在超密集网络场景中, 针对以用户为中心的重叠虚拟小区系统的和速率的最大化, 提出了一种基于效用函数最优化模型的功率分配方案。通过分层交替迭代算法求解最佳功率分配, 首先将原问题分解为功率分割和虚拟功率分配两个子问题; 然后在高层功率分割中引入拉格朗日函数, 求解出一种基于均衡策略的最佳功率分割算法, 在底层利用虚拟功率完成进一步的功率分配。由于功率分割系数采用了最大化信干漏比(SLNR)的特征矢量形式, 从而实现了信号增强与干扰减少之间的均衡。仿真结果表明, 该算法在性能上优于传统的功率分配算法, 有效减少了干扰, 提高了系统的和速率。

In the ultra-dense network scenario, a power allocation scheme based on the utility function optimization model is proposed to maximize the sum rate of user-centric overlapped virtual cell systems. The optimal power allocation is obtained based on the hierarchical alternating iterative algorithm. Firstly, the original problem is decomposed into two sub-problems: power splitting and virtual power allocation. Secondly, an optimal power splitting algorithm based on equilibrium strategy is obtained by introducing the Lagrangian function at the upper layer, and further power allocation is achieved by using the virtual power at the bottom layer. Since the power splitting coefficient takes the form of eigenvector which maximizing Signal to Leakage plus Noise Ratio (SLNR), a balanced effect on signal enhancement and interference reduction is achieved. Simulation results show that the proposed algorithm is superior to conventional power allocation algorithms in performance, which can effectively reduce the interference and increase the sum rate of the system.