教授 博士生导师 硕士生导师
性别: 男
毕业院校: 北京航空航天大学
学位: 博士
所在单位: 信息与通信工程学院
学科: 通信与信息系统. 信号与信息处理. 电路与系统
办公地点: 创新园大厦A520
联系方式: Tel: 86-0411-84707719 实验室网址: http://wican.dlut.edu.cn
电子邮箱: mljin@dlut.edu.cn
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论文类型: 期刊论文
发表时间: 2019-03-07
发表刊物: ELECTRONICS LETTERS
收录刊物: SCIE、EI
卷号: 55
期号: 5
页面范围: 268-269
ISSN号: 0013-5194
关键字: Compressed sensing; Maximum likelihood; MIMO systems; Multiplexing equipment, Antenna matching; Compressive sensing; Detection performance; Euclidean distance; Information transmission; Maximum likelihood detectors; Multi input multi output systems; Space-shift keying, Antennas
摘要: Generalised space shift keying (GSSK) technique proposed for massive multi-input-multi-output systems has a higher information transmission rate due to the activation of multiple antennas at the same time, and also has significant advantage in terms of hardware cost. However, the maximum likelihood detector has a very high complexity which makes it computationally intractable for large-scale GSSK systems. In this Letter, a sparse detector is proposed by exploiting the inherent property of sparsity in GSSK. Different from the existing compressed sensing (CS)-based detectors, the proposed detector utilises Euclidean distance instead of inner product operation for antenna matching. Moreover, it can remove erroneous antenna indices by backtracking to promote the detection performance. The simulation results show that the proposed scheme outperforms the existing CS-based detectors while maintaining low complexity.