Distributed Detection and Data Fusion
Distributed Detection and Data Fusion
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Coded cooperation in wireless communications: space-time transmission and iterative decoding
IEEE Transactions on Signal Processing
Cooperative diversity in wireless networks: Efficient protocols and outage behavior
IEEE Transactions on Information Theory
Capacity bounds and power allocation for wireless relay channels
IEEE Transactions on Information Theory
Cooperative Strategies and Capacity Theorems for Relay Networks
IEEE Transactions on Information Theory
Cooperative communication in wireless networks
IEEE Communications Magazine
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This paper considers the joint symbol detection and channel estimation problem for cooperative communications in cluster-based networks. The proposed joint detection and estimation scheme is derived by using the expectation maximization (EM) algorithm. In addition, the cooperative communication between the relays and the destination is based on the concept of compress-and-forward (CF) scheme. Most importantly, the distribution detection theory is incorporated in developing the joint detection and estimation rules. Specifically, each relay makes its decision based on its joint detection and estimation rule and then forwards it to the destination node. The destination node makes a decision by fusing the decisions sent from the relays using its joint detection and estimation rule. In our considered structure, the feedback channels are also allowed from the destination node to all the relays to further improves the performance of cooperative communications. The simulation results show that the performance of cooperative communication can improve significantly by using the fusion technique and the feedback channels.