基于对偶分解的MU-CoMP联合资源分配算法

Joint resource allocation algorithm based on dual decomposition for MU-CoMP

在MU-CoMP-JT(multi-users coordinated multiple-points joint transmission)资源分配算法中,大多数将功率分配与子载波分配分为独立的2个部分进行独立求解,这样势必会降低系统性能,而实际上子载波分配和功率分配是密切相关的。为了有效地提升系统吞吐量,采用了迫零预编码技术,研究了一种在多个小区和多个子信道之间联合优化用户调度与功率分配的资源分配算法,该算法以最大化用户权重速率为目标,基于对偶分解理论,将原优化问题分解为多个独立优化的子问题。仿真结果表明,该算法与最优的穷尽分配算法相比性能有所降低,但有效地降低了复杂度,同时也能获得较好的性能。

In the resource allocation algorithms of MU-CoMP-JT（ multi-users coordinated multiple-points joint transmission）,most algorithms divided power allocation and subcarrier allocation into two parts and solved independently,which would reduce the performance of system. In fact the subcarrier allocation is closely related to power allocation. In order to effectively improve the system throughput,this paper uses zero-forcing precoding,and studies a joint resource allocation algorithm,which is joint optimization of the user scheduling and power allocation across multiple sub-channels and multiple cells. The algorithm aims to maximize user weight rate,decomposes the original optimization problem into multiple independent optimization sub-problems based on the theory of dual decomposition. The simulation results show that the proposed algorithm performance is slightly reduced compared to the optimal allocation algorithm,but it can effectively reduce computational complexity and get a good performance.