基于博弈论的认知无线电网络跨层资源分配

Cross-layer resource allocation in cognitive radio networks based on game theory

针对多跳认知无线电网络的多层资源分配问题,提出了协作去耦合方法和跨层联合方法,协作去耦合方法首先单独完成路径选择任务,随后进行信道与功率的博弈分配;跨层联合方法则通过博弈直接对路径、信道、功率三层资源进行同时分配,两种方法都综合考虑网络层、介质访问控制层、物理层的启发原则,引入了节点被干扰度信息和节点主动干扰度信息来辅助路径选择,设计了基于功率允许宽度信息的Boltzmann探索来完成信道与功率选择,设计了长链路和瓶颈链路替换消除机制以进一步提高网络性能,从促进收敛角度,选择序贯博弈并设计了具体的博弈过程,此外还分析了博弈的纳什均衡,讨论了两种算法的复杂度,仿真结果表明,协作去耦合方法和跨层联合方法在成功流数量、流可达速率、发射功耗性能指标上均优于简单去耦合的链路博弈、流博弈方法。

In this paper, we propose a cooperative decoupling method and a cross-layer joint method for multi-layer resource allocation in multi-hop cognitive radio networks. In cooperative decoupling method, the task of path choosing is ac-complished independently, and then the game of channel and power allocations is implemented. In cross-layer joint method, the three-layer resource of path, channel and power is allocated simultaneously by process of game. The heuris-tic principles of network layer, media access control layer and physical layer are employed synthetically in two methods. The degree of receiving interference and the degree of sending interference are adopted to assist path choosing. The Boltzmann exploration based on the width of permitting power is designed to select the channel and power. The means of replacement and elimination of long link or bottleneck link are proposed to further enhance network performance. The sequential game process instead of simultaneous game process is chosen because the former has better convergence property in current scenario, and the concrete process of game is provided. Moreover, the Nash equilibrium of the games and the complexity of the algorithms are analyzed and discussed. Simulation results show that the cooperative decou-pling method and the cross-layer joint method have better performances in the number of success flows, the achievable data transmission rate and power consumption than the cooperative link game and the local flow game with simple decoupling.