Tensor-based modulation (TBM) provides a multi-linear spreading framework for blind multi-user separation in unsourced random access. In this paper, we show that TBM is a coded modulation built on a non-binary linear block code over $\mathbb{Z}_M$, whose symbols are mapped to $M$-PSK modulation, defining a geometrically uniform signal space code. We explicitly derive this generator matrix, characterize its rank deficiency, and show that reference symbols for tensor identifiability correspond to code shortening, producing a quasi-systematic or a systematic code, depending on the number of considered reference symbols for the TBM. Simulations in single-user AWGN and multi-user non-coherent multi-antenna fading channels demonstrate strong robustness and interference resilience, establishing TBM as a scalable, algebraically structured modulation-coding scheme bridging tensor representations and modern coding theory.

The joint use of Soft-Input Soft-Output (SISO) detectors and channel decoders in an iterative manner has received growing attention for Multi-User Multiple-Input Multiple-Output (MU-MIMO) transmission schemes since several years, as it has been shown to operate close to fundamental limits, at least asymptotically. Amongst SISO detectors, message passing algorithms such as Vector Expectation Propagation (VEP) proved to outperform significantly linear detectors such as Linear Minimum Mean Square Error (LMMSE). Aside from its higher computational complexity, turbo VEP receivers rely on different hyper-parameters that can be optimized.In this context, we propose a joint optimization through deep-unfolding of the hyper-parameters that naturally arise in this kind of doubly iterative turbo VEP receivers. One of the difficulties arising for this type of receiver is when and how to choose between an extrinsic or an A Posteriori (APP) information feedback within the turbo receiver. The optimal selection is shown here to depend on the type of the considered SISO components. By properly choosing the hyper-parameters to be optimized, we show that deep-unfolding can naturally optimize the trade-off between extrinsic and APP information feedback and bring performance gains.

Multi-User Multiple-Input Multiple-Output (MU-MIMO) communication systems have gained significant attention due to their potential to enhance spectral efficiency and improve overall system performance. Soft-Input Soft-Output (SISO) detectors and decoders for iterative algorithms are commonly employed for the estimation of transmitted bits in such system. Message passing SISO detectors such as Vector Expectation Propagation (VEP) have demonstrated significant superiority over linear detectors such as Linear Minimum Mean Square Error (LMMSE) at the cost of higher computational complexity. SISO receivers rely on different hyper-parameters that can be optimized. In this article, we propose a modification of Gated Recurrent Unit (GRU), a type of neural network architecture from the Recurrent Neural Networks (RNN) field, suitable to learn hyperparameters of unfolded SISO iterative algorithms for multi-user MIMO communications. Our proposed algorithm outperforms both non-learned and state-of-the-art unfolded algorithms with a fair complexity increase.

In the context of the Gaussian linear model, recent works have studied factor graph modification using QR decomposition that enables the derivation of scalar Expectation Propagation (EP) based detectors. In this paper, we investigate on new factor graph representations induced by the use of the Golub-Kahan bi-diagonal Decomposition (GKD) and of the Singular Value Decomposition (SVD). New EP messages induced by the GKD or SVD underlying graphs are derived, that can be both scalar or vector messages. Complexity and performance of the resulting algorithms are studied for digital communications applications.

This work presents low-density parity-check (LDPC) codes with low error floors, close to capacity performance and highly efficient encoders targeting high throughput applications such as free-space optical downlinks from low earth orbit (LEO) satellites to ground. We devise a code design strategy to find suitable protograph LDPC code ensembles and discuss an field-programmable gate array (FPGA) implementation of the obtained codes. In addition to having competitive decoding performance, the proposed codes have advantages in terms of encoding complexity. An FPGA prototype highlights significant improvements in resource utilization by a factor of around 10 compared to standardized DVB-S2 and CCSDS solutions.

Existing error correcting schemes approaching the capacity of orthogonal modulations are mainly resorting to optimized bit-interleaved coded modulation (BICM) schemes with mandatory iterative decoding or to non binary coded coding schemes for which the field order is matched to the modulation order. The latter approach is efficient especially for short codeword lengths but suffers from a high complexity for high modulation orders. In this paper, we study properties of multi-level coding (MLC) schemes for high order orthogonal modulations and propose to consider non binary MLC to naturally address layer reduction. Design of non binary LDPC codes for non binary MLC is then investigated for both the Gaussian and Rayleigh fading channels showing good performance in both asymptotic and finite length regimes.

