is supported. The algorithms are constructed in an iterative manner, where each iteration consists of two efficiently solvable semidefinite programs. The proofs of the convergence are provided, as well. Numerical examples show significant performance gains in comparison to the system which performs the optimization of the precoder only.

In this paper we deliberate on channel coding for spatial data streams and focus on their equal-rate non-uniform power distribution in successive interference cancellation (SIC) detection algorithm. We focus on high spectral efficiency bit interleaved coded modulation (BICM) MIMO OFDM system where, after serial to parallel conversion, per antenna coding and antenna cycling, spatial data streams are simultaneously transmitted by using an antenna array. The reception is based on SIC detection algorithm. Standard receiver solutions for such schemes employ minimum mean square error (MMSE) successive stripping decoders. Application of MMSE filters combined with the Gaussian assumption of post detection interference institutes sub-optimality in the metrics and furthermore these equalizers are intricate in computation. We propose a novel near optimal demodulator based on match filter outputs for a 2x2 system which reduces the sub optimality of the metric resulting in an improved performance and a significant reduction in computational complexity with respect to the MMSE based solutions. We further extend the idea to higher-dimensional MIMO systems showing that there is a slight degradation in the performance with increase in dimensionality of the system but is concurrently coupled with a boost in complexity savings.

To combine the high power efficiency of Continuous Phase Modulation (CPM) with either high spectral efficiency or enhanced performance in low Signal to Noise conditions, some authors have proposed to introduce CPM in a MIMO frame, by using Space Time Codes (STC). In this paper, we address the code design problem of Space Time Block Codes combined with CPM and introduce a new design criterion based on L2 orthogonality. This L2 orthogonality condition, with the help of simplifying assumption, leads, in the 2x2 case, to a new family of codes. These codes generalize the Wang and Xia code, which was based on pointwise orthogonality. Simulations indicate that the new codes achieve full diversity and a slightly better coding gain. Moreover, one of the codes can be interpreted as two antennas fed by two conventional CPMs using the same data but with different alphabet sets. Inspection of these alphabet sets lead also to a simple explanation of the (small) spectrum broadening of Space-Time Coded CPM.

This article introduces a 3D space-time-space block code for future terrestrial digital TV in single frequency networks. The proposed 3D code is based on a double layer structure designed for inter-cell and intra-cell space time coded transmissions. We show that this new structure is particularly efficient for SFN environments whatever the location of the receiver. It is then suitable for fixed, portable and mobile reception.

32-Amplitude and Phase-Shift-Keying (32APSK) is one of the modulation schemes proposed in the 2nd generation Digital Video Broadcasting over Satellite (DVB-S2) standard. This paper presents a Non-Data-Aided (NDA) SNR estimation scheme for 32APSK using the Expectation-Maximization (EM) algorithm. Two variants of the EM algorithm are presented, first with an arbitrary initialization and a second version that is initialized by modifying an existing (suboptimal) SNR estimation technique. We demonstrate a significantly faster convergence with the latter form of initialization. We compare the performance of this estimator to the Cramer-Rao Lower Bound (CRLB) of NDA SNR estimation and show that the estimator performs very close to the CRLB over all SNRs of practical interest even for block sizes of 100 symbols. The estimator has also been implemented on FPGAs and we show that the fixed point implementation also performs very close to the theoretical limit.

This paper proposes an OFDM receiver for the forward link of a fixed broadband satellite system. Although the satellite channel is not frequency selective, OFDM could be preferred to single carrier waveforms if it allows to improve the system spectral efficiency. The possible gain would arise from the possibility to reduce the overhead in a non-frequency selective channel. The cyclic prefix, introduced to suppress Inter Symbol Interference (ISI), or the pilots used to estimate the channel, are not necessary in such context. Nevertheless, a part of the overhead in OFDM-based systems is necessary for synchronization purposes. This paper focuses on this problem. We propose a complete synchronization structure essentially based on a non pilot aided algorithm, only requiring some reduced overhead for a first coarse synchronization stage. The performance of the proposed receiver is assessed through simulation results.

This work presents a novel Initial Ranging scheme for orthogonal frequency-division multiple-access networks. Users that intend to establish a communication link with the base station (BS) are normally misaligned both in time and frequency and the goal is to jointly estimate their timing errors and carrier frequency offsets with respect to the BS local references. This is accomplished with affordable complexity by resorting to the ESPRIT algorithm. Computer simulations are used to assess the effectiveness of the proposed solution and to make comparisons with existing alternatives.

In this paper, we present a joint algorithm to estimate the fine symbol timing and carrier frequency offsets of wireless orthogonal frequency division multiplexing (OFDM) signals. To jointly estimate synchronization parameters using the maximum likelihood (ML) criterion, we propose to transmit a special pilot symbol. By using a periodic training sequence, we convert the problem of obtaining the ML solution from searching exhaustively over the entire uncertainty range to that of solving a polynomial, thereby greatly reducing the computational load. With the proposed orthogonal and periodic training sequence, we obtain a closed-form expression for the synchronization parameters, hence greatly simplifying the algorithm complexity. Simulations demonstrate that the joint estimation method provides better accuracy than existing joint and separate sampling clock and carrier frequency offsets estimation algorithms.

