A distributed approach to precoder selection using factor graphs for wireless communication networks

Abstract

This paper addresses distributed parameter coordination methods for wireless communication systems. This proposes a method based on a message-passing algorithm, namely min-sum algorithm, on factor graphs for the application of precoder selection. Two particular examples of precoder selection are considered: transmit antenna selection and beam 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 for the precoder selection examples 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. Besides, the proposed method usually reaches the global optima in an efficient manner. Methods of improving the rate of convergence of the graph-based distributed coordination technique and reducing its associated message size are therefore important topics for wireless communication networks.

A Factor Graph Approach to Nonuniform Power Distribution

“…For "better channel" links we could send more information through those since the probability of higher distortion is smaller when compared to the "worse channel" links. In our previous work [6] we have only considered the uniform power allocation case. In general, this assignment of different powers can be performed by multiplying each precoding matrix by a weighting matrix.…”

“…Different from the work in [3], we assume multi-stream precoders to be selected from a pre-defined codebook and also spatially correlated MIMO channels. The distributed approach is founded on the min-sum algorithm in factor graphs [1], [6]. Besides, different from our work in [6], we propose the use of a weighting matrix to allocate different power levels to data streams.…”

“…The distributed approach is founded on the min-sum algorithm in factor graphs [1], [6]. Besides, different from our work in [6], we propose the use of a weighting matrix to allocate different power levels to data streams. Such a matrix is combined with precoding matrices in the 3GPP long-term evolution (LTE) codebook [7].…”

Message-Passing Algorithm for Sum-rate Maximization in Multi-antenna Underlay D2D Communications

“…The factor graph is a bipartite graph that represents how the multivariate functions can be factorized. The MPA has also been used to perform resource allocation, with the min-sum variant, which is equivalent to the max-product MPA, in [5]- [8].…”

Distributed piecewise filtering design for large-scale networked nonlinear systems

“…In the distributed control, the supplemental feedbacks with the interconnected information are provided for the local controllers to enhance the requirements of stability and performance. As a result, the distributed control avoids those shortages appearing in both centralized and decentralized controls [6,7].…”