基于DNN的Sub-6 GHz辅助毫米波网络功率分配算法

DNN-based Sub-6 GHz assisted millimeter wave network power allocation algorithm

针对毫米波系统功率控制测量伴随的信令开销与功耗,以及迭代操作带来的复杂度问题,提出了一种使用Sub-6 GHz频段预测毫米波链路功率分配的算法。首先,分析了Sub-6 GHz频段信道信息到毫米波频段最佳功率分配的映射关系。其次,基于这种映射关系设计了一种深度神经网络(DNN)模型,通过使用加权最小均方误差(WMMSE)准则对神经网络进行了不同场景的训练,实现利用Sub-6 GHz频段对毫米波频段信道的功率分配进行预测。仿真结果表明,所提算法在仅采用Sub-6 GHz频段信道信息的情况下,与毫米波频段下的WMMSE算法相比,可在耗时少于其0.1%的同时,获得其不小于97%的和速率性能。

Aimed at the problems of the signaling cost and power consumption in the power control measurement of the millimeter wave system,as well as the complexity caused by iteration operations,a millimeter wave link power allocation prediction algorithm using the Sub-6 GHz frequency band was proposed.Firstly,the mapping between the Sub-6 GHz band channel information and the optimal power allocation of the millimeter wave band was analyzed.Then,a deep neural network(DNN)model was utilized to realize this mapping function.To predict the power allocation of millimeter wave channel with Sub-6 GHz channel as input,the neural network was trained with the weighted mean square error minimization method(WMMSE)as the supervisor in different scenarios.The simulation results show that compared with the WMMSE algorithm in millimeter wave band,the proposed algorithm can obtain more than 97%of its sum-rate performance while taking less than 0.1%of the time.