In this paper, we investigate the optimal power allocation at the MAC layer in both the asymptotic and the finite blocklength regimes in a two-user NOMA uplink network, under statistical delay constraints captured through the link-layer rate. Using the link-layer effective rate analytic expressions, we provide closed-form expressions of the optimal power coefficients in low and high signal-to-ratio (SNR) regimes. These are validated by an extensive set of simulations, showing that that the proposed power allocation policy optimizes the performance of NOMA compared to OMA at Layer 2.

This paper investigates decoder diversity architectures for short low-density parity-check (LDPC) codes, based on recurrent neural network (RNN) models of the belief-propagation (BP) algorithm. We propose a new approach to achieve decoder diversity in the waterfall region, by specializing BP-RNN decoders to specific classes of errors, with absorbing set support. We further combine our approach with an ordered statistics decoding (OSD) post-processing step, which effectively leverages the bit-error rate optimization deriving from the use of the binary cross-entropy loss function. We show that a single specialized BP-RNN decoder combines better than BP with the OSD post-processing step. Moreover, combining OSD post-processing with the diversity brought by the use of multiple BP-RNN decoders, provides an efficient way to bridge the gap to maximum likelihood decoding.

Recently a number of nonlinear precoding algorithms have been developed for designing a downlink transmit signal that is constrained by some nonlinearity, such as one-bit quantization, power-amplifier saturation or constant modulus. These methods use iterative search algorithms to directly design the signal that is transmitted from each antenna. Since the dimension of the search space equals the number of antennas, the computational complexity of these approaches can be high for massive MIMO scenarios. Thus, in this paper we pose the problem in a smaller dimensional space by constraining the signal prior to the nonlinearity to be the output of a linear precoder. The search is then over the vector of predistorted symbols at the input to the linear precoder, which is typically much smaller than the number of antennas. We focus on algorithms that minimize the bit error rate at the receivers, and show that performance can be obtained that is similar to algorithms that operate directly in the antenna domain.

Linear precoders have been shown to perform reasonably well at low SNR when the basestation of a MIMO downlink employs one-bit digital-to-analog converters to quantize the precoder outputs. However, at medium-to-high SNRs, an error floor is encountered due to the coarse quantization. This paper examines methods for slightly perturbing the transmitted signal prior to quantization in an effort to improve downlink performance at higher SNRs. The perturbation is performed with the goal of minimizing the worst-case probability of error among the user terminals, and assumes that the symbols to be transmitted are drawn from a finite alphabet constellation. Two different types of perturbations are studied, and it is found via simulation that the methods can provide dramatic gains in downlink performance.

Channel state information (CSI) is essential for efficient power and spectrum allocation policies. In cognitive radio (CR) channels, although perfect CSI of the direct link (between the secondary transmitter and the secondary receiver) is a reasonable assumption at the secondary transmitter (ST), however, perfect knowledge of its interfering links to the primary receivers (PRs) is not. Power allocation and scheduling algorithms are often based on perfect global CSI at the secondary transmitter (ST). In this paper, we analyze the impact of channel estimation errors on both the secondary and primary users. On the one hand, the robustness of water-filling type of algorithms allowing the secondary user (SU) to minimize its power consumption under QoS and CR interference power constraints to channel estimation errors in the SU interfering links is analyzed. On the other hand, the impact of these estimation errors on the PU interference constraints is also analyzed. To this aim, we consider the worst case with respect to these estimation errors. Our analysis shows that the water-filling algorithm provides robustness in terms of power consumption and scheduling of the SU given the realistic estimation error models especially when the SU is overestimating the interfering power gains. We also provide possible solutions to ensure that the created interference is below the tolerated thresholds.