A new class of doubly-generalized LDPC codes over extended code alphabets has been recently proposed in [1]. These codes have been shown to have good asymptotic and minimum distance properties in the range of high code rates, and their structure is solely based on non-binary repetition and parity-check component codes. In this work we go further in the investigation of the new code class, called Repetition-parity-Parity (RPP) in the rest of the paper, by extending the definition of [1] to irregular degree distributions. One performs the asymptotic decoding analysis of the RPP ensemble over the binary erasure channel and formulates a degree distribution optimization problem by means of an approximated EXIT analysis. Some insights on the stability, minimum distance properties and low complexity encoding and decoding of RPP codes have been also developed.

This paper studies new geometrically shaped circular quadrature amplitude modulation (CQAM) constructions that can approach the Gaussian capacity. Then, we compare the performance of obtained constellations with existing Gaussian shaping strategies for regular and some simple optimized non-binary protographs. We also investigate the potential benefit of additional probabilistic shaping on the proposed CQAMs.

In this paper, we investigate on bit-interleaved chirp spread spectrum (CSS) coded modulations with iterative decoding (ID) based on low-density parity-check (LDPC) codes. First, we study coded modulation (CM) and bit-interleaved coded modulation (BICM) capacities of CSS based LoRa-like waveforms over Gaussian and Rayleigh fading channels for both coherent and non-coherent receivers. LoRa-like waveforms being by essence nonlinear nonbinary memoryless continuous-phase modulations, this study shows that optimized BICM schemes with iterative decoding are mandatory to close the non negligible gap to the CM capacity when outer binary error-correcting schemes are used. Then, we design LDPC codes, optimized for BICM-ID CSS modulation schemes using both coherent and non coherent receivers. In particular, we show that one has to be careful when using optimized codes for the different regimes. Indeed, unstructured LDPC codes optimized for the coherent regime may be asymptotically non stable when used in the non coherent regime. On the contrary, optimized codes for the non coherent case are always stable in the coherent regime with negligible to fair loss of performance. Finally, designed sparse-graph based BICM-ID CSS modulation schemes show significant performance improvement over classical or advanced LoRa legacy CSS waveforms at finite length.

In this study, we intend to make an in-depth investigation of the performance-complexity trade-off of low complexity Multiple-Input Multiple-Output (MIMO) signal detection based on message passing algorithms. Several detection algorithms such as Belief Propagation (BP) and Expectation Propagation (EP) have been proposed to approximate symbol Maximum A Posteriori (MAP) for high dimensional signaling. We propose a thorough examination of those algorithms and some of their low-complexity versions, through a complexity/performance trade-off analysis to identify modes of operation depending on the number of antennas and constellation order. Finally, we propose a new simplified BP detection scheme, which combines the advantages of QR precoding and Interference Cancellation (IC).

Earth observation through satellite images is crucial to help economic activities as well as to monitor the impact of human activities on ecosystems. Current satellite systems are subjected to strong computational complexity constraints. Thus, image compression is performed onboard with specifically tailored algorithms while image denoising is performed on the ground. In this letter, we intend to address satellite image compression and denoising with neural networks. The first proposed approach uses a single neural architecture for joint onboard compression and denoising. The second proposed approach sequentially uses a first neural architecture for onboard compression and a second one for on ground denoising. For both approaches, the onboard architectures are lightened as much as possible, following the procedure proposed by Alves de Oliveiraet al.(2021). The two approaches are shown to outperform the current satellite imaging system and their respective pros and cons are discussed.

The maximum a posteriori (MAP) threshold corresponds to the fundamental limit that one can hope to achieve with the given channel code ensemble. Apart from theoretical interests, finding this limit is also desirable sincespatial-coupledcode ensembles approach this MAP threshold due to phenomenon termed asthreshold saturation. However finding this MAP threshold, in general, is known to be computationally prohibitive. This work proposes a tractable method for estimating the MAP threshold for various families of sparse-graph code ensembles over non-binary complex-input additive white Gaussian noise (AWGN) channel. Towards this, we provide a method to approximate the extended belief propagation generalized extrinsic information transfer (EBP-GEXIT) chart and estimate the MAP threshold by applying theMaxwell constructionto it. To illustrate the validity of our method, we study spatial coupling for serially-concatenated turbo-codes and numerically observe threshold saturation of these codes to the MAP thresholds estimated via our method.

