Title :
Sparse Coding Quantization for Downlink MU-MIMO with Limited CSI Feedback
Author :
Qi Wang ; Hao Feng ; Cimini, Leonard J. ; Greenstein, Larry J. ; Chan, Douglas S. ; Hedayat, Ahmadreza
Author_Institution :
Univ. of Delaware, Newark, DE, USA
Abstract :
A novel quantization method, sparse coding quantization (SCQ), is proposed for downlink multiuser multiple-input multiple-output (MU-MIMO) systems. Compared to conventional vector quantization (VQ), SCQ utilizes a linear combination of several codewords rather than a single one to represent the channel matrix. Both analytical and simulation results reveal that the proposed technique can achieve the same sum rate performance as VQ at a reasonable cost in feedback overhead. Thus, SCQ is more practical because it significantly reduces the time and space complexity for generating, searching and storing the codebook. % The net capacity, which indicates the tradeoff between sum rate and overhead, is also studied.
Keywords :
MIMO communication; vector quantisation; CSI feedback; MU-MIMO; channel matrix; downlink multiuser multiple-input multiple-output systems; sparse coding quantization; vector quantization; Antennas; Complexity theory; MIMO; Quantization (signal); Signal to noise ratio; Simulation; Vectors;
Conference_Titel :
Military Communications Conference, MILCOM 2013 - 2013 IEEE
Conference_Location :
San Diego, CA
DOI :
10.1109/MILCOM.2013.216