User mobility has become a key attribute in the design of optimal resource allocation policies for future wireless networks. This has become increasingly apparent in cognitive radio (CR) systems where the licensed, primary users (PUs) of the network must be protected from harmful interference by the network's opportunistic, secondary users (SUs): here, unpredictability due to mobility requires the implementation of safety net mechanisms that are provably capable of adapting to changes in the users' wireless environment. In this context, we propose a distributed learning algorithm that allows SUs to adjust their power allocation profile (over the available frequency carriers) “on the fly”, relying only on strictly causal channel state information. To account for the interference caused to the network's PUs, we incorporate a penalty function in the rate-driven objectives of the SUs, and we show that the proposed scheme matches asymptotically the performance of the best fixed power allocation policy in hindsight. Specifically, in a system with S orthogonal subcarriers and transmission horizon T, this performance gap (known as the algorithm's average regret) is bounded from above as O(T-1logS). We also validate our theoretical analysis with numerical simulations which confirm that the network's SUs rapidly achieve a “no-regret” state under realistic wireless cellular conditions. Moreover, by finetuning the choice of penalty function, the interference induced by the SUs can be kept at a sufficiently low level, thus guaranteeing the PUs' requirements.

Optimal parameter estimation requires simultaneous processing of all available measurements. The complexity of this task may become too large when measurements from two or more multimodal sensor networks are available. In such cases, fusion of estimates obtained from each data set separately may be practical. In this paper, we derive the optimal linear combination of the possibly non-linear estimators, and propose sub-optimal weightings. We analyze the asymptotic performance gain of the first sub-optimal approach with respect to the individual optimal estimates. The theoretical results are supported by simulations.

In this paper we present an original way to simplify the architecture of a frequency synthesizer for the 3.1-10.6 GHz band. On the basis of measurement results, obtained by a produced CMOS prototype, the architecture performances are analyzed. As spur frequencies are inevitably generated, we propose to apply an interferences reduction method at the receiver. This solution allows meeting the MultiBand OFDM (Orthogonal Frequency Division Multiplexing) requirements, despite the imperfect spectrum of the generated frequencies and allows simplifying the synthesizer's structure, limiting the use of band-pass filters.

This paper investigates the classification of photographic paper textures using visual descriptors. Such classification is called fine grain due to the very low inter-class variability. We propose a novel image representation for photographic paper texture categorization, relying on the incorporation of a powerful local descriptor into an efficient higher-order model deviation where texture is represented by computing statistics on the occurrences of specific local visual patterns. We perform an evaluation on two different challenging datasets of photographic paper textures and show such advanced methods indeed outperforms existing descriptors.

In this paper, we analyze the optimal blockwise subcarrier allocation scheme in coded Orthogonal Frequency Division Multiple Access (OFDMA) uplink systems without channel state information at the transmitter side. Due to the Discrete Fourier Transform, the subcarrier gains in OFDMA systems are correlated and this correlation plays a determinant role since it causes a degradation of the transmission performance. As a consequence, there exist some subcarrier allocation schemes which are preferable to achieve higher diversity gains. We propose the minimization of an inter-carrier sum-correlation function defined as the sum of correlations of each subcarrier with respect to the others in the same allocation scheme. We show the robustness of the proposed blockwise allocation policy to the effect of carrier frequency offsets (CFO). Moreover, we propose the block-size which provides the best trade-off between diversity and CFO for practical values of CFO. Finally, numerical simulations validating our results are presented.

In OFDMA, the total available subcarriers are assigned to different users for simultaneous transmission. In case of an unsynchronized uplink OFDMA, each user has a different carrier frequency offset (CFO), which results in loss of orthogonality among subcarriers and causes severe intercarrier interference. In this paper, a self- successive interference canceller (self-SIC) algorithm is proposed for uplink OFDMA systems to mitigate both the self-intercarrier interference and multiuser interference resulting from carrier frequency offsets. We show that for a carrier allocation with larger blocksizes, the proposed compensation algorithm significantly reduces the implementation complexity without performance degradation.

