基于博弈论的交叉优化公平调度算法

Cross optimizing a fair access scheduling algorithm based on game theory

针对大多数文献仅仅是分别优化多输入多输出系统(MIMO)链路级性能或是仅仅单纯在系统级进行调度,提出了一种基于博弈论的交叉优化公平调度算法,将系统级的调度策略和链路级的物理层优化相结合,并且采用基于博弈论的功率分配算法调整各天线上每个用户的功率分配.仿真结果表明,该算法不但在系统级为每个用户提供了公平的调度机会,而且充分利用MIMO系统的空间复用技术以及天线匹配技术实现了系统级和链路级的交叉优化,并且采用基于博弈论的功率分配方法,有效地克服了不同天线上不同用户之间的相互干扰动态变化的问题,不会造成用户干扰之间的交互循环,提高了系统容量.

To date, optimization of multiple input multiple output （MIMO） systems is either made at the link level or at the system level. This can only generate sub optimal solutions, so a cross optimization fair scheduling algorithm based on game theory is proposed, in which a power allocation algorithm based on game theory is employed to adjust power allocation of all users of each antenna by combining scheduling strategy on the system level with physical optimization at the link level. Simulation results showed that the proposed algorithm not only provides fair channel access opportunities to users at the system level but also utilizes the spatial multiplexing of multiple-input multiple-output systems and antenna mapping to achieve cross optimization between the system level and the physical level. Mutual interference between users of different antennas is eliminated efficiently, without causing circulation of users＂ interferences.