This paper considers the transmission of a Reed-Solomon (RS) code over a binary modulated time-correlated flat Rician fading channel with hard-decision demodulation. We define a binary packet (symbol) error sequence that indicates whether or not an RS symbol is transmitted successfully across the discrete channel whose input enters the modulator and whose output exits the demodulator. We then approximate the discrete channel's packet error sequence using an Mth order Markov queue-based channel (QBC). In other words, the QBC is used to model the discrete channel at the packet level. Modeling accuracy is evaluated by comparing the simulated probability of codeword error (PCE) for the discrete channel with the numerically evaluated PCE for the QBC. Modeling results identify accurate low-order QBCs for a wide range of fading conditions and reveal that modeling the discrete channel at the packet level is an efficient tool for non-binary coding performance evaluation over channels with memory.

In this paper, downlink opportunistic scheduling is studied in a multiuser environment with single-antenna base station and users. Analytical symbol error rate (SER) expressions are derived under the assumptions of full and quantized channel state information (CSI) at the transmitter. These expressions are used to optimize the channel state feedback parameters.

This paper considers the multiple access channel (MAC) assisted by N parallel relays. For the channel, the rate region with decode-and-forward is derived, considering both full-duplex and half-duplex relaying. The asymptotic sum-rate of the channel, under Rayleigh-distributed fading, is also presented. We prove that the sum-rate of the MAC with D&F relays converges almost surely to the sum-rate without relays. Hence, at the asymptote, multiuser diversity makes D&F relaying useless. Nevertheless, is also shown here that for finite number of users, the sum-rate converges to a strictly increasing function of the number of relays.

The efficiency of multi-access communications over wireless fading links benefits from channel-adaptive allocation of the available bandwidth and power resources. Different from most existing approaches that allocate resources based on perfect channel state information (P-CSI), this work optimizes channel scheduling and resource allocation over orthogonal fading channels when user terminals and the scheduler rely on quantized channel state information (Q-CSI). The novel unifying approach optimizes an average transmit-performance criterion subject to average QoS requirements. The resultant optimal policy per fading realization either allocates the entire channel to a single (winner) user, or, to a small group of winner users whose percentage of shared resources is found by solving a linear program. Both alternatives become possible by smoothing the allocation scheme. The smooth policy is asymptotically optimal and incurs reduced computational complexity.

We consider a multiuser, multi-antenna downlink system in which a base station (BS) equipped with $M$ transmit antennas communicates with $K$ single-antenna receivers. We propose a transmission mode switching scheme, in which the BS selects between single-user and multiuser mode. For that, the BS is assisted by distributed mode selection decisions taken by the mobiles based on local knowledge and statistical information for the other users. Each user feeds back scalar channel quality information (CQI) and its preferred mode. Performance analysis and simulations show this algorithm to exhibit linear capacity growth in the interference-limited region and significant throughput gains for low to moderate number of users.

Interference management is one of effective means of improving system throughput, which is particularly important for the emerging 4G wireless networks that demand increasing data rates. In order to mitigate the inter-cell interference we evaluate the performance of an hierarchical centralized inter-cell scheduling method which aims at improving the system throughput. The proposed algorithm, which is based on an existing one, besides selecting the BSs allowed to transmit, performs an exhaustive power control in order to find the optimal power levels of transmitting BSs. Simulation results show that the proposed method outperforms classical approaches in terms of spectral efficiency improvements.

Multiple Antenna Enhancements via Symbol Timing Relative Offsets (MAESTRO) was recently introduced as a scheme to improve the performance of a V-BLAST like multi-antenna system by introducing sub-symbol timing offsets between the transmit antennas. In this paper, we address the role of receiver structure on performance and the optimal choice of the time offset parameter. A similar timing offset V-BLAST scheme was also introduced by Shao et al., where the authors use a zero-forcing (ZF) receiver and conclude the system outperforms V-BLAST only for small block sizes. We show that the zero-forcing (ZF) receiver suggested by Shao et al. is deficient and is the main reason for some of the drawbacks observed by them. The optimal ZF receiver is derived, and along with the linear MMSE receiver, is shown to exhibit no such weaknesses. The problem of optimal offset is also examined and the optimal offset for a 2x2 MIMO system derived.