In this paper, we propose, analyze and compare three different methods for opportunistic spectrum sharing access when the primary users implements an Incremental Redundancy (IR) type Hybrid Automatic ReQuest (H-ARQ) protocol. The first method consists in allowing the secondary user to communicate only during the first primary transmission round of the IR H-ARQ protocol. In this scenario, if the the secondary receiver fails to decode its message after the first round, it realizes a successive interference cancellation in the subsequent primary HARQ rounds by listening to the primary user. The second method consists in realizing a perfect interference cancellation at the secondary receiver with causal channel state information. In this method, the secondary user communicates only when the secondary receiver succeeds in decoding the primary message.To improve throughput performance at the secondary, the secondary pair is also considering the use of an IR-HARQ protocol. In a third method, the secondary user communicates following the same rule as in the proposed second method, but implementing an Adaptive Modulation and Coding scheme instead of HARQ. In particular, we show that this last protocol with a small number of interfered slots allows to limit the loss in the primary throughput needed for the secondary user to transmit.

In this paper, we are interested in resource allocation strategies for wireless time-hopping ultra-wide band (TH-UWB) communications with multiple rate capabilities between users. Multiple rates are achieved by assigning different processing gains, i.e. Nf, to users. For this purpose, the multiple-access interference (MAI) variance accounting for multi-rate is needed. It is a challenging task due to the lack of a suitable closed-form expression for the MAI variance in a multi-rate context. We further study the multi-rate resource allocation problem in uplink TH-UWB systems for which an optimal search cannot be envisaged due to the exponential complexity induced. Our contribution lies in three-fold: i) A new intercode correlation expression accounting for multi-rate communications is derived, and the variance of the MAI averaging over the codes is obtained. ii) The multi-rate resource allocation problem is tackled by relaxing the integer constraint on the processing gains and modeled via a signomial programming problem. iii) Based on this, a branch and bound (BB) algorithm is derived for the allocation of the processing gains in TH-UWB systems. We also propose a really simple heuristic with linear complexity for the Nfallocation. We show that the algorithm proposed outperforms the BB algorithm in average throughput and average starvation rate.

In this paper, we investigate the effect of subcarrier allocation on the CFO for uplink OFDMA systems. Carriers are allocated to the users in order to get maximum throughput by making use of the channel frequency diversity. But in systems with CFO, while allocating the carriers to the users, attention must be paid to the ICI resulting due to CFO. In this paper we propose a carrier allocation scheme that provides a good compromise between the throughput maximization and robustness to the CFO induced ICI for systems with and without channel state information (CSI).

In this paper, we propose a joint estimation method of carrier frequency offsets (CFO) and channel impulse responses (CIR) for an uplink OFDMA system. We consider the CFOs come into play from the emitters due to frequency mismatch between the terminals and base station oscillators. We also take into account the cyclic prefix to derive a new model of the received signal.

In this paper, we consider the source-channel rate allocation for different transmission schemes. We propose a new trellis structure and a new algorithm that are able to deal with both variable length packet and fixed length packet problems. The trellis description allows to handle any kind of transmission schemes and can therefore be applied to Bit Interleaved Coded Modulations (BICM), parallel channels or Hybrid-Automatic Repeat reQuest (HARQ).

In this paper, an efficient rate allocation scheme to maximize the throughput in uplink multi-rate time-hopping ultra-wideband (TH-UWB) communications is proposed. This is a challenging task due to the lack of a suitable closed form expression of the multiuser interference in a multi-rate context. Moreover, an exhaustive search for the optimal solution would be too prohibitive due to the high complexity induced. Our contribution can be summarized as follows: i) A new expression of the multiuser interference variance accounting for multi-rate communications is proposed. ii) Thanks to this, a computational efficient multi-rate allocation scheme is proposed. The algorithm allows to achieve high throughput while keeping a relatively low starvation rate and it outperforms a Max-Min algorithm with a fix rate for all users. Moreover, the simulations based on the theoretical analysis give insights on the influence of the different UWB parameters on the global throughput.

