scholarly journals Parallel low-complexity MIMO detection algorithm using QR decomposition and Alamouti space-time code

2010 ◽  
Author(s):  
Maher Arar ◽  
Abbas Yongacoglu
Keyword(s):  
Low Complexity ◽  
Detection Algorithm ◽  
Qr Decomposition ◽  
Space Time ◽  
Mimo Detection ◽  
Time Code

scholarly journals A Very Low Complexity QRD-M MIMO Detection Based on Adaptive Search Area

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 756 ◽  
Author(s):  
Bong-seok Kim ◽  
Sang-Dong Kim ◽  
Dongjun Na ◽  
Kwonhue Choi
Keyword(s):  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Symbol Error Rate ◽  
Detection Algorithm ◽  
Qr Decomposition ◽  
Noise Power ◽  
Adaptive Search ◽  
Mimo Detection ◽  
Channel Condition ◽  
Search Area

We propose a low complexity QR decomposition (QRD)-M multiple input multiple output (MIMO) detection algorithm based on adaptive search area. Unlike the conventional QRD-M MIMO detection algorithm, which determines the next survivor path candidates after searching over the entire constellation points at each detection layer, the proposed algorithm adaptively restricts the search area to the minimal neighboring constellation points of the estimated QRD symbol according to the instantaneous channel condition at each layer. First, we set up an adaptation rule for search area using two observations that inherently reflect the instantaneous channel condition, that is, the diagonal terms of the channel upper triangle matrix after QR decomposition and Euclidean distance between the received symbol vector and temporarily estimated symbol vector by QRD detection. In addition, it is found that the performance of the QRD-M algorithm degrades when the diagonal terms of the channel upper triangle matrix instantaneously decrease. To overcome this problem, the proposed algorithm employs the ratio of each diagonal term and total diagonal terms. Moreover, the proposed algorithm further decreases redundant complexity by considering the location of initial detection symbol in constellation. By doing so, the proposed algorithm effectively achieves performance near to the maximum likelihood detection algorithm, while maintaining the overall average computation complexity much lower than that of the conventional QRD-M systems. Especially, the proposed algorithm achieves reduction of 76% and 26% computational complexity with low signal to noise ratio (SNR) and high SNR, compared with the adaptive QRD-M algorithm based on noise power. Moreover, simulation results show that the proposed algorithm achieves both low complexity and lower symbol error rate compared with the fixed QRD-M algorithms.

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.

Efïicient and low-complexity space time code for massive MIMO RFID systems

2017 ◽  
Author(s):  
Mohamed S. Abouzeid ◽  
Lukasz Lopacinski ◽  
Eckhard Grass ◽  
Thomas Kaiser ◽  
Rolf Kraemer
Keyword(s):  
Massive Mimo ◽  
Low Complexity ◽  
Space Time ◽  
Time Code ◽  
Rfid Systems
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