A compact and closed-form expression of capacity is derived for an uplink multiband satellite system in the presence of nonlinear interference. The nonlinear effect comes from the satellite high-power amplifier modeled by a Volterra series expansion. The derivations reveal that the nonlinear interference can provide a constructive power contribution that could be used to increase the transmission rate. Consequently, decoders designed by viewing this interference as only an additional noise are suboptimal. Numerical results confirm this claim and also show that an appropriate power allocation amongst the subbands may be of interest.

In this paper, a new class of doubly-generalized LDPC codes is proposed. The particular point of the proposed construction is the presence of a small fraction of single parity-check codes at the variable nodes side. Together with the use of extended alphabets, the existence of such a fraction has been shown to improve the asymptotic decoding threshold, without harming the minimum distance behaviour of the code ensemble. Note that the improvement is more significant in cases where the code initially contains check nodes of high degrees, which corresponds to the region of moderate and high code rates.

In this paper, a novel category of expectation propagation (EP) based frequency domain (FD) semi-blind receivers are proposed for single-carrier block transmissions. A recently proposed EP-based framework for deriving double-loop turbo detectors is extended to handle joint data-aided channel estimation along with EP-based soft interference cancellation (IC). When addressing this problem in a message passing framework, an unconventional probability density function prevent us from establishing analytical update functions for estimating data and channel estimates. This is solved with variational inference methods, such as mean-field (MF), expectation maximization (EM) or EP, using a three-loop receiver structure with flexible performance-complexity trade-off, thanks to fast Fourier transform (FFT) based processing.

We investigate the problem of estimating the maximum a posteriori (MAP) threshold for serially concatenated turbo codes. First, we provide a method to compute this MAP threshold using a numerical approximation of the EBP-GEXIT chart and the Maxwell construction. Second, we explore where the spatially coupled belief propagation (BP) threshold is located with respect to the previously computed MAP threshold and analyze the saturation phenomenon of such schemes. Simulation results indicate that the BP threshold of the spatially coupled turbo-codes saturates to the MAP threshold obtained using the EBP-GEXIT chart.

This paper investigates the dynamic behaviour of doubly iterative bit-interleaved coded modulation (BICM) receivers based on expectation propagation (EP). When implemented in the frequency domain, for single-carrier (SC) systems, such receivers achieve attractive performance-complexity trade-offs in quasi-static wideband channels. With this category of receivers, conventional binary extrinsic information transfer (EXIT) functions are subject to a great number of parameters, including channel realizations, constellation and inner iteration parameters. Hence, this paper proposes a novel extrinsic information evolution analysis method which simplifies the receiver's EXIT function into independent inner transfer functions. The core idea is to track state-evolution dynamics of EP through numerically stable extrinsic variance/information transfer (EXVIT) functions. Numerical results attest to the accuracy of this method for tracking the asymptotic receiver behaviour.

This paper analyzes some emerging techniques from the broad area of Bayesian learning for the design of iterative receivers for single-carrier transmissions using bit-interleaved coded-modulation (BICM) in wideband channels. In particular, approximate Bayesian inference methods, such as expectation propagation (EP), and iterative signal-recovery methods, such as approximate message passing (AMP) algorithms are evaluated as frequency domain equalizers (FDE). These algorithms show that decoding performance can be improved by going beyond the established turbo-detection principles, by iterating over inner detection loops before decoding. A comparative analysis is performed for the case of quasistatic wideband communications channels, showing that the EP-based approach is more advantageous. Moreover, recent advances in structured learning are revisited for the iterative EP-based receiver by unfolding the inner detection loop, and obtaining a deep detection network with learnable parameters. To this end, a novel, mutual-information dependent learning cost function is proposed, suited to turbo detectors, and through learning, the detection performance of the deep EP network is optimized.

In satellite communications, the non-linear distortions introduced by the amplifier in the payload have to be overcome. When advanced mitigation techniques are considered at the receiver side, the current channel model is often based on Volterra series derived from an approximation of the non linear transfer function of the on-board amplifier. This nonlinear model is conditioning the performance at the receiver side. In this paper, a new non-linear model is proposed, leading to improved receiver performances. The polynomial approximation is improved considering both the usual model truncation to the 3rd order and the signal fluctuation at the input of the amplifier. First, the impact of the polynomial order of the AM/AM and AM/PM curve approximation is studied. Then, a non-linear model is derived based on a piecewise polynomial approximation of the amplifier response. Based on this refined nonlinear model, significant detection performance improvements are shown for both Nyquist and Faster-than-Nyquist rates.

