Graph based low complexity MIMO detection with intermediate hard-decision

2012 ◽  
Author(s):  
Kangwoon Seo ◽  
Seokhyun Yoon
Keyword(s):  
Low Complexity ◽  
Mimo Detection ◽  
Hard Decision

scholarly journals Low-complexity Large MIMO Detection via Layered Belief Propagation in Beam Domain

2021 ◽  
pp. 1-1
Author(s):  
Takumi Takahashi ◽  
Antti Tolli ◽  
Shinsuke Ibi ◽  
Seiichi Sampei
Keyword(s):  
Belief Propagation ◽  
Low Complexity ◽  
Mimo Detection

Low Complexity MIMO Detection Using Complement and LSB Set Approximation

2021 ◽  
Author(s):  
Sourav Chakraborty ◽  
Nirmalendu Bikas Sinha ◽  
Monojit Mitra
Keyword(s):  
Low Complexity ◽  
Mimo Detection ◽  
Set Approximation

scholarly journals A Novel Iterative Discrete Estimation Algorithm for Low-Complexity Signal Detection in Uplink Massive MIMO Systems

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 980 ◽  
Author(s):  
Hui Feng ◽  
Xiaoqing Zhao ◽  
Zhengquan Li ◽  
Song Xing
Keyword(s):  
Computational Complexity ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Estimation Algorithm ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Base Station ◽  
Damping Factor ◽  
Mimo Detection ◽  
Discrete Estimation

In this paper, a novel iterative discrete estimation (IDE) algorithm, which is called the modified IDE (MIDE), is proposed to reduce the computational complexity in MIMO detection in uplink massive MIMO systems. MIDE is a revision of the alternating direction method of multipliers (ADMM)-based algorithm, in which a self-updating method is designed with the damping factor estimated and updated at each iteration based on the Euclidean distance between the iterative solutions of the IDE-based algorithm in order to accelerate the algorithm’s convergence. Compared to the existing ADMM-based detection algorithm, the overall computational complexity of the proposed MIDE algorithm is reduced from O N t 3 + O N r N t 2 to O N t 2 + O N r N t in terms of the number of complex-valued multiplications, where Ntand Nr are the number of users and the number of receiving antennas at the base station (BS), respectively. Simulation results show that the proposed MIDE algorithm performs better in terms of the bit error rate (BER) than some recently-proposed approximation algorithms in MIMO detection of uplink massive MIMO systems.

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