Improved sparse error recovery approach for detecting QAM signals in overloaded massive MIMO systems
ID:138 View Protection:ATTENDEE Updated Time:2020-08-05 10:17:28 Hits:365 Oral Presentation

Start Time:2020-06-08 14:40(Asia/Shanghai)

Duration:20min

Session:S Special Session » SS14Dependent Source Separation

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Abstract
With a convenient concatenation of a convex relaxation-based detector and a simple greedy algorithm, we propose an improved Sparse error Recovery Detection approach (PDSR) for massive Multiple Input Multiple Output (m-MIMO) systems that, in particular, transmit QAM signals. The proposed PDSR approach can perform well in situations, where the classical one, either acts poorly or completely fails. We further propose an Alternating Direction Method of Multipliers (ADMM)-based solver for the convex detector, which is advantageous in maintaining an affordable complexity to the overall proposed detection scheme. Numerical experiments show the efficiency of our approach, especially when applied to overloaded m-MIMO systems.
Keywords
Massive MIMO (m-MIMO); Signal detection; Convex optimization; ADMM; Greedy algorithms; Compressive sensing
Speaker
Yacine Meslem
Ecole Militaire Polytechnique, Algeria

Submission Author
Yacine Meslem Ecole Militaire Polytechnique, Algeria
Abdeldjalil A飐sa-El-Bey IMT Atlantique, France
Mustapha Djeddou Military Polytechnic School, Algeria
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    Jun 08

    2020

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    Jun 11

    2020

  • Jan 12 2020

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  • Apr 15 2020

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  • Dec 31 2020

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