This work proposes a tractable evaluation of the maximum a posteriori (MAP) threshold of sparse-graph ensembles, by using an approximation for the extended belief propagation generalized extrinsic information transfer (EBP-GEXIT) function, first proposed by Measson et al. The approximation allows to find a MAP threshold in such numerically involved cases as the binary-input additive white Gaussian noise (AWGN) channel, graph ensembles with general component codes and/or irregularities. The paper contains examples of estimations of the MAP thresholds in the case of irregular low-density parity-check (LDPC), generalized LDPC, and doubly generalized LDPC codes ensembles. Our estimations are confirmed by numerical simulations.

A novel multiuser multiple-input multiple-output (MU-MIMO) receiver for single-carrier frequency-division multiple-access (SC-FDMA) is proposed within the expectation propagation (EP) framework. Recent advances in iterative receiver design show the ability of low complexity EP-based iterative algorithms to achieve performance close to maximum a posteriori (MAP) detection. In this paper, based on the exact derivation of frequency-domain EP-based turbo receivers, we propose a novel spectrally and computationally efficient soft interference canceller (IC) with a doubly-iterative architecture. Asymptotic and finite-length analysis show that our proposal outperforms existing schemes with comparable complexity, in various spatial-multiplexing configurations.

This paper investigates the design and analysis of minimum mean square error (MMSE) turbo decision feedback equalization (DFE), with expectation propagation (EP), for single carrier modulations. Classical non iterative DFE structures have substantial advantages at high-data rates, even compared with turbo linear equalizers-interference cancellers (LE-IC), hence making turbo DFE-IC schemes an attractive solution. In this paper, we derive an iterative DFE-IC, capitalizing on the use of soft feedback based on expectation propagation, along with the use of prior information for improved filtering and interference cancellation. This turbo iterative DFE-IC significantly outperforms turbo LE-IC, especially at high-spectral efficiency and also exhibits performance improvements over existing DFE-IC variants. The proposed scheme can also be self-iterated, as done in the recent trend on EP-based equalizers, and it is shown to be an attractive alternative to linear self-iterated receivers. For time-varying (TV) filter equalizers, an efficient matrix inversion scheme is also proposed, considerably reducing the computational complexity relative to existing methods. Using finite-length and asymptotic analysis on a severely selective channel, the proposed DFE-IC is shown to achieve higher rates than known alternatives, with better waterfall thresholds and faster convergence, while keeping a similar computational complexity.

An original expectation propagation-based message passing framework is introduced, wherein transmitted symbols are considered to belong to the multivariate white Gaussian distribution family. This approach allows deriving a novel class of single-tap frequency domain (FD) receivers with a quasi-linear computational complexity in block length, thanks to fast-Fourier transform-based implementation. This framework is exposed in detail, through the design of a novel double-loop single-carrier FD equalizer (FDE), where self-iterations of the equalizer with the demapper and turbo iterations with the decoder provide numerous combinations for the performance and complexity tradeoff. Furthermore, the flexibility of this framework is illustrated with the derivation of an overlap FDE, used for time-varying channel equalization, among others, and with the design of an FD multiple-input multiple-output detector, used for spatial multiplexing. Through these different receiver design problems, this framework is shown to improve the mitigation of inter-symbol, inter-block, and multi-antenna interferences, compared to alternative single-tap FD structures of previous works. Thanks to finite-length and asymptotic analysis, supported by numerical results, the improvement brought by the proposed structures is assessed and then completed by also accounting for computational costs.

In this paper, we provide a general framework for spatially-coupled concatenated systems. We explicit the analogy with spatially-coupled protographs and provide an adapted EXIT chart analysis. By proposing a continuous-valued coupling matrix, we propose a code design procedure for faster convergence. When considering general bit- interleaved coded-modulation scheme, we also conjecture that the spatially-coupled scheme of general detectors saturates to a value very close (lower bound) to the threshold given by the Area theorem.

In this paper, we present a new data-aided carrier-recovery method for Continuous Phase Modulation (CPM) signals over frequency-selective channels. We first present a linear model of the received signal based on Mengali representation over selective channels and show how to use it to perform joint channel and carrier-frequency estimation. We also derive a low-complexity version of the estimator. Simulation results show that this method performs better than the optimal method suited to the Additive White Gaussian Noise (AWGN) channels.

