认知网中基于联盟博弈的资源分配与功率控制

为解决认知型飞蜂窝和宏蜂窝构成的双层网络中存在的上行干扰问题,通过分析建模,提出了一种用户合作策略。在频分复用划分不同频率段的用户基础上,让同一频段的宏用户与飞用户采用合作博弈的方式组成联盟,联盟内部通过时分复用方式共享信道。在形成联盟的用户中,根据联盟后的用户速率,进行功率控制。仿真结果表明,优化模型提高了双层异构网络中飞蜂窝网络用户的吞吐量和接入率,降低了异构网络中的相互干扰,提高了系统的能效,增加了用户接入率。

Resource Allocation and Power Control Based on Alliance Game in Cognitive Network

In order to solve the uplink interference problem in the double-layer network composed of cognitive femtocells and macrocells, a user cooperation strategy is proposed through analysis and modeling. First, based on frequency division multiplexing, users in different frequency bands are divided, and macro users and users in the same band adopt a cooperative game to form alliances. The alliance internally shares channels through time division multiplexing. Second, among the users forming alliances, power control is performed based on the user rate after the alliance. Simulation results show that the optimization model improves the throughput and access rate of the femtocell users in the double-heterogeneous network, reduces the mutual interference in heterogeneous networks, improves the system energy efficiency, and increases the user access rate.