Orthogonal Frequency Division Multiplexing (OFDM) is very sensitive to carrier frequency offsets (CFO). The CFO results in intercarrier interference (ICI). This drawback of OFDM is inherited to Orthogonal Frequency Division Multiple Access (OFDMA). In this paper, we propose a new ICI model for an uplink OFDMA system that takes into account the presence of the cyclic prefix which is usually ignored. Simulations validate the accuracy of our derivation. The subcarrier allocation is revisited in the presence of CFO.

This paper addresses the spectrum-sharing for wireless communication with a licensee-primary and a secondary users interfering with each other. We propose a new practical power control policy for the secondary user, under outage performance requirements for both users, with partial knowledge of channel state information.

This paper presents a link adaptation strategy for non-binary LDPC code over a time-variant frequency-selective channel. The algorithm is based first on the adoption of waterfilling technique to wisely adapt the transmitted power. It is shown that as long as best subchannels are identified with the waterfilling algorithm, an equal power distribution can be applied with performance comparable to the ideal power adaptation. What it is more important is to decide which are the subchannels that should not be used in order to increase the energy efficiency of the system. The throughput is increased with the adoption of multilevel modulations that changes the rate of each subchannel depending on the channel-to-noise ratio and the quality of service required. The Galois Field GF(64) code symbols are mapped into four modulation schemes (BPSK, 4QAM, 16QAM, 64QAM) and the channel is assumed to be constant over six OFDM symbols. Simulation results are presented when a perfect channel state information is available at the transmitter and at the receiver side. In real dynamic channel environments, the performance of the system degrades due to the delay and the approximation of the feedback information. Simulation of partial channel state information scenario is also reported.

In this paper, we present a simple and effective precoding technique to mitigate inter-symbol interference from multiple transmissions of the same packet in automatic repeat request (ARQ) protocols over slowly time-varying frequencyselective channels. We minimize the power of inter-symbol interference by introducing phase-precoding transmission diversity among subsequent ARQ transmissions. For each packet retransmission, only the phases of the modulated symbols are changed according to a specific pattern. In order to find the best precoding phases assuming that no channel state information is available at the transmitter, we first derive a performance criterion on the precoding phases for a maximum likelihood receiver. Then, we propose a low complexity periodic precoding solution. Simulation results show that the proposed precoding scheme provides a substantial gain in terms of frame error rate performance of the joint detector without significant increase in receiver complexity, leading to enhanced throughput efficiency and better dropping rate in comparison with the non-precoded system.

In a frequency selective channel for wireless applications, we provide a new resources allocation procedure that enables the transmission of scalable images in accordance with end-to-endQualityofService(QoS) constraints. This scheme is based on anUnequalErrorProtection(UEP) policy with the possible truncation of the source data layers (after the source coding stage) and an optimal use of the available resources for each layer (with local flattening over the channel portion). The proposed algorithm is applied to the transmission of JPEG-2000 scalable images over an OFDM channel. We analyze the performance of our method in term of perceived quality and speed, and show better results than State-Of-The-Art UEP schemes.

In this paper, we investigate the use of cyclic frequency diversity (CFD) scheme for single-carrier packet retransmission over frequency-selective channels in the context hybrid automatic repeat request protocols (HARQ). For each retransmission of the same packet, the transmitted signal is cyclically shifted in the frequency-domain in order to compensate for channel fading over a part of the channel bandwidth in the previous transmissions. We consider efficient frequency-domain equalization based on the minimum mean square error (MMSE) criterion. We determine an optimal solution for frequency-shift values in order to maximize system throughput by maximizing the signal to interference-plus-noise ratio (SINR) at the output of the joint MMSE equalizer. The CFD scheme has low complexity and provides a substantial gain in terms of frame error rate, especially for high rate channel coding.