Multisymbol receiver is an effective method to demodulate noncoherent sequences. However it is necessary to correlate an important number of symbols in a noncoherent scheme to reach the performances carried out by optimal coherent Maximum a Posteriori (MAP) detectors such as BCJR. In this paper, we propose an advanced multisymbol receiver by adding some memory to the decision process. The advanced receiver, called here Multisymbol With Memory (MWM) takes into account the cumulative phase information unlike multisymbol algorithm and thus it can be seen as a truncated BCJR. An exact mathematical derivation is performed for this truncated BCJR. Then an implementation of the MWM detector applied to a continuous phase frequency shift keying modulation is presented. Finally an asymptotic analysis is carried out based on the achievable Symmetric Mutual Information rate. The proposed system exhibits good performances compared to classical multisymbol receivers at the expense of increased complexity and can approach the performances of a coherent receiver.

In this paper, we consider a bit-interleaved coded modulation scheme (BICM) composed of an error correcting code serially concatenated with a M-ary non linear modulation with memory. We first compare demodulation strategies for both the coherent and the non coherent cases. Then, we perform an asymptotic analysis and try to show that the design of coding schemes performing well for both the coherent and the non coherent regimes should be done carefully when considering sparse graph based codes such as low-density parity-check (LDPC) codes. It will be shown that optimized coding schemes for the non coherent setting can perform fairly well when using coherent demodulation, while on the contrary, optimized coding schemes for the coherent setting may lead to “non stable” coding schemes in the non coherent setting.

In order to increase the capacity of future satellite communication systems, faster-than-Nyquist (FTN) signaling is increasingly considered. The gain in terms of transmission rate is obtained at the price of significant intersymbol interference (ISI) introduction. To benefit from an improved spectral efficiency (SE), many iterative detectors have already been investigated, demonstrating the interest of such a waveform in linear and non linear channels. A thorny point in FTN signaling remains its synchronization since the usual algorithms considered in the DVB-S2X standard cannot be applied on this waveform without significant loss on the performance. This paper proposes a synchronization scheme for FTN signaling in a satellite context. It is based on a Volterra decomposition of the received signal in order to fit both with linearized and non-linearized amplifiers which can be found in the satellite payload. Two steps, initialization and tracking are considered, based on training sequences fulfilling the DVB-S2Xs frames requirements. After start of sequence detection and frequency offset correction, the channel estimation is used for time offset issue in the two proposed schemes. Their performance are compared to the performance of a perfect synchronized detection.

In this paper, we investigate coded antenna selection for spectrally shaped Spatial Modulation (SM). Spectrally shaped SM aims at reducing the complex envelope fluctuations. This is done at the expense of a bandwidth expansion given by a roll-off factor β when root raised cosine (RRC) spectral filtering is considered. Nevertheless, this extra redundancy can be exploited by enabling the use of redundancy on the bit antenna selection stream. Indeed, we can associate a high performance error correcting code with a corresponding rate R = γ+β used to encode antenna selection bits and thus, we can achieve better performance at the receiver. Simulation results show that the proposed scheme exhibit a lower peak-to-average power ratio (PAPR) compared with the conventional SM scheme while achieving enhanced performance and diversity when an efficient coding scheme is used to improve antenna selection.

Faster-than-Nyquist (FTN) signaling appears as an attractive method to improve spectral efficiency at the price of an increased complexity at the receiver. The receiver generally implements a turbo-equalization/detection scheme to benefit from all the promises of the FTN signaling. However, this is not the only limitation we have to deal with. Indeed, compressing in the time domain impact the emitted signal and it usually results in an increase of the envelope fluctuations. This leads to an inherent multi-objectives trade-off between performance, targeted spectral efficiency and limited Peak to Average Power Ratio (PAPR). The last aspect is crucial when considering a satellite communication link due to non-linear amplification effects that can occur on-board the satellite. Usually, FTN studies focus on spectral efficiency increase for a fixed modulation order, trying to trade-off between performance and PAPR properties. In this paper, we show that, for a given asymptotic spectral efficiency, we can compress low order modulations to increase the spectral efficiency of these schemes while controlling the PAPR increase to achieve a better PAPR than the non compressed scheme with a higher modulation order. Thus, for the same asymptotic spectral efficiency, we can achieve 1 dB gain in terms of PAPR and 2 dB gain in Bit Error Rate (BER) performances for a coded 8-PSK FTN system compared to a coded 16-APSK. For the same BER performances, the asymptotic spectral efficiency gain obtained in linear context is over 20 %, higher when non-linearities are taken into account.

