Research Article
Linear Precoding for Massive MIMO Systems with IQ Imbalance
@INPROCEEDINGS{10.1007/978-3-319-73564-1_48, author={Juan Liu and Jianxin Dai and Chonghu Cheng and Zhiliang Huang}, title={Linear Precoding for Massive MIMO Systems with IQ Imbalance}, proceedings={Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part I}, proceedings_a={MLICOM}, year={2018}, month={2}, keywords={Massive MIMO IQ imbalance Minimum mean square error Linear precoding Bit error rate}, doi={10.1007/978-3-319-73564-1_48} }- Juan Liu
Jianxin Dai
Chonghu Cheng
Zhiliang Huang
Year: 2018
Linear Precoding for Massive MIMO Systems with IQ Imbalance
MLICOM
Springer
DOI: 10.1007/978-3-319-73564-1_48
Abstract
The massive multiple-input multiple-output (MIMO) system is one of the most promising techniques, which extends degrees of freedom, increases the throughput of systems, supports more data streams and decreases transmit power. However, using cheap hardware in massive MIMO system can affect the overall performance of the system and deteriorate the user experience. The IQ imbalance caused by using cheap hardware is one of the important factors affecting system performance. To solve this problem, this paper proposes the design of precoding matrix based on the minimum mean square error (MMSE) criterion to suppress the influence of IQ imbalance on system performance. The numerical simulation results validate the effectiveness of the proposed algorithm, and show that the bit error rate (BER) performance of the proposed algorithm has obvious better than that of ZF, BD and WL-BD precoding.
