Optimization of resource allocation in FDD massive MIMO systems  

作　　者：Jun Cai Chuan Yin Youwei Ding 

机构地区：[1]School of Artificial Intelligence and Information Technology,Nanjing University of Chinese Medicine,Nanjing 210046,China [2]School of Electronic and Information,Hangzhou Dianzi University,Hangzhou 310018,Zhejiang,China

出　　处：《Digital Communications and Networks》2024年第1期117-125,共9页数字通信与网络（英文版）

基　　金：supported by the foundation of National Key Laboratory of Electromagnetic Environment(Grant No.JCKY2020210C 614240304);Natural Science Foundation of ZheJiang province(LQY20F010001);the National Natural Science Foundation of China under grant numbers 82004499;State Key Laboratory of Millimeter Waves under grant numbers K202012.

摘　　要：The performance of massive MIMO systems relies heavily on the availability of Channel State Information at the Transmitter(CSIT).A large amount of work has been devoted to reducing the CSIT acquisition overhead at the pilot training and/or CsI feedback stage.In fact,the downlink communication generally includes three stages,i.e.,pilot training,CsI feedback,and data transmission.These three stages are mutually related and jointly determine the overall system performance.Unfortunately,there exist few studies on the reduction of csIT acquisition overhead from the global point of view.In this paper,we integrate the Minimum Mean Square Error(MMSE)channel estimation,Random Vector Quantization(RVQ)based limited feedback and Maximal Ratio Combining(MRC)precoding into a unified framework for investigating the resource allocation problem.In particular,we first approximate the covariance matrix of the quantization error with a simple expression and derive an analytical expression of the received Signal-to-Noise Ratio(SNR)based on the deterministic equivalence theory.Then the three performance metrics(the spectral efficiency,energy efficiency,and total energy consumption)oriented problems are formulated analytically.With practical system requirements,these three metrics can be collaboratively optimized.Finally,we propose an optimization solver to derive the optimal partition of channel coherence time.Experiment results verify the benefits of the proposed resource allocation schemes under three different scenarios and illustrate the tradeoff of resource allocation between three stages.

关 键 词：Massive MIMO FDD CSIT Resource allocation 

分 类 号：TN92[电子电信—通信与信息系统]