Gibbs sampling based distributed OFDMA resource allocation

• Published in: Science China. Information sciences 2014-04, Vol.57 (4), p.14-25
• Main Authors: Garcia, Virgile, Chen, Chung Shue, Zhou, YiQing, Shi, JingLin
• Format: Article
• Language: English
• Subjects: Algorithms; Allocations; Cellular communication; China; Computer Science; Convergence; Gibbs抽样; Global optimization; Information Systems and Communication Service; Networking and Internet Architecture; NP-hard; OFDMA; Optimization; Research Paper; Resource allocation; Sampling; Strategy; 分布式优化; 吉布斯抽样; 收敛速度; 资源分配问题; 采样算法
• ISSN: 1674-733X; 1869-1919
• DOI: 10.1007/s11432-014-5076-x

In this article, we present a distributed resource and power allocation scheme for muRip]e-resource wireless cellular networks. The global optimization of multi-cell multi-link resource allocation problem is known to be NP-hard in the general case. We use Gibbs sampling based algorithms to perform a distributed optimization that would lead to the global optimum of the problem. The objective of this article is to show how to use the Gibbs sampling （GS） algorithm and its variant the Metropolis-Hastings （MH） algorithm. We also propose an enhanced method of the MH algorithm, based on a priori known target state distribution, which improves the convergence speed without increasing the complexity. Also, we study different temperature cooling strategies and investigate their impact on the network optimization and convergence speed. Simulation results have also shown the effectiveness of the proposed methods.