Low-Complexity Detection for Index Modulation Multiple Access

Index modulation multiple access (IM-MA) is recently proposed to exploit the IM concept to the uplink multiple access system, where multiple users transmit their own signals via the selected time slots. However, the computational complexity of the optimal maximum-likelihood (ML) detection in IM-MA i...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE wireless communications letters Ročník 9; číslo 7; s. 943 - 947
Hlavní autoři: Li, Jun, Li, Qiang, Dang, Shuping, Wen, Miaowen, Jiang, Xue-Qin, Peng, Yuyang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.07.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
bit error rate
Complexity
Computational complexity
Computer simulation
Electronic mail
Index modulation
Indexes
Likelihood ratio
Media
Modulation
multi-user system
Multiple access
OFDM
Permutations
Wireless communication
ISSN:2162-2337, 2162-2345
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Index modulation multiple access (IM-MA) is recently proposed to exploit the IM concept to the uplink multiple access system, where multiple users transmit their own signals via the selected time slots. However, the computational complexity of the optimal maximum-likelihood (ML) detection in IM-MA is tremendously high when the number of users or time slots is large. In this letter, we propose a low-complexity detection method for IM-MA, which is inspired by the log likelihood ratio (LLR) algorithm. In addition, because of the heavy search burden for all LLR values, we further propose a suboptimal method to determine the permutation set, which records the number of users allocated to each time slot. Simulation results and the complexity analysis verify that the proposed detection performs closely to the optimal ML detection with reduced computational complexity.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2162-2337
2162-2345
DOI:10.1109/LWC.2020.2974730