With the world population becoming increasingly urban and the multiplication of mega cities, urban leaders have responded with plans calling for so called smart cities relying on instantaneous access to information using mobile devices for an intelligent management of resources. Coupled with the advent of the smartphone as the main platform for accessing the Internet, this has created the conditions for the looming wireless bandwidth crunch.

In this work, we apply Spatial Modulation (SM) to in the so-called spectrally shaped SC-OFDM (SS SC-OFDM) at the transmitter. The idea behind SS SC-OFDM lies in applying a frequency window between the Fast Fourier Transform (FFT) and the Inverse Fast Fourier Transform (IFFT) in order to lower the side-lobes of the resulting time domain generated waveform. Thus, we can avoid the peak-to-average power ratio (PAPR) problem encountered in multicarrier systems. At the receiver, a reduced-rank (rr) Least Square (LS) channel estimation and a combining Minimum Mean Square Error (MMSE) equalization are used to retrieve the transmitted block of information bits, considering two flight scenarios for different environments.

The spatial coupling is an efficient technique that improves the threshold of Low Density Parity Check (LDPC) codes. In this paper, we investigate the performance of the serial concatenation of Continuous phase modulation (CPM) and LDPC convolutional codes over a memoryless additive white Gaussian noise channel. We show that coupling protographs optimized for CPM improves their performance and helps designing very good `small' protographs. Inspired from convolutional codes and thanks to the inner structure of CPM, we also introduce a new termination without rate loss but that still exhibits a coupling gain and it thus has a very good threshold. We will illustrate the behavior of different LDPC convolutional codes with different termination methods by giving some examples and studying their performance using multidimensional EXIT analysis.

In this paper, we provide a proof for the conjecture made by Abu Surra et al. [1] to simplify the computation of ensemble input output weight enumerators for protograph-based low density parity check (LDPC) codes. Furthermore, we propose a new method to compute more efficiently the ensemble weight enumerator. This approach can be applied particularly to lighten the computations for high rate codes, generalized LDPC codes or spatially coupled LDPC codes.

In this paper, we investigate on some efficient channel estimation methods for the aeronautical multipaths channel. The proposed methods exploit both the particular form of the channel impulse response and a priori knowledge of some parameters (mainly delays) that can be inferred from geometrical considerations based on geolocation. The first estimation method is based on a parametric multipath channel model while the second tries to exploit the relative sparsity of the channel impulse response. In both cases, this reduces the number of variables to be estimated and it provides better performance compared to a direct classical least-square estimation of the discrete equivalent channel impulse response.

In recent random access methods used for satellite communications, collisions between packets are not considered as destructive. In fact, to deal with the collision problem, successive interference cancellation is performed at the receiver. Generally, it is assumed that the receiver has perfect knowledge of the interference. In practice, the interference term is affected by the transmission channel parameters, i.e., channel attenuation, timing offsets, frequency offsets and phase shifts, and needs to be accurately estimated and canceled to avoid performance degradation. In this paper, we study the performance of an enhanced channel estimation technique combining estimation using an autocorrelation based method and the Expectation-Maximization algorithm integrated in a joint estimation and decoding scheme. We evaluate the effect of residual estimation errors after successive interference cancellation. To validate our experimental results, we compare them to the Cramer-Rao lower bounds for the estimation of channel parameters in case of superimposed signals.

In this paper, we derive an asymptotic analysis for a capacity approaching design of serially concatenated turbo schemes with low density parity check (LDPC) codes and continuous phase modulation (CPM) based on Laurent decomposition. The proposed design is based on extrinsic mutual information evolution and Gaussian approximation. By inserting partial interleavers between LDPC and CPM and allowing degree-1 variable nodes under a certain constraint we show that designed rates are very close to the maximum achievable rates. Furthermore, we discuss the selection of low complexity receivers that works with the same optimized profiles.

In this paper, we derive an asymptotic analysis and optimization of coded CPM systems using both unstructured and protograph-based LDPC codes ensembles. First, we present a simple yet effective approach to design unstructured LDPC codes : by inserting partial interleavers between LDPC and CPM, and allowing degree-1 and degree-2 variable nodes in a controlled pattern, we show that designed codes perform that can operate very close to the maximum achievable rates. Finally, the extension to protograph based codes is discussed. We provide some simple rules to design good protograph codes with good threshold properties.