In this paper, we address the problem of optimization of the training sequence interval for MIMO (Multiple- Input Multiple-Output) flat fading channels when an iterative receiver composed of a likelihood generator and a Maximum A Posteriori (MAP) decoder is used. At each iteration of the receiver, the channel is estimated using the hard decisions on the transmitted symbols at the output of the decoder. The optimal length of the training interval is found by maximizing an effective signal-to-noise ratio (SNR) taking into account the data throughput loss due to the use of pilot symbols.

Direct-conversion architectures suffer from the mismatch between the in-phase (I) and the quadrature-phase (Q) branches, commonly called I/Q imbalance. Even low I/Q imbalances imply poor performance of orthogonal frequency division multiplexing (OFDM) systems. In this paper, we propose a new algorithm that uses both training and data symbols in a decision-directed fashion to jointly estimate the channel and compensate for high receiver I/Q imbalance. Simulation results show that our method can compensate for high I/Q imbalance values and also estimate a frequency selective channel.

In this paper we investigate the Euclidean distance distribution in turbo-equalized systems over static frequency-selective (ISI) channels . We propose a novel approach in evaluating the squared Euclidean distance between transmitted sequences at the output of the ISI channel based on the correlogram of error sequences. By inspecting autocorrelation properties of error sequences, we derive the main statistics of the output Euclidean distance. The proposed method provides a more comprehensive tool to predict system behavior with finite or infinite packet length. We exploit obtained results to evaluate the frame error rate (FER) performance of the system under maximum-likelihood sequence estimation.

Wireless applications are subject to the end-to-end quality of service (QoS) requirements. This paper presents a new resources allocation algorithm that allows to transmit scalable multimedia data over a frequency selective channel with partial channel knowledge. The available resources are subject to payload and QoS constraints and the algorithm aims at maximizing the transmission robustness to channel estimation errors. The impact of this technique is evaluated for a MPEG-4 audio application.

Consider the problem of base-station and sub-carrier assignment on the downlink of a two-cell OFDMA system with adaptive modulation. The aim is to maximize a common data rate that can be offered to each user with a guaranteed maximum rate-outage probability. A target bit-error rate is also guaranteed with a maximum outage probability. The channel model takes into account the propagation path-loss in addition to log-normal shadowing and Rayleigh fading. The channel-state information available about each user corresponds to the shadowed path-loss that we define. We use the well-known frequency-reuse partitioning as an inter-cell interference mitigation technique. We suggest a simple threshold-based method for optimizing the reuse scheme. This method allows us to transform the considered optimization problem into a tractable one that we resolve numerically. Simulation results allows us to validate the proposed method and to compare the average achieved performance to that obtained with static BS-assignment and/or static frequency-reuse scheme.

Consider the problem of resource allocation on the downlink of a cellular OFDMA system. A fairness constraint is defined by a minimum data rate, a maximum bit-error rate and a maximum outage probability. This paper proposes a low-complexity resource allocation algorithm that requires a reduced feedback-overhead. Under a partial channel-state information, we derive the optimal subcarrier and power allocation that provides the best overall outage performance using the lowest possible number of subcarriers. Unneeded subcarriers lend themselves to interference-free use in other cells assuming some inter-cell coordination.We first evaluate the maximum achievable number of users when all subcarriers are used. This defines an upper-bound on system load. Then, for an arbitrary load ratio, we describe the corresponding resource allocation and provide an analytic upper-bound on the achievable outage probability.

In this paper, we present an effective phase precoding diversity scheme to mitigate intersymbol interference from multiple transmissions in hybrid automatic repeat request (HARQ) protocols over slowly time varying frequency-selective channels. For each HARQ transmission, only the phases of modulated symbols are changed according to a periodic pattern. This diversity scheme results in a spectrum thinning of the Euclidean distance at the output of the noiseless ISI channel. Periodic phase precoding only requires a small increase in receiver complexity but provides a substantial gains in terms of frame error rate.

