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Article Dans Une Revue Radio Science Année : 2022

Precoded Large Scale Multi‐User‐MIMO System Using Likelihood Ascent Search for Signal Detection

Résumé

Multiple antennas at each User Equipment (UE) and/or thousands of antennas at the Base Station comprise the extremely spectrum efficient large scale Multi-User Multiple Input Multiple Output (MU-MIMO) system (BS). Due to space constraints, the closely spaced numerous antennas at each UE may cause Inter Antenna Interference (IAI). Furthermore, when one UE comes into contact with another UE in the same cellular network, Multi-User Interference (MUI) may be introduced to the received signal. To mitigate IAI, efficient precoding pre-coding is necessary at each UE, and the MUI present at the BS can be cancelled by efficient Multi-user Detection (MUD) techniques. The majority of earlier literatures deal with one or more of these interferences. This paper implements a joint pre-coding and MUD, Lenstra-Lovasz (LLL) based Lattice Reduction (LR) assisted Likelihood Accent Search (LAS) (LLL-LR-LAS), to mitigate IAI and MUI simultaneously LLL-based LR pre-coding mitigates IAI at each UE, and the LAS algorithm is a neighbourhood search-based MUD that cancels BS MUI. The proposed approaches' performance was evaluated using Bit Error Rate (BER) analysis, and their complexity were determined using multiplication and addition.
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hal-03890650 , version 1 (20-12-2022)

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Kalapraveen Bagadi, Chinthaginjala V. Ravikumar, Mohammad Alibakhshikenari, Nagaraj Challa, A. Rajesh, et al.. Precoded Large Scale Multi‐User‐MIMO System Using Likelihood Ascent Search for Signal Detection. Radio Science, 2022, 57 (12), pp.e2022RS007573. ⟨10.1029/2022RS007573⟩. ⟨hal-03890650⟩
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