Modified augmented belief propagation for general memoryless channels

In this paper, we propose an efficient implementation of the augmented belief propagation (ABP) algorithm for low-density parity-check codes over general memoryless channels. ABP is a multistage BP based decoder that uses a backtracking processing when decoding fails. The algorithm proceeds in two main steps, namely a symbol selection step and an augmented decoding step. The former is based on a criterion related both to the stopping subgraph connectivity and to the input reliability, while the latter can be either implemented using a list based or a greedy approach. Compared to the original implementation, we consider a different approach for both steps. First, the proposed node selection is only based on the dynamic of sign changes of the extrinsic messages at the variable nodes output. This enables us to consider indifferently general memoryless channels, while still taking into account the graph irregularity. Then, we propose a simple yet efficient implementation of the augmented decoding procedure based on pruning of the branching tree The proposed algorithm shows near maximum likelihood decoding performance while decreasing the overall complexity (computation and memory) of the original algorithm. Moreover, complexity-performance trade-off is an built-in feature for this kind of algorithm

Joint Network/Channel Decoding for Heterogeneous Multi-Source/Multi-Relay Cooperative Networks

International audienceIn this paper, we study joint network/channel decoding for multi{source multi{relay heterogeneous wireless networks. When convolutional and network codes are used at the phys- ical and network layers, respectively, we show that error correction and diversity properties of the whole network can be characterized by an equivalent and distributed convo- lutional network/channel code. In particular, it is shown that, by properly choosing the network code, the equivalent code can show Unequal Error Protection (UEP) properties, which might be useful for heterogeneous wireless networks in which each source might ask for a di®erent quality{of{ service requirement or error probability. Using this repre- sentation, we show that Maximum{Likelihood (ML) joint network/channel decoding can be performed by using the trellis representation of the distributed convolutional net- work/channel code. Furthermore, to deal with decoding er- rors at the relays, a ML{optimum receiver which exploits side information on the source{to{relay links is proposed

Multiplicatively Repeated Non-Binary LDPC Codes

We propose non-binary LDPC codes concatenated with multiplicative repetition codes. By multiplicatively repeating the (2,3)-regular non-binary 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 non-binary 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.Comment: To appear in IEEE Transactions on Information Theor

Allocation de ressources multi-débit pour la radio ULB impulsionnelle

National audienceDans cet article, nous considérons un système de communication multi-utilisateurs mettant en oeuvre une couche physique ultra-large bande (ULB) impulsionnelle à répartition par code. Nous nous intéressons tout d'abord à l'expression de la variance de l'interférence d'accès multiple (IAM) lorsque les utilisateurs ont des durées symboles différentes grâce à un nombre de trames, $N_f$, variable selon les utilisateurs. Nous nous intéressons ensuite au problème de la maximisation du débit global en affectant un nombre de trames différent pour chaque utilisateur sous contrainte de qualité de service (QoS) hétérogène pour certaines classes d'utilisateurs. Nous proposons une heuristique à complexité linéaire avec le nombre d'utilisateurs pour l'allocation du nombre de trames et évaluons ses performances par rapport à deux algorithmes de références

Allocation conjointe de puissance et rendement d'un utilisateur cognitif exploitant les retransmissions d'un utilisateur primaire : le cas du canal en Z

National audienceDans cet article, nous considérons le problème de l’allocation conjointe de puissance et de rendement pour un utilisateur secondaire exploitant le protocole de retransmission d’un utilisateur primaire. Nous proposons un algorithme, basé sur les Processus de Markov Décisionnels (MDP), permettant de calculer une allocation optimale pour le problème de la maximisation du débit de l’utilisateur secondaire tout en garantissant un débit minimal pour l’utilisateur primaire

Opportunistic Secondary Spectrum Sharing Protocols for Primary implementing an IR type Hybrid-ARQ Protocol

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

XOR Network Coding for Data Mule Delay Tolerant Networks

International audienceWe propose a simple yet efficient scalable scheme for improving the performance of Delay Tolerant Networks (DTNs) with data mules by using XOR network coding. We carry out a theoretical analysis based on a model abstracted from the Village Communication Networks (VCNs), beginning with two villages and then extending to N villages. We also examine how the delivery probability is affected by the different overlapping intervals of two data mules. The theoretical analysis indicates that the maximum delivery probability increases by 50% and our simulation results illustrate this point, showing that the overhead ratio and average delay are reduced as well. Finally, our scheme is applied to a real network, the Toulouse public transportation network. We analyze the dataset, calculate the overlapping intervals of inter-vehicles and the amount of data that transit vehicles can exchange in one day, showing a 54:4% improvement in throughput