A Novel Deep Neural Network Based Antenna Selection Architecture for Spatial Modulation Systems

被引:4
|
作者
Arslan, Ilker Ahmet [1 ]
Altin, Gokhan [2 ]
机构
[1] Natl Def Univ, Hezarfen Aeronaut & Space Technol Inst, TR-34149 Istanbul, Turkey
[2] Natl Def Univ, Turkish Air Force Acad, Dept Elect Engn, Istanbul, Turkey
关键词
MIMO systems; Spatial modulation; Transmit antenna selection; Deep neural network;
D O I
10.1109/ICEST52640.2021.9483468
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
With the constantly developing technology, the speed and accuracy requirement of communication systems are increasing day by day. Spatial modulation (SM) is a recent and promising technique which additionally uses antenna indices for multiple input multiple output (MIMO) systems. In order to add another degree of freedom to SM's efficiency, transmit antenna selection (TAS) algorithms are a crucial field to study. On the other hand, use of artificial intelligence significantly developed in nowadays in wide variety of areas such as biology, robotics, automation etc. The main purpose of this study is to realize TAS for SM systems using deep neural network (DNN). Besides, the processing load of the proposed DNN is reduced without involving the repetitive parts of the TAS metric which is not studied in the literature as far as we know. It is shown that the proposed DNN based TAS algorithm outperforms existing studies in terms of symbol error rate.
引用
收藏
页码:141 / 144
页数:4
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