Receive diversity with multiple antennas is a very well-known technique to improve receiver performance in fading environments. The concept is particularly simple in OFDM systems, where the channel effect on each subcarrier amounts to a complex multiplication of the transmitted symbol. It is also well known that, provided the antenna noise covariance matrix is known by the receiver, interference rejection combining (IRC), is the optimal linear combining solution. However, estimation of this matrix is usually unfeasible, in which case suboptimum combining techniques such as antenna selection, equal gain combining (EGC) and maximum ratio combining (MRC) are employed. MRC is commonly employed, because it is the optimum technique for uncorrelated noise. However, we'll see in this contribution, that when interference is taken into account, sub-optimum MRC or EGC may be a better choice.

In this paper, we propose a novel channel estimation technique based on 2D spread pilots. The merits of this technique are its simplicity, its flexibility regarding the transmission scenarios, and the spectral efficiency gain obtained compared to the classical pilot based estimation schemes used in DVB standards. We derive the analytical expression of the mean square error of the estimator and show it is a function of the autocorrelation of the channel in both time and frequency domains. The performance evaluated over a realistic channel model shows the efficiency of this technique which turns out to be a promising channel estimation for the future mobile video broadcasting systems.

Hybrid MIMO communication systems combine spatial multiplexing with diversity gain to achieve both high spectral efficiency and link reliability. We present a novel generalized hybrid scheme that allows the use of any number of spatial multiplexing layers (V-BLAST) and any number of quasi-orthogonal layers (ABBA). We also present a low-complexity, ordered, successive interference cancellation receiver based on sorted QR decomposition. The receiver detects each symbol in the same manner, regardless of whether it was spatially or diversity coded, simplifying the receiver's formulation. We show that this novel scheme outperforms other recent hybrid schemes in terms of bit error rate, even when there is precoding at the transmitter. We also show our proposal has lower complexity, achieved by exploiting the structure of the linear dispersion matrices.

Wireless communication systems must be designed to mitigate fading to guarantee a reliable communication. In future technologies, a successful method to improve reliable communication over a wireless link is to use multiple antennas. Recently, a lot of effort has been put into designing closed-loop STBCs schemes with a full rate, full diversity and some array gain for four transmit antennas with one or two bit feed back in case of two complex symbols transmission, respectively. TIn this paper, we propose a new enhancement of diversity using joint Space-Time Block Codes for four transmit antennas with one bit feedback. We show that the proposed scheme can achieve a full diversity, full rate and some array gain with simple linear decoding, and it has same performance compare to EO-STBCs for four transmit antennas with two complex transmit symbols .

This paper introduces a constrained version of a recently proposed generalized data windowing scheme applied to the Conjugate Gradient algorithm. This scheme combines two types of data windowing, the finite sliding window and the exponentially weighted data window, in an attempt to attain the best of both methods in a linearly constrained scenario. The proposed algorithm was tested in a simple adaptive beamforming application, where the expected better performance was demonstrated.

In this contribution we study the impact of transmitter and receiver impairments on the throughput for MIMO and 64QAM transmissions in an evolved HSDPA system. A simple additive white Gaussian noise model is used to model impairments in the transmitter and receiver chain. The investigation is performed through computer simulations both on link and system level. It is found that the impact from transmitter and receiver distortions is rather small for MIMO with 16QAM while the impact when 64QAM is used is more pronounced.

In the framework of cognitive radio, electro-magnetic environment sensing is a crucial task. In order to distinguish various systems relying on OFDM modulations from each others (such as WiMAX, WiFi, DVB-T), we need to be able to estimate precisely the inter-carrier spacing used in the transmitted signal. When the ratio between cyclic prefix and OFDM symbol duration is small or when the multipath propagation channel is almost as large as the cyclic prefix, standard approaches based on detection of cyclic prefix via an autocorrelation fall down. Therefore we propose a new algorithm to estimate the parameters of an OFDM modulated signal (especially the inter-carrier spacing) relying on the fourth order statistics of the received signal. We theoretically prove its robustness to multipath channels, time offset and frequency offset. Then its performance is analysed through numerical simulations and compared to standard approach which confirms the accuracy of the new algorithm.

Dynamic spectrum access (DSA) is an emerging notion in cognitive radio, aiming to improve the spectrum usage with reliable secondary access to the spectral resources. The main challenge in DSA is the detection of spectral opportunities and their efficient utilization without causing interference to the primary users. For this goal, we propose to make use of a reinforcement learning approach: the Multi Armed Bandit (MAB). The MAB approach provides the secondary users with the rules and policies necessary to achieve a tradeoff between exploitation and exploration in DSA. Different MAB strategies are tested on an IEEE802.11medium access model and evaluated in dynamic environment. Our study shows that the MAB constitute a viable solution for the DSA. Adding to that, the performances of the MAB algorithms can be improved with a finite tuning of the internal parameters.

We consider a cognitive radio scenario where a primary and a secondary user wish to communicate with their corresponding receivers simultaneously over frequency selective channels. Under realistic assumptions that the secondary transmitter has no side information about the primary's message and each transmitter knows only its local channels, we propose a Vandermonde precoder that cancels the interference from the secondary user by exploiting the redundancy of a cyclic prefix. Our numerical