Abstract
The multiple-input multiple-output (MIMO) technology can make full use of spectrum and increase the communication throughput. In the coded MIMO system, the main challenge of soft detection is to efficiently generate the loglikelihood ratios (LLR) values for channel decoder. The exact maximum a posteriori (MAP) probability detection can guarantee the optimal performance, but its realization is difficult due to its enormous complexity. In this paper, we propose efficient soft detection algorithms based on differential metrics. We apply the differential metrics for the list sphere decoding, and propose the list gradient algorithm. We further propose a novel algorithm that can generate the values of LLR and provide a trade-off between performance and complexity. The proposed algorithms do not need the QR decomposition and matrix inversion. The proposed algorithms have fixed complexity, and are appropriate for pipelined hardware implementation. The numerical results verify the efficiency of our algorithms.
| Original language | English |
|---|---|
| Title of host publication | 2017 IEEE 85th Vehicular Technology Conference, VTC Spring 2017 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Volume | 2017-June |
| ISBN (Electronic) | 9781509059324 |
| DOIs | |
| Publication status | Published - 2017 Nov 14 |
| Event | 85th IEEE Vehicular Technology Conference, VTC Spring 2017 - Sydney, Australia Duration: 2017 Jun 4 → 2017 Jun 7 |
Other
| Other | 85th IEEE Vehicular Technology Conference, VTC Spring 2017 |
|---|---|
| Country | Australia |
| City | Sydney |
| Period | 17-06-04 → 17-06-07 |
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All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics
Cite this
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Efficient Soft MIMO Detection Algorithms Based on Differential Metrics. / Chang, Wang Yueh; Chang, Ming-Xian.
2017 IEEE 85th Vehicular Technology Conference, VTC Spring 2017 - Proceedings. Vol. 2017-June Institute of Electrical and Electronics Engineers Inc., 2017. 8108240.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Efficient Soft MIMO Detection Algorithms Based on Differential Metrics
AU - Chang, Wang Yueh
AU - Chang, Ming-Xian
PY - 2017/11/14
Y1 - 2017/11/14
N2 - The multiple-input multiple-output (MIMO) technology can make full use of spectrum and increase the communication throughput. In the coded MIMO system, the main challenge of soft detection is to efficiently generate the loglikelihood ratios (LLR) values for channel decoder. The exact maximum a posteriori (MAP) probability detection can guarantee the optimal performance, but its realization is difficult due to its enormous complexity. In this paper, we propose efficient soft detection algorithms based on differential metrics. We apply the differential metrics for the list sphere decoding, and propose the list gradient algorithm. We further propose a novel algorithm that can generate the values of LLR and provide a trade-off between performance and complexity. The proposed algorithms do not need the QR decomposition and matrix inversion. The proposed algorithms have fixed complexity, and are appropriate for pipelined hardware implementation. The numerical results verify the efficiency of our algorithms.
AB - The multiple-input multiple-output (MIMO) technology can make full use of spectrum and increase the communication throughput. In the coded MIMO system, the main challenge of soft detection is to efficiently generate the loglikelihood ratios (LLR) values for channel decoder. The exact maximum a posteriori (MAP) probability detection can guarantee the optimal performance, but its realization is difficult due to its enormous complexity. In this paper, we propose efficient soft detection algorithms based on differential metrics. We apply the differential metrics for the list sphere decoding, and propose the list gradient algorithm. We further propose a novel algorithm that can generate the values of LLR and provide a trade-off between performance and complexity. The proposed algorithms do not need the QR decomposition and matrix inversion. The proposed algorithms have fixed complexity, and are appropriate for pipelined hardware implementation. The numerical results verify the efficiency of our algorithms.
UR - http://www.scopus.com/inward/record.url?scp=85040577417&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85040577417&partnerID=8YFLogxK
U2 - 10.1109/VTCSpring.2017.8108240
DO - 10.1109/VTCSpring.2017.8108240
M3 - Conference contribution
AN - SCOPUS:85040577417
VL - 2017-June
BT - 2017 IEEE 85th Vehicular Technology Conference, VTC Spring 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -