感知无线电网络中最优的分布式功率分配

Optimal Distributed Power Allocation in Cognitive Radio Networks

在干扰温度模型下,将分布式感知无线电网络与授权系统的频谱共享问题转化为有约束的非线性功率优化问题.为了提高多个测量点场景下感知无线电网络的吞吐量,提出了一种全局最优的分布式功率分配算法.该算法利用原始-对偶方法求解,通过有限的信息交换,实现了吞吐量最优的功率分配,理论分析和仿真结果表明,算法的收敛结果满足干扰温度约束,系统吞吐量明显提升.

Spectrum sharing mechanism among distributed cognitive radio nodes is studied. Based on interference temperature model, the spectrum sharing problem is changed into a nonlinear power optimization problem. A distributed power allocation algorithm is proposed to maximize the network utility under multiple interference temperature limits. The presented algorithm solves the nonlinear optimization using primal-dual method with limited information exchange among cognitive radio nodes. Analysis and simulation show that the network utility is enhanced dramatically using the proposed algorithm.