Paper Info
Title
Optimal Massive MIMO Detection for 5G Communication Systems via