Abstract
This chapter addresses distributed parameter coordination methods for wireless communication systems. We present two distributed algorithms for the problem of precoder selection. The first and simplest method is the greedy solution in which each communication node in the network acts selfishly. The second method and the focus of this chapter is based on a message-passing algorithm, namely min-sum algorithm, in factor graphs. Three kinds of precoding codebook are considered: transmit antenna selection, fixed-beam selection, and LTE precoder selection. Evaluations on the potential of such an approach in a wireless communication network are provided and its performance and convergence properties are compared with those of a baseline selfish/greedy approach. Simulation results are presented and discussed, which show that the graph-based technique generally obtains gain in sum rate over the greedy approach at the cost of a larger message size. For instance, the percentage gain in sum rate over the greedy is about 33 % within 5 iterations in a 7-cell network considering single-layer LTE precoders. Besides, the graph-based method usually reaches the global optimum in a efficient manner. Methods of improving the rate of convergence of graph-based distributed coordination technique and reducing its associated message size are therefore important topics for wireless communication networks.
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Guerreiro, I.M., Cavalcante, C.C., Hui, D. (2014). Distributed Optimization Techniques in Wireless Communication Networks. In: Cavalcanti, F. (eds) Resource Allocation and MIMO for 4G and Beyond. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8057-0_6
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