Journal
JOURNAL OF SUPERCOMPUTING
Volume 78, Issue 5, Pages 7059-7077Publisher
SPRINGER
DOI: 10.1007/s11227-021-04163-y
Keywords
MIMO communications; Maximum likelihood detection; Parallel computing; Generalized spatial modulation
Categories
Funding
- Spanish Ministry of Science, Innovation and Universities
- European Union [RTI2018- 098085-BC41]
- GVA [PROMETEO/2019/109, RED 2018-102668-T]
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Generalized Spatial Modulation is a technique designed to enhance transmission efficiency in MIMO systems, but retrieving sent signals accurately is challenging and computationally expensive. This paper proposes a parallel method using OpenMP for computing the maximum likelihood solution, which is faster and significantly reduces worst-case computing times compared to the sequential version.
Generalized Spatial Modulation is a recently developed technique that is designed to enhance the efficiency of transmissions in MIMO Systems. However, the procedure for correctly retrieving the sent signal at the receiving end is quite demanding. Specifically, the computation of the maximum likelihood solution is computationally very expensive. In this paper, we propose a parallel method for the computation of the maximum likelihood solution using the parallel computing library OpenMP. The proposed parallel algorithm computes the maximum likelihood solution faster than the sequential version, and substantially reduces the worst-case computing times.
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