Design of near-optimal local likelihood search-based detection algorithm for coded large-scale MU-MIMO system

2020 ◽  
Vol 33 (12) ◽  
pp. e4436 ◽  
Author(s):  
Naga Raju Challa ◽  
Kalapraveen Bagadi
Keyword(s):  
Large Scale ◽  
Mimo System ◽  
Detection Algorithm ◽  
Local Likelihood

scholarly journals Low Complexity, Pairwise Layered Tabu Search for Large Scale MIMO Detection

2021 ◽  
Author(s):  
SOURAV CHAKRABORTY ◽  
Nirmalendu Bikas Sinha ◽  
Monojit Mitra
Keyword(s):  
Tabu Search ◽  
Upper Bound ◽  
Large Scale ◽  
Complexity Analysis ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Detection Performance ◽  
Mimo Detection

Abstract This paper presents a low complexity pairwise layered tabu search (PLTS) based detection algorithm for a large-scale multiple-input multiple-output (MIMO) system. The proposed algorithm can compute two layers simultaneously and reduce the effective number of tabu searches. A metric update strategy is developed to reuse the computations from past visited layers. Also, a precomputation technique is adapted to reduce the redundancy in computation within tabu search iterations. Complexity analysis shows that the upper bound of initialization complexity in the proposed algorithm reduces from O(Nt4) to O(Nt3). The detection performance of the proposed detector is almost the same as the conventional complex version of LTS for 64QAM and 16QAM modulations. However, the proposed detector outperforms the conventional system for 4QAM modulation, especially in 16x16 and 8x8 MIMO. Simulation results show that the per cent of complexity reduction in the proposed method is approximately 75% for 64x64, 64QAM and 85% for 64x64 16QAM systems to achieve a BER of 10-3. Moreover, we have proposed a layer-dependent iteration number that can further reduce the upper bound of complexity with minor degradation in detection performance.

scholarly journals Static and dynamic functional connectivity supports the configuration of brain networks associated with creative cognition

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Abhishek Uday Patil ◽  
Sejal Ghate ◽  
Deepa Madathil ◽  
Ovid J. L. Tzeng ◽  
Hsu-Wen Huang ◽  
...  
Keyword(s):  
Cognitive Processes ◽  
Large Scale ◽  
Brain Networks ◽  
Blood Oxygen Level Dependent ◽  
Detection Algorithm ◽  
Brain Regions ◽  
Creative Cognition ◽  
Network Flexibility ◽  
Community Detection Algorithm ◽  
Window Approach

AbstractCreative cognition is recognized to involve the integration of multiple spontaneous cognitive processes and is manifested as complex networks within and between the distributed brain regions. We propose that the processing of creative cognition involves the static and dynamic re-configuration of brain networks associated with complex cognitive processes. We applied the sliding-window approach followed by a community detection algorithm and novel measures of network flexibility on the blood-oxygen level dependent (BOLD) signal of 8 major functional brain networks to reveal static and dynamic alterations in the network reconfiguration during creative cognition using functional magnetic resonance imaging (fMRI). Our results demonstrate the temporal connectivity of the dynamic large-scale creative networks between default mode network (DMN), salience network, and cerebellar network during creative cognition, and advance our understanding of the network neuroscience of creative cognition.

scholarly journals Extended Coprime Array Configuration Generating Large-Scale Antenna Co-Array in Massive MIMO System

2019 ◽  
Vol 68 (8) ◽  
pp. 7841-7853 ◽  
Author(s):  
Wang Zheng ◽  
Xiaofei Zhang ◽  
Yunfei Wang ◽  
Mengjie Zhou ◽  
Qihui Wu
Keyword(s):  
Massive Mimo ◽  
Large Scale ◽  
Mimo System ◽  
Array Configuration ◽  
Coprime Array

scholarly journals Improved QR Decomposition-Based SIC Detection Algorithm for MIMO System

2013 ◽  
Vol 5 (4) ◽  
pp. 1251-1256 ◽  
Author(s):  
Li Liu ◽  
Jinkuan Wang ◽  
Fulai Liu ◽  
Xin Song ◽  
Yuhuan Wang
Keyword(s):  
Mimo System ◽  
Detection Algorithm ◽  
Qr Decomposition

scholarly journals On the machine learning–based smart beamforming for wireless virtualization with large‐scale MIMO system

2019 ◽  
Vol 30 (9) ◽  
Author(s):  
Naveen Naik Sapavath ◽  
Sunitha Safavat ◽  
Danda B. Rawat
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Mimo System ◽  
Wireless Virtualization
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