Symbol detection based on Voronoi surfaces with emphasis on superposition modulation
A challenging task when applying high-order digital modulation schemes is the complexity of the detector. Particularly, the complexity of the optimal a posteriori probability (APP) detector increases exponentially with respect to the number of bits per data symbol. This statement is also true for th...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2017-08-01
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| Series: | Digital Communications and Networks |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352864817300263 |
| _version_ | 1818413032193130496 |
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| author | Martin Damrath Peter Adam Hoeher Gilbert J.M. Forkel |
| author_facet | Martin Damrath Peter Adam Hoeher Gilbert J.M. Forkel |
| author_sort | Martin Damrath |
| collection | DOAJ |
| description | A challenging task when applying high-order digital modulation schemes is the complexity of the detector. Particularly, the complexity of the optimal a posteriori probability (APP) detector increases exponentially with respect to the number of bits per data symbol. This statement is also true for the Max-Log-APP detector, which is a common simplification of the APP detector. Thus it is important to design new detection algorithms which combine a sufficient performance with low complexity. In this contribution, a detection algorithm for two-dimensional digital modulation schemes which cannot be split-up into real and imaginary parts (like phase shift keying and phase-shifted superposition modulation (PSM)) is proposed with emphasis on PSM with equal power allocation. This algorithm exploits the relationship between Max-Log-APP detection and a Voronoi diagram to determine planar surfaces of the soft outputs over the entire range of detector input values. As opposed to state-of-the-art detectors based on Voronoi surfaces, a priori information is taken into account, enabling iterative processing. Since the algorithm achieves Max-Log-APP performance, even in the presence of a priori information, this implies a great potential for complexity reduction compared to the classical APP detection. |
| first_indexed | 2024-12-14T10:56:45Z |
| format | Article |
| id | doaj.art-37ae40bc549748638157a3608e70cd1e |
| institution | Directory Open Access Journal |
| issn | 2352-8648 |
| language | English |
| last_indexed | 2024-12-14T10:56:45Z |
| publishDate | 2017-08-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Digital Communications and Networks |
| spelling | doaj.art-37ae40bc549748638157a3608e70cd1e2022-12-21T23:04:53ZengKeAi Communications Co., Ltd.Digital Communications and Networks2352-86482017-08-013314114910.1016/j.dcan.2017.01.001Symbol detection based on Voronoi surfaces with emphasis on superposition modulationMartin DamrathPeter Adam HoeherGilbert J.M. ForkelA challenging task when applying high-order digital modulation schemes is the complexity of the detector. Particularly, the complexity of the optimal a posteriori probability (APP) detector increases exponentially with respect to the number of bits per data symbol. This statement is also true for the Max-Log-APP detector, which is a common simplification of the APP detector. Thus it is important to design new detection algorithms which combine a sufficient performance with low complexity. In this contribution, a detection algorithm for two-dimensional digital modulation schemes which cannot be split-up into real and imaginary parts (like phase shift keying and phase-shifted superposition modulation (PSM)) is proposed with emphasis on PSM with equal power allocation. This algorithm exploits the relationship between Max-Log-APP detection and a Voronoi diagram to determine planar surfaces of the soft outputs over the entire range of detector input values. As opposed to state-of-the-art detectors based on Voronoi surfaces, a priori information is taken into account, enabling iterative processing. Since the algorithm achieves Max-Log-APP performance, even in the presence of a priori information, this implies a great potential for complexity reduction compared to the classical APP detection.http://www.sciencedirect.com/science/article/pii/S2352864817300263Digital modulationDemodulationDetection algorithmsLinear approximation |
| spellingShingle | Martin Damrath Peter Adam Hoeher Gilbert J.M. Forkel Symbol detection based on Voronoi surfaces with emphasis on superposition modulation Digital Communications and Networks Digital modulation Demodulation Detection algorithms Linear approximation |
| title | Symbol detection based on Voronoi surfaces with emphasis on superposition modulation |
| title_full | Symbol detection based on Voronoi surfaces with emphasis on superposition modulation |
| title_fullStr | Symbol detection based on Voronoi surfaces with emphasis on superposition modulation |
| title_full_unstemmed | Symbol detection based on Voronoi surfaces with emphasis on superposition modulation |
| title_short | Symbol detection based on Voronoi surfaces with emphasis on superposition modulation |
| title_sort | symbol detection based on voronoi surfaces with emphasis on superposition modulation |
| topic | Digital modulation Demodulation Detection algorithms Linear approximation |
| url | http://www.sciencedirect.com/science/article/pii/S2352864817300263 |
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