원문정보
보안공학연구지원센터(IJFGCN)
International Journal of Future Generation Communication and Networking
Vol.9 No.2
2016.02
pp.257-268
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In this paper, signal vector based detection (SVD) algorithm for spatial modulation (SM) is modified to achieve a near maximum-likelihood (ML) performance and reduces the complexity compared to ML. First, the proposed low-complexity SVD (LC-SVD) algorithm orders the antenna index list based on the angle between the received vector y and the channel vector j h , and then it estimates symbol by compensating the channel attenuation with transmitting antenna index list. We can trade-off between the performance and the complexity by changing the number of the candidate transmitting antennas. The theoretical analysis and simulation results show that the LC-SVD algorithm can achieve a near-ML performance with lower complexity.
목차
Abstract
1. Introduction
2. System Model
2.1. SM Modulator
2.2. MRC detector
2.3. ML-Optimum Detector
3. Low-Complexity Signal Vector Based Detection
3.1. SVD
3.2. Proposed LC-SVD
3.3. Complexity Analysis
4. Simulation Results
4.1. BER Performance
4.2. Comparison on Complexity
5. Conclusions
Acknowledgment
References
1. Introduction
2. System Model
2.1. SM Modulator
2.2. MRC detector
2.3. ML-Optimum Detector
3. Low-Complexity Signal Vector Based Detection
3.1. SVD
3.2. Proposed LC-SVD
3.3. Complexity Analysis
4. Simulation Results
4.1. BER Performance
4.2. Comparison on Complexity
5. Conclusions
Acknowledgment
References
저자정보
참고문헌
자료제공 : 네이버학술정보