This paper presents the project ldquourban planning for radio communicationsrdquo which is part of ldquoSystem@ticrdquo Paris-Region Cluster, one of the French Lt pole of competitiveness Gt initiative. We present first an overview of the project which deals with spectrum scarcity issues in crowded cities. We browse the different technical aspects addressed in the project and the corresponding challenges. We then present, as an example, the recent results of two particular topics studied in the project: one related to the system architecture dealing with the radio enabler concept and the other one related to radio access about hybrid ARQ.

Minimum rate maximization (MRM) is a link adaptation strategy that guarantees a minimum quality of service, in terms of instantaneous signal-to-interference-plus-noise ratio, to all users in a DS-CDMA system. This is achieved by power and rate allocation that maximizes the minimum user information rate. As MRM resource allocation relies on knowledge of the channel coefficients, the achievable quality of service suffers from a degradation when the channel is dynamic and imperfectly estimated. The purpose of this paper is to add auto-regressive channel prediction to compensate for the Doppler-induced channel time-variations and improve the performance of the MRM strategy

In this paper, we propose a method based on the modification of the channel noise variance at the equaliser input in order to improve the performance of a turbo-equaliser. We will show a relation between the modified channel noise variance and the a priori information statistics. The simulation are done for 2 types of turbo-equalisers.

This paper presents the impact of the high-frequency memory of a non-linear amplifier on a multi-carrier (OFDM) transmission and an original, yet very simple, method to compensate for it directly at the transmitter. Our method is efficient thanks to the usage of a long enough cyclic prefix, as in actual OFDM systems.

In the context of DS-CDMA transmissions, we study the average performance of a link adaptation strategy performed through dynamic rate and power adaptation based on the minimum user information rate maximization subject to a target bit error rate for erroneous frames. Analytical expressions and bounds for the average information rate per user are derived when a Rayleigh fading environment is assumed. When compared to a link adaptation strategy based on the total throughput maximization, simulation results show improved performance, supporting more users in the cell for a wide range of channel conditions.

This paper describes the optimization of LDPC codes for unequal error protection (UEP) transmission schemes. The method is based on a hierarchical optimization of the irregularity for each class within the codeword by maximizing the average data node degree with a given error sensitivity at a finite number of decoding iterations.

This paper addresses the design and performance of time-recursive receivers for diversity based communication systems with flat Rayleigh or Ricean fading. The paper introduces a general state-space model for such systems, where there is temporal correlation in the channel gain. Such an approach encompasses a wide range of diversity systems such as spatial diversity, frequency diversity, and code diversity systems which are used in practice. The paper describes a number of noncoherent receiver structures derived from both sequence and a posteriori probability-based cost functions and compares their performance using an orthogonal frequency-division multiplex example. In this example, the paper shows how a standard physical delay-Doppler scattering channel model can be approximated by the proposed state-space model. The simulations show that significant performance gains can be made by exploiting temporal, as well as diversity channel correlations. The paper argues that such time-recursive receivers offer some advantages over block processing schemes such as computational and memory requirement reductions and the easier incorporation of adaptivity in the receiver structures.

We derive a low complexity turbo-detector for coded asynchronous DS-CDMA over frequency selective channels. Our detector is a suboptimal variant of the MAP algorithm based on state-reduction and per-survivor processing. In order to reduce the loss due to state-reduction, we propose to use, as a prefilter for the turbo-detector, a multidimensional whitened matched filter (WMF) which leads to a white-noise "minimum phase" channel model. Simulation results show that the use of the WMF yields significant improvement. Thanks to the iterative turbo processing (detection and decoding are iterated several times), the performance loss due to the use of the suboptimum List-type equalizer is in part recovered.

We propose a decoder for low-complexity equalization of coded frequency selective multiple-input multiple-output channels. The decoder combines parallel decision feedback decoding (PDFD) and the list-type approach. This alternative achieves a good trade-off between performance and complexity even when the channel is not minimum phase.