In this paper, we investigate a sub-optimal but efficient receiver structure for the equalization of aeronautical communications via a satellite link. The structure is based on the inherent sparsity of the equivalent discrete baseband channel model that enables an efficient implementation based on simple parallel trellis using Maximum A Posteriori (MAP) detection combined with iterative residual interference estimation and cancellation. The proposed scheme is shown to be very efficient while significantly decreasing the complexity compared to a MAP receiver that does not exploit the sparsity of the aeronautical channel.

This article deals with Minimum Mean Square Error (MMSE) turbo equalization of nonlinear interference using a volterra series decomposition of the underlying nonlinear channel. Although it has been often argued that linear MMSE based equalization is unsuited for cancelling nonlinear interference, we show that this common belief is not true in a strict sense. By a proper derivation of the linear based MMSE soft equalizer, we are able to show that the underlying structure of the equalizer is equivalent to a Soft Interference Canceller (SIC) treating both the linear and nonlinear interference. Based on these results, approximations are provided for lowering the computational complexity. Links to previously proposed “nonlinear” SIC are emphasized showing that the previously proposed structures are nothing but approximations of a linear MMSE receiver applied to nonlinear ISI channels. Simulations show that significant improvements can be achieved by using the proposed exact and approximate MMSE based turbo-equalizers.

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, the asymptotic iterative performance of block-Markov, sparse-graph codes over the binary erasure relay channel is investigated. Note that the full-duplex relay channel is a particular case of the considered model. We obtain two interesting results: a) the block-Markov structure does not improve the asymptotic performance of good erasure-correcting sparse-graph codes; b) under certain conditions, it does however improve the asymptotic performance of good erasure-detecting (i.e. bad erasure-correcting) sparse-graph codes.

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 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.

The asymptotic iterative performance of the block-Markov encoding scheme, defined over bilayer LDPC codes, is analyzed. This analysis is carried out for both half-duplex and full-duplex regimes. For the sake of clarity and simplicity, a transmission over the binary erasure relay channel is assumed. To analyze the iterative performance of the coding scheme, the asymptotic threshold boundary γ (∈1, ∈2) is used as a performance measure. It is derived for two sparse-graph ensembles: Block-Markov Bilayer-Expurgated and -Lengthened LDPC ensembles.

In this paper we present a coding rate adaptation technique for a Time-Hopping Impulse-Radio Ultra-Wide Band (TH-IR-UWB) system assuming that the Multi-User Interference (MUI) is modeled as an additive interference noise following a Generalized Gaussian Distribution (GGD). The shape parameter induced by the GGD model is in general time-variant since it strongly depends on the essential UWB system parameters and the received signal power of the active users. In this paper, we show that the performance of a TH-IR-UWB LDPC coded system is quite independent of the GGD shape parameter when we consider the mutual information between the soft input to the decoder and the transmitted sequence, especially for medium to high-rate regimes. This allows to derive a simple and efficient link adaptation scheme based on a rate-compatible protograph-based LDPC code. Simulated results are provided to evaluate the performance of the described coding rate adaptation algorithm for a TH-IR-UWB multi-user system.

We propose nonbinary LDPC codes concatenated with multiplicative repetition codes. By multiplicatively repeating the (2,3)-regular nonbinary LDPC mother code of rate 1/3, we construct rate-compatible codes of lower rates 1/6, 1/9, 1/12,.... Surprisingly, such simple low-rate nonbinary LDPC codes outperform the best low-rate binary LDPC codes so far. Moreover, we propose the decoding algorithm for the proposed codes, which can be decoded with almost the same computational complexity as that of the mother code.

The problem of frame synchronization of non-binary Low-Density Parity-Check (LDPC) codes is considered in this paper. We propose two techniques of blind frame synchronization that are based on syndrome calculation over the Galois Field GF(q). While the first technique computes hard values of the syndrome, the second one deals with probabilities. Furthermore, we present in this paper a theoretical analysis on the proposed synchronization criteria. This analysis is validated by comparison to simulated results. Although non-binary LDPC codes have short lengths and their decoding is very effective even at low Signal-to-Noise Ratio (SNR), simulation results have shown that the proposed Non-Binary Soft Syndrome (NBSS) based synchronization algorithm is well adapted to such codes. The Frame Error Rate (FER) curves obtained after synchronization and decoding are very close to the perfect synchronization case.

