A Fast Antenna Selection Algorithm Based on Dissimilarity Coefficient in MIMO System

Author(s):  
ZhiBin Xie ◽  
ShuJuan Liu ◽  
YuBo Tian ◽  
PeiYu Yan
2014 ◽  
Vol 687-691 ◽  
pp. 3956-3962
Author(s):  
Nae Zheng ◽  
Xiu Kun Ren ◽  
Peng Dong ◽  
Shi Lei Zhu

The antenna number in distributed MIMO system is much larger than that in distributed antenna system (DAS) and traditional centralized MIMO system. Therefore adopting the existing antenna selection algorithms with excellent performance will make it difficult to realize the system due to the complexity of the algorithms. In order to solve the problem, a novel antenna selection algorithm performed at the base station (BS) is proposed according to the structural characteristics of the system. In the proposed algorithm, the antenna search scope is narrowed down by port selection based on the trace of the sub-channel matrices, and antennas with little contributions to the system capacity are removed gradually by iteratively updating the optimization parameter, which further reduces the complexity. When this algorithm is treated as the transmit antenna selection algorithm, its port selection process is performed by the user equipment, which can reduce the feedback overhead. Simulation results show that the proposed algorithm possesses the similar system capacity with the optimal algorithm.


Author(s):  
Tasher Ali Sheikh ◽  
Joyatri Bora ◽  
Md. Anwar Hussain

Background and Objectives: We propose here joint semi-orthogonal user selection and antenna selection algorithm based on precoding scheme. Methods: The focus of this proposed algorithm is to increase the system sumrate and decrease the complexity. We select and schedule users from a large number of users based on semi-orthogonality condition among them. Here, we select only the maximum channel gain antennas to maximize the system sumrate. Subsequently, the user selection and antenna selection have been scheduled in an adequate manner in order to obtain maximum system sumrate. We calculate the system sumrate for two scenarios: firstly, by considering the interference and secondly without considering the interference. We achieve maximum system sumrate at MMSE and lowest at without precoding while considering the interference. However, when we do not consider the interference we obtain lowest sumrate at MMSE and maximum at without precoding. Results and Conclusion: Here, we apply the precoding scheme to increase the system sumrate and we obtain approximately 20% to 35% higher system sumrate compared to without precoding, when interference is considered. Thus, we achieve higher sumrate in our proposed algorithms compared to other existing work.


Sign in / Sign up

Export Citation Format

Share Document