Error Vector Magnitude-Based Low Complexity Adaptive Power Allocation in SM-MIMO System
In this article, we propose the error vector magnitude (EVM)-based adaptive power allocation (PA) for spatial modulation (SM) multiple-input-multiple-output (MIMO) system to optimize the minimum squared Euclidean distance and reduce the system complexity. We first investigate the typical Euclidean d...
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| Published in | IEEE systems journal Vol. 16; no. 4; pp. 6164 - 6174 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.12.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1932-8184 1937-9234 |
| DOI | 10.1109/JSYST.2022.3149868 |
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| Summary: | In this article, we propose the error vector magnitude (EVM)-based adaptive power allocation (PA) for spatial modulation (SM) multiple-input-multiple-output (MIMO) system to optimize the minimum squared Euclidean distance and reduce the system complexity. We first investigate the typical Euclidean distance (ED)-based PA (ED-PA) algorithm. Second, an EVM-based ED-PA algorithm is proposed, where a simplified closed-form PA solution for the quadrature amplitude modulation is obtained in the case of two transmit antennas. For more transmit antennas, we further propose a low complexity-PA (LC-PA) algorithm, where all the transmit antennas are grouped with two antennas in each group and the proposed EVM-based ED-PA algorithm is utilized to assign the power within each group. Numerical results reveal that the proposed EVM-based ED-PA and LC-PA algorithms have considerably lower complexity and can achieve the optimal average bit error rate (ABER) and suboptimal ABER performance at low-and-moderate signal-to-noise ratio (SNR) region and high-SNR region, respectively, compared with the typical PA algorithms in SM-MIMO system. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1932-8184 1937-9234 |
| DOI: | 10.1109/JSYST.2022.3149868 |