Robust Successive Compute-and-Forward over Multi-User Multi-Relay Networks

This paper develops efficient Compute-and-forward (CMF) schemes in multi-user multi-relay networks. To solve the rank failure problem in CMF setups and to achieve full diversity of the network, we introduce two novel CMF methods, namely, extended CMF and successive CMF. The former, having low complexity, is based on recovering multiple equations at relays. The latter utilizes successive interference cancellation (SIC) to enhance the system performance compared to the state-of-the-art schemes. Both methods can be utilized in a network with different number of users, relays, and relay antennas, with negligible feedback channels or signaling overhead. We derive new concise formulations and explicit framework for the successive CMF method as well as an approach to reduce its computational complexity. Our theoretical analysis and computer simulations demonstrate the superior performance of our proposed CMF methods over the conventional schemes. Furthermore, based on our simulation results, the successive CMF method yields additional signal-to-noise ratio gains and shows considerable robustness against channel estimation error, compared to the extended CMF method.Comment: 44 pages, 10 figures, 1 table, accepted to be published in IEEE Trans. on Vehicular Tec

Optimal Cooperative MAC Protocol with Efficient Selection of Relay Terminals

A new cooperative protocol is proposed in the context of wireless mesh networks. The protocol implements ondemand cooperation, i.e. cooperation between a source terminal and a destination terminal is activated only when needed. In that case, only the best relay among a set of available terminals is re-transmitting the source message to the destination terminal. This typical approach is improved using three additional features. First, a splitting algorithm is implemented to select the best relay. This ensures a fast selection process. Moreover, the duration of the selection process is now completely characterized. Second, only terminals that improve the outage probability of the direct link are allowed to participate to the relay selection. By this means, inefficient cooperation is now avoided. Finally, the destination terminal discards the source message when it fails to decode it. This saves processing time since the destination terminal does not need to combine the replicas of the source message: the one from the source terminal and the one from the best relay. We prove that the proposed protocol achieves an optimal performance in terms of Diversity-Multiplexing Tradeoff (DMT)

Splitting algorithm for DMT optimal cooperative MAC protocols in wireless mesh networks

A cooperative protocol for wireless mesh networks is proposed in this paper. The protocol implements both on-demand relaying and a selection of the best relay terminal so only one terminal is relaying the source message when cooperation is needed. Two additional features are also proposed. The best relay is selected with a splitting algorithm. This approach allows fast relay selection within less than three time-slots, on average. Moreover, a pre-selection of relay candidates is performed prior to the splitting algorithm. Only terminals that are able to improve the direct path are pre-selected. So efficient cooperation is now guaranteed. We prove that this approach is optimal in terms of diversity-multiplexing trade-off. The protocol has been designed in the context of Nakagami-mfading channels. Simulation results show that the performance of the splitting algorithm does not depend on channel statistics

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs