Performance of Turbo Product Codes on the Multiple-Access Relay Channel with Relatively Poor Source-Relay Links

International audienceIn this paper, we study a cooperative coding scheme based on turbo product codes where a number of sensors transmit to a same destination with the help of a relay. This network can be modeled by a multiple-access relay channel (MARC). In the proposed scheme, the relay applies algebraic systematic Network Coding to the source codewords and forwards only the additional redundancy to the destination where an overall product codeword is observed. Based on the single-relay scenario that has been studied in a previous paper, we analyze the error probabilities at the relay input and output for different relay strategies. Taking into account the residual errors at the relay, an appropriate loglikelihood ratio is used at the destination by the turbo decoder. The error performance under the degraded source-relay channel condition is shown on the Rayleigh fading channel. Besides that, we analyze the error correlation in the relay-generated redundancy and investigate the benefits of using multi-relay cooperation. Different cooperation schemes are compared in terms of performance, complexity and energy consumption

Guard Interval Adaptation for In-home Power Line Communication

International audienceThis paper aims to analyze the choice of the guard interval (GI) length in PLC systems to optimize the achievable throughput under power and symbol error-rate (SER) constraints. In general, the GI length is chosen so that there is no interference, i.e. the GI length is greater than or equal to the channel impulse response length. However, many previous works have shown that in PLC systems, this GI choice is inefficient in terms of achievable throughput. Indeed, shorter GI evidently results in inter-symbol interference (ISI) and intercarrier interference (ICI), but the gain offered by shortened GI may exceed the loss caused by interference. In this paper, we propose a simple solution for the GI length adaptation in PLC systems to optimize the achievable throughput

Robust Detection of Binary CPMs With Unknown Modulation Index

International audienceWe consider soft-output detection of a binary continuous phase modulation (CPM) generated through a low-cost transmitter, thus characterized by a significant modulation index uncertainty, and sent over a channel affected by phase noise. The proposed detector is designed by adopting a simplified representation of a binary CPM signal with the principal component of its Laurent decomposition and is obtained by using the framework based on factor graphs and the sum-product algorithm. It does not require an explicit estimation of the modulation index nor of the channel phase and is very robust to large uncertainties of the nominal value of the modulation index. Being soft-output in nature, this detector can be employed for iterative detection/decoding of practical coded schemes based on a serial concatenation, possibly through a pseudo-random interleaver, of an outer encoder and a CPM modulation forma

Turbo Detection Based On Sparse Decomposition For Massive MIMO Transmission

International audienceIn this paper, we address the problem of underdetermined massive MIMO detection for QAM constellations. In [1], the authors showed the utility of projecting the signal in a basis of the modulation alphabet, looking for the sparsest vector representation. As an extension of this work and in order to reduce the detection complexity, we present first an equivalent real-valued formulation of the optimization problem, all the more interesting as the modulation order is high. Then we consider an outer forward error correcting (FEC) code and we propose a turbo detection scheme. We focus on the medium SNR value range where detection errors involve adjacent symbols. Based on this hypothesis, we propose a sparse vector formulation to be treated as a soft detection output that can be directly exploited in a symbol-to-binary conversion to feed the FEC decoder with reliable soft input. The FEC decoder output will be exploited to provide a priori information within the detection criterion based on a regularization approach. Simulation results show the efficiency of the proposed scheme in comparison with reference schemes of the state-of-art

Binary Continuous Phase Modulations Robust to a Modulation Index Mismatch

International audienceWe consider binary continuous phase modulation (CPM) signals used in some recent low-cost and low-power consumption telecommunications standard. When these signals are generated through a low-cost transmitter, the real modulation index can end up being quite different from the nominal value employed at the receiver and a significant performance degradation is observed, unless proper techniques for the estimation and compensation are employed. For this reason, we design new binary schemes with a much higher robustness. They are based on the concatenation of a suitable precoder with binary input and a ternary CPM format. The result is a family of CPM formats whose phase state is constrained to follow a specific evolution. Two of these precoders are considered. We will discuss many aspects related to these schemes, such as the power spectral density, the spectral efficiency, simplified detection, the minimum distance, and the uncoded performance. The adopted precoders do not change the recursive nature of CPM schemes. So these schemes are still suited for serial concatenation, through a pseudo-random interleaver, with an outer channel encoder

