Residual neural network based joint transmit-receive antenna selection in MIMO system

2021 ◽  
Author(s):  
Zhibin Guo ◽  
Jiaxin Cai
2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Chaowei Wang ◽  
Weidong Wang ◽  
Cheng Wang ◽  
Shuai Wang ◽  
Yang Yu

Antenna selection has been regarded as an effective method to acquire the diversity benefits of multiple antennas while potentially reduce hardware costs. This paper focuses on receive antenna selection. According to the proportion between the numbers of total receive antennas and selected antennas and the influence of each antenna on system capacity, we propose a fast adaptive antenna selection algorithm for wireless multiple-input multiple-output (MIMO) systems. Mathematical analysis and numerical results show that our algorithm significantly reduces the computational complexity and memory requirement and achieves considerable system capacity gain compared with the optimal selection technique in the same time.


Author(s):  
Patel Sagar ◽  
Bhalani Jaymin

Spatial correlation is a critical impairment for practical Multiple Input Multiple Output (MIMO) wireless communication systems. To overcome from this issue, one of the solutions is receive antenna selection. Receive antenna selection is a low-cost, low-complexity and no requirement of feedback bit alternative option to capture many of the advantages of MIMO systems. In this paper, symbol error rate (SER) versus signal to noise ratio (SNR) performance comparasion of proposed receive antenna selection scheme for full rate non-orthogonal Space Time Block Code (STBC) is obtained using simulations in MIMO systems under spatially correlated channel at transmit and receive antenna compare with several existing receive antenna selection schemes. The performance of proposed receive antenna selection scheme is same as conventional scheme and beat all other existing schemes.


Author(s):  
Vighnesh S Bhat ◽  
Surabhi Garudanagiri Dayanand ◽  
Ananthanarayanan Chockalingam

2013 ◽  
Vol 10 (3) ◽  
pp. 91-99 ◽  
Author(s):  
Junling Wang ◽  
Ana Isabel Perez-Neira ◽  
Meiguo Gao

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