Massive Mimo Channel Estimation Based On Block Iterative Support Detection
2016 IEEE Wireless Communications and Networking Conference(2016)
摘要
Massive MIMO has become a promising key technology for future 5G wireless communications to increase the channel capacity and link reliability. However, with greatly increased number of transmit antennas at the base station (BS) in massive MIMO systems, the pilot overhead for accurate acquisition of channel state information (CSI) will be prohibitively high. To address this issue, we propose a block iterative support detection (block- ISD) based algorithm for channel estimation to reduce the pilot overhead. The proposed block-ISD algorithm fully exploits the block sparsity inherent in the block-sparse equivalent channel impulse response (CIR) generated by considering the spatial correlations of MIMO channels. Furthermore, unlike conventional greedy compressive sensing (CS) algorithms that rely on prior knowledge of the channel sparsity level, block-ISD relaxes this demanding requirement and is thus more practically appealing. Simulation results demonstrate that block-ISD yields better normalized mean square error (NMSE) performance than classical CS algorithms, and achieve a reduction of 87.5% pilot overhead than conventional channel estimation techniques.
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关键词
massive MIMO channel estimation,block iterative support detection,5G wireless communications,channel capacity,link reliability,transmit antennas,base station,channel state information,CSI,block-ISD based algorithm,pilot overhead reduction,block-sparse equivalent channel impulse response,CIR,spatial correlations,greedy compressive sensing algorithm,CS algorithms,channel sparsity level,normalized mean square error performance,NMSE performance
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