We propose a new structure for blind equalization with spatiotemporal diversity at the receiver (SIMO system). This structure is derived from the Wiener filter. It is composed of a prefilter deduced from the data spectral density (no blind criterion is needed) and a FIR filter, independent of the noise level, to be obtained blindly. The new prefilter is robust to a total lack of effective diversity and benefits from any available diversity. Simulations show that this new blind equalizer performs similarly to the Wiener filter even with a very small amount of data.

We investigate a sub-optimal iterative receiver for joint equalization and decoding called a turbo-equalizer. We view the evolution of the error variance of the transmitted symbols through iterative processing, obtaining the convergence analysis. This allows us to predict the asymptotic performance (when the turbo-equalizer has converged) but also the trigger point observed in its performance.

We examine the use of a blind adaptive "pre-whitening" filter to precede an equalizer adapted by the constant modulus algorithm (CMA). The idea is based on results presented in which the use of a (fixed, or non-adaptive) pre-whitening filter provides an isometry (i.e. geometry preserving transformation) between the combined channel-equalizer (or global space) and the equalizer tap space. As much analysis found in CMA literature is done in "global space" now applies to the pre-whitened "equalizer tap space", considerable exploitation of a known geometric structure is now possible. This paper's main result demonstrates a method for improving the convergence rates of CMA adapted equalizers using the results of pre-whitening analysis. The slow convergence of CMA equalizers is a common negative point associated with this well-known, robust blind equalization algorithm.

Sub-optimal joint equalization and decoding is performed by iterated equalization and decoding. This processing is named turbo-equalization with reference to the turbo-decoding of serially concatenated codes. We propose to optimize the equalizer structure (an interference canceler) thanks to the training sequence available to estimate the channel impulse response. The interference canceler, optimized at each iteration, permits one to reduce the number of iterations needed to achieve a given performance. The gain is all the more important that the channel is hard to equalize.

A low-complexity and iterative receiver is proposed for the CDMA uplink, consisting of a low-complexity equalizer and single-user decoders. Iterations are used to feed the equalizer with more reliable data, which improves performance. This receiver called turbo-CDMA is aimed to eliminate MUI almost completely in the presence of multipath and to be robust to the near-far effect. Simulation results show that the performance approaches single-user performance at moderate and also low signal-to-noise ratios, even for a severe distortion channel.

In this paper, we consider the problem of blind detection of DS-CDMA signals in a multipath, asynchronous context (up-link transmission). We show that blind source extraction techniques provide a general framework but must be constrained to ensure the detection of the source signal corresponding to a given spreading sequence. First, we provide an original analysis of the constrained methods derived from the work of Tsatsanis (1997), unifying all these approaches and showing their limitations in multipath propagation. Second, we also propose a complete multiuser detection system based on the constant modulus algorithm, in the case of large channel dispersion (more than one symbol period).

The performance of equalizers depends on the discrete time model of the input signal and noise. The use of a higher sampling rate results in colored noise when the bandwidth of the noise-limiting prefilter is not sufficiently large. It is shown that the mean square error (MSE) performance of linear equalizers becomes sensitive to the decision delay when the input noise is colored, and by using the appropriate delay, a significant improvement in the MSE can be achieved. This is in contrast to the behaviour observed in the white noise case well known in the literature. This behaviour is explained in time domain by showing the contributions to the MSE from the columns of the channel convolution matrix and the noise eigenvectors. In the frequency domain, it is shown that the equalizer exploits the noise correlation to improve the MSE.

Existing methods for blind channel equalization that explicitly use channel diversity lead either to estimation of a single equalizer (without control of the transmission delay) like linear prediction or to estimation of all equalizers associated to every possible input/output delay. In this contribution we propose a novel solution based on second order statistics that allows estimation of an equalizer with a pre-selected delay, implying a priori control of the MSE performance.

