Low-complexity near-optimal signal detection in underdetermined large-MIMO systems

2012 ◽  
Author(s):  
Tanumay Datta ◽  
N. Srinidhi ◽  
A. Chockalingam ◽  
B. Sundar Rajan
Keyword(s):  
Signal Detection ◽  
Mimo Systems ◽  
Low Complexity ◽  
Optimal Signal

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 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 Soft-Output Signal Detection Based on Improved Kaczmarz Iteration Algorithm for Uplink Massive MIMO System

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1564
Author(s):  
Hebiao Wu ◽  
Bin Shen ◽  
Shufeng Zhao ◽  
Peng Gong
Keyword(s):  
Signal Detection ◽  
Output Signal ◽  
Mimo Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Base Station ◽  
Matrix Inversion ◽  
Iteration Algorithm

For multi-user uplink massive multiple input multiple output (MIMO) systems, minimum mean square error (MMSE) criterion-based linear signal detection algorithm achieves nearly optimal performance, on condition that the number of antennas at the base station is asymptotically large. However, it involves prohibitively high complexity in matrix inversion when the number of users is getting large. A low-complexity soft-output signal detection algorithm based on improved Kaczmarz method is proposed in this paper, which circumvents the matrix inversion operation and thus reduces the complexity by an order of magnitude. Meanwhile, an optimal relaxation parameter is introduced to further accelerate the convergence speed of the proposed algorithm and two approximate methods of calculating the log-likelihood ratios (LLRs) for channel decoding are obtained as well. Analysis and simulations verify that the proposed algorithm outperforms various typical low-complexity signal detection algorithms. The proposed algorithm converges rapidly and achieves its performance quite close to that of the MMSE algorithm with only a small number of iterations.

Sign in / Sign up

Export Citation Format

Share Document