In this paper, we propose an extrinsic distortion-based source-channel allocation for JPWL transcoding systems. The distortion based approach is possible thanks to the extrinsic distortion estimation using information contained in the compressed bitstream. The proposed estimation method gives a coarse grain estimator of the true distortion, but keeping the same relative order of magnitude for distortion. Although coarse, this estimation can be used efficiently in a distortion based source-channel allocation strategy. Simulation results are provided in the context of JPEG2000 bitstream wireless transmissions using JPWL tools.

We propose non-binary LDPC codes concatenated with multiplicative repetition codes. To the best of the authors' knowledge, for the transmissions over the memoryless binary-input output-symmetric channels, 2m-ary the (2,dc)-regular LDPC code for m ~ 8 and dc≥ 3 is the best code so far among codes with moderate code length. By multiplicatively repeating the 2m-ary (2,3)-regular LDPC code of rate 1/3, we construct rate-compatible codes of lower rates 1/6,1/9,1/12,.... Surprisingly, such simple low-rate codes outperform the best low-rate binary codes so far.

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 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.

For a (lambda(x); rho(x)) standard irregular LDPC code ensemble, the growth rate of the average weight distribution for small relative weight omega is given by log(lambda'(0)rho'(1))omega + O(omega2) in the limit of code length n. If lambda'(0)rho'(1) < 1, there exist exponentially few code words of small linear weight, as n tends to infinity. It is known that the condition coincides with the stability condition of density evolution over the erasure channels with the erasure probability 1. In this paper, we show that this is also the case with multi-edge type LDPC (MET-LDPC) codes. MET-LDPC codes are generalized structured LDPC codes introduced by Richardson and Urbanke. The parameter corresponding lambda'(0)rho'(1) appearing in the conditions for MET-LDPC codes is given by the spectral radius of the matrix defined by extended degree distributions.

Non-binary LDPC codes are now recognized as a potential competitor to binary coded solutions, especially when the codeword length is small or moderate. More and more works are reported with good performance/complexity tradeoffs, which make non-binary solutions interesting for practical applications, such as 4G-wireless systems or DVB-like systems. In this paper, we show that proposing non-binary LDPC codes built on finite fields is actually a limitation, both from performance and implementation points of view. By considering non-binary codes on the general linear group, we show in particular that a slight performance improvement can be obtained, compared to Galois Field codes, with reasonable additional cost in the hardware implementation. The performance gain is quite small, but comes at a slight extra decoding cost, and is obtained by proper generalization of the code optimization techniques that are standard for non-binary LDPC codes on fields.

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.

The design of efficient rateless coding schemes for multicast applications in wireless environments is investigated. First, the rateless paradigm for non-ergodic channels is introduced by making use of the dynamic-decoding nature of rateless codes that allows them to adapt opportunistically the code rate to the channel realization (assumed unknown at the transmitter). The information theoretical limits of such codes can be interpreted in terms of the notion of outage capacity. Then, we consider a quasi-static Rayleigh-fading channel with perfect and imperfect channel state information (CSI) at the receiver. We show that the optimal consistent measure of information for decoding with imperfect CSI, is given by the log-likelihood ratio (LLR) of the received bits via a composite (more noisy) channel. The optimization of Raptor codes, which depends on the delay requirements of decoding, is obtained by using Information content evolution under Gaussian approximation. Simulation results show that optimized Raptor codes can operate very close to the theoretical limits on a wide range of delay requirements.

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.

In this paper, a method to design regular (2, dc)- LDPC codes over GF(q) with both good waterfall and error floor properties is presented, based on the algebraic properties of their binary image. First, the algebraic properties of rows of the parity check matrix H associated with a code are characterized and optimized to improve the waterfall. Then the algebraic properties of cycles and stopping sets associated with the underlying Tanner graph are studied and linked to the global binary minimum distance of the code. Finally, simulations are presented to illustrate the excellent performance of the designed codes.

This paper is eligible for the student paper award. In this paper, we present an analytical analysis of the convergence of raptor codes under joint decoding over the binary input additive white noise channel (BIAWGNC), and derive an optimization method. We use information content evolution under Gaussian approximation, and focus on a new decoding scheme that proves to be more efficient: the joint decoding of the two code components of the raptor code. In our general model, the classical tandem decoding scheme appears to be a sub-case, and thus, the design of LT codes is also possible.

In this paper, we develop algebraic properties of regular (2, tr, N) non binary LDPC codes designed using their binary image. First, we characterize the algebraic properties of optimized rows of the parity check matrix H associated with a code, and then we study the algebraic properties of cycles and stopping sets associated with the underlaying Tanner graph

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.