Research On The Cooperative Diversity In Wireless Communication Networks

With the developments of micro-electro-mechanical systems and low power-consuming integrated digital electronics, new technologies have emerged continuously. Wireless ad-hoc network and wireless sensor network are two representative networks. The two networks and cooperative diversity technology based on which have bring up a prevalent attention. However, the special characteristics of the networks have also posed many challenges to the design and management of the interrelated networks. First of all, in WSN, we need to allot and manage the energy effectively. Second, in ad-hoc network, all the nodes are distributed. Furthermore, the cooperation demands the nodes to expend energy on helping other nodes, so some individuals may refuse to cooperate with other nodes in the network to save their energy. Therefore, research on the partial cooperative behavior is necessary.In this paper, we do some work about the power allocation of cooperative nodes in wireless sensor networks and selfishness and performance in wireless ad-hoc networks.First, we assume that all the nodes in the wireless sensor networks are cooperative. Then we study the problem of optimal power allocation among the nodes with two cooperative communication schemes. We proposed a nonlinear model for the energy consuming with cooperative method, then we use particle swarm optimization (PSO) to achieve the optimal power allocation. The result shows that the power consuming of single node decreased with the increasing cooperative nodes. The lifetime of the whole network is prolonged effectively.Second, we study the problem of the performance of bit error rate (BER) in case of partial cooperation with amplify-and-forward method in ad-hoc networks. We use on-off model to describe the selfish behavior of the relays. Then we analyze the performance of BER with one and two relays, which are selfish nodes. We proposed a method that the terminal can choose the cooperative scheme according to the critical selfish probability of nodes. Simulations validate our analysis.