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: 2020-01-01
发表刊物: IEEE ACCESS
收录刊物: SCIE
卷号: 8
页面范围: 44643-44651
ISSN号: 2169-3536
关键字: Receiving antennas; MIMO communication; Modulation; Transmitting antennas; Resource management; Bit error rate; Multiple-input-multiple-output (MIMO); pre-coding aided spatial modulation; power allocation; bit error rate (BER)
摘要: Pre-coding aided spatial modulation (PSM) is a recently introduced concept that achieves low complexity and low cost at the receiver. However, it is only suitable for the symmetric or under-determined system due to the utilization of the linear pre-coding. In this paper, a novel PSM-based transmission strategy termed as grouped pre-coding aided spatial modulation (group PSM) is proposed for the over-determined MIMO system where the number of receive antennas is larger than the number of transmit antennas. In our group PSM scheme, the receive antennas are equally divided into several groups. A single receive antenna group is selected during each time slot and the index of the receive antenna group is used for conveying extra information bits. We design a low complexity detection method for the proposed scheme and derive the bit error rate expression. To further improve the performance of group PSM, we propose a power allocation method, where the power allocated for each receive antenna group is optimized based on maximizing the minimum Euclidean distance between received group PSM signal constellations. We also generalize our group PSM scheme in order to improve the multiplexing gain and flexibility, where a particular subset of receive antenna groups is activated so as to convey more information bits. Our simulation results validate the accuracy of the theoretical analysis and demonstrate that both the proposed group PSM and generalized group PSM schemes achieve good performance and significantly increase the scalability of PSM in practice.