Bit loading in mimo-plc systems with the presence of interference

International audienceIn broadband indoor power line communication (PLC) systems, multiple input multiple output (MIMO) techniques have been introduced to address the increasing demand for high data rates under the constraint of limited allocated bandwidth. Whereas the self inter-antenna interference can be dealt with on each subcarrier, both inter-carrier and inter-symbol interference can occur yielding sub-optimal bit loading if not considered. In this paper, we extend to the MIMO case the lowcomplexity bit/power allocation algorithm, called Reduced Complexity Algorithm (RCA), that we previously applied to the SISO case. Based on the Greedy principle, the RCA takes the interference into account to optimize the bit loading. We consider two MIMO schemes: optimum eigen beamforming and spatial multiplexing. Simulation results show the efficiency of the RCA in terms of throughput and computation cost in both cases

A Computationally Efficient Discrete Bit-Loading Algorithm for OFDM Systems Subject to Spectral-Compatibility Limits

International audienceThis paper considers bit-loading algorithms to maximize throughput under total power and spectral mask constraints in interference-free OFDM systems. The contribution is twofold. First, we propose a simple criterion to switch between two wellknown algorithms from the literature: the conventional Greedy and Greedy-based bit-removing (with maximum allowable bit loading initialization) algorithms. Second, we present a new lowcomplexity loading algorithm that exploits the bit vector obtained by rounding the water-filling algorithm solution to the associated continuous-input rate maximization problem as an efficient initial bit vector of the Greedy algorithm.We theoretically prove that this bit vector has two interesting properties. The first one states that it is an efficient bit vector, i.e., there is no movement of a bit from one subcarrier to another that reduces the total used power. The second one states that the optimized throughput, starting from this initial bit vector, is achieved by adding or removing bits on each subcarrier at most once. Simulation results show the efficiency of the proposed algorithm, i.e., the achievable throughput is maximized with significant reduction of computation cost as compared to many algorithms in the literature

Allocation de débit à faible complexité dans les systèmes OFDM en présence de contraintes spectrales

National audienceCet article traite de la maximisation du débit dans les systèmes OFDM soumis à des contraintes de limitation de la puissance. Nous proposons un algorithme d'allocation glouton dans lequel le vecteur de bits initial est la discrétisation par arrondi de la solution "Water-Filling" du problème continu associé. Nous montrons théoriquement que ce vecteur est "efficace", c'est-àdire qu'il n'existe pas de mouvement d'un bit d'une sous-porteuse à l'autre qui réduise la puissance totale utilisée. Les résultats de simulation montrent l'efficacité de l'algorithme proposé : le débit réalisable est maximisé avec une réduction significative du coût de calcul par rapport à des algorithmes de référence de la littérature

Achievable Throughput Optimization in OFDM Systems in the Presence of Interference and its Application to Power Line Networks

International audienceThe aim of this paper is to study the bit-loading and power allocation problem in the presence of interference (Inter-carrier Interference (ICI) and Inter-Symbol Interference (ISI)) in Orthogonal Frequency Division Multiplexing (OFDM) systems. ISI and ICI significantly degrade the performance of OFDM systems and make the resource management optimized without the assumption of interference less efficient. To solve this problem, an initial solution based on the greedy approach is proposed in this paper. Then, several reduced complexity approaches, which yield a little degradation compared to the initial solution, have been developed. Simulation results presented in the context of Power Line Communication (PLC) show that the performance of proposed algorithms is tight with their upper bound. Moreover, these algorithms efficiently improve the system performance as compared to the constant power water-filling allocation algorithm as well as maximum power allocation algorithm

Low-complexity detector for very large and massive MIMO transmission

International audienceMaximum-Likelihood (ML) joint detection has been proposed as an optimal strategy that detects simultaneously the transmitted signals. In very large multiple-input-multiple output (MIMO) systems, the ML detector becomes intractable due the computational cost that increases exponentially with the antenna dimensions. In this paper, we propose a relaxed ML detector based on an iterative decoding strategy that reduces the computational cost. We exploit the fact that the transmit constellation is discrete, and remodel the channel as a MIMO channel with sparse input belonging to the binary set {0, 1}. The sparsity property allows us to relax the ML problem as a quadratic minimization under linear and l1-norm constraint. We then prove the equivalence of the relaxed problem to a convex optimization problem solvable in polynomial time. Simulation results illustrate the efficiency of the low-complexity proposed detector compared to other existing ones in very large and massive MIMO context