The improved convergence speed and tracking properties of fractionally-spaced equalizers are analyzed. We consider in particular the effect of a frequency offset between the transmitter baud rate and the receiver sampling clock that induces important time-variations. We show that a fractionally-spaced equalizer can handle the intersymbol interference (ISI) induced when the propagation channel does not introduce too much ISI.

We address the deconvolution of MIMO linear mixtures. The approach is based on the construction of a hierarchical family of composite criteria involving CM criterion and second order statistics constraint. Although, the criteria are based on fourth order statistics, we give a complete proof of convergence of this structure. We show that each cost function leads to the restoration of one single source. Moreover the approach is naturally robust with respect to the channels order estimation. An adaptive algorithm is derived for the simultaneous estimation of all sources.

We address the comparison of sub-space (SS), linear prediction (LP) and constant modulus (CM) identification/equalization algorithms in terms of robustness to loss of fractionally-spaced channel disparity. We show that SS procedure leads to an inconsistent channel estimation. Investigating a left-inverse channel estimation, we show that LP results in the estimation of the so-called minimum-phase multivariate channel factorization. We show that the CM criterion still perform reasonable channel estimation, even if proper algorithm initialization is still a critical subject.

The constant modulus algorithm (CMA) is a popular blind equalization algorithm. A common device used in demonstrating the convergence properties of CMA is the assumption that the source sequence is i.i.d. (independent, identically distributed). Previous results in the literature show that a finite length fractionally-spaced equalizer allows for perfect equalization of moving average channels (under certain channel conditions known as zero-forcing criteria). CMA has previously been shown to converge to such perfectly equalizing settings under an independent, platykurtic source. This paper investigates the effect of the distribution from which an independent source sequence is drawn on the CMA error surface and stationary points in the perfectly-equalizable fractionally-sampled equalizer case. Results include symbolic identification of all stationary points, as well as the eigenvalues and eigenvectors associated with their Hessian matrix. Results show quantitatively the loss of error surface curvature (in both direction and magnitude) at all stationary points. Simulations included demonstrate the affect this has on convergence speed.

In the noise-free case, fractionally-spaced equalization by constant modulus algorithm (FSE-CMA) was shown to be robust to the channel identifiability condition. The effect of additive channel noise on FSE-CMB steady-state behavior is analyzed in terms of the perturbation of the equalizer convergence settings with respect to the convergence settings of the noise-free case. The loss of performance is characterized by the additional residual mean square error induced by the noise. We show that, in noisy conditions, FSE-CMA exhibits an interesting "smoothing effect" that leads to a trade-off between zero forcing (ZF) equalization and output noise enhancement (NE). We also show that the main loss is due to the NE and not to residual intersymbol interference.

Under certain conditions on the equalizer length and on the channel dynamics, temporal or spatial diversity allows one to achieve blind equalization perfectly by means of second-order statistics only. Loss of channel disparity causes perfect equalization to no longer be achievable. The achievable channel-equalizes combination then depends only on the part of the multichannel transfer function lacking disparity. We show that the fractionally spaced equalizer adapted by the constant modulus algorithm (FSE-CMA) still achieves "reasonable" equalization. Its performance equals that of the non-fractional CMA, with a slightly shorter baud-length equalizer than the FSE, applied to the part of the channel lacking disparity.

CMA fractionally spaced equalizers (CMA-FSEs) have been shown, under certain conditions, to be globally asymptotically convergent to a setting which provides perfect equalization. Such a result relies heavily on the assumptions of a white source and no channel noise (as is the case in much of the literature's analysis of CMA). Herein, we relax the white source assumption and examine the effect of source correlation on CMA. Analytic results are meshed with examples showing CMA-FSE source correlation effects. Techniques for finding all stationary and saddle points on the CMA-FSE error surface are presented using recent developments in the algebraic-geometry community.