scholarly journals Low‐complexity signal detection for large‐scale MIMO systems with second‐order Richardson method

2020 ◽  
Vol 56 (9) ◽  
pp. 467-469
Author(s):  
Imran A. Khoso ◽  
Xiaofei Zhang ◽  
Abdul Hayee Shaikh
Keyword(s):  
Signal Detection ◽  
Large Scale ◽  
Mimo Systems ◽  
Low Complexity ◽  
Second Order ◽  
Richardson Method

scholarly journals Low-Complexity Soft-Output Signal Detection Based on Gauss–Seidel Method for Uplink Multiuser Large-Scale MIMO Systems

2015 ◽  
Vol 64 (10) ◽  
pp. 4839-4845 ◽  
Author(s):  
Linglong Dai ◽  
Xinyu Gao ◽  
Xin Su ◽  
Shuangfeng Han ◽  
Chih-Lin I ◽  
...  
Keyword(s):  
Signal Detection ◽  
Output Signal ◽  
Large Scale ◽  
Mimo Systems ◽  
Low Complexity ◽  
Seidel Method

scholarly journals Low‐complexity near‐optimal signal detection for uplink large‐scale MIMO systems

2014 ◽  
Vol 50 (18) ◽  
pp. 1326-1328 ◽  
Author(s):  
Xinyu Gao ◽  
Linglong Dai ◽  
Yongkui Ma ◽  
Zhaocheng Wang
Keyword(s):  
Signal Detection ◽  
Large Scale ◽  
Mimo Systems ◽  
Low Complexity ◽  
Optimal Signal

scholarly journals Low-complexity sparse-aware multiuser detection for large-scale MIMO systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Rong Ran ◽  
Hayoung Oh
Keyword(s):  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Finite Alphabet ◽  
Multiuser Detectors ◽  
Input Multiple Output ◽  
Error Detector ◽  
Significant Performance

AbstractSparse-aware (SA) detectors have attracted a lot attention due to its significant performance and low-complexity, in particular for large-scale multiple-input multiple-output (MIMO) systems. Similar to the conventional multiuser detectors, the nonlinear or compressive sensing based SA detectors provide the better performance but are not appropriate for the overdetermined multiuser MIMO systems in sense of power and time consumption. The linear SA detector provides a more elegant tradeoff between performance and complexity compared to the nonlinear ones. However, the major limitation of the linear SA detector is that, as the zero-forcing or minimum mean square error detector, it was derived by relaxing the finite-alphabet constraints, and therefore its performance is still sub-optimal. In this paper, we propose a novel SA detector, named single-dimensional search-based SA (SDSB-SA) detector, for overdetermined uplink MIMO systems. The proposed SDSB-SA detector adheres to the finite-alphabet constraints so that it outperforms the conventional linear SA detector, in particular, in high SNR regime. Meanwhile, the proposed detector follows a single-dimensional search manner, so it has a very low computational complexity which is feasible for light-ware Internet of Thing devices for ultra-reliable low-latency communication. Numerical results show that the the proposed SDSB-SA detector provides a relatively better tradeoff between the performance and complexity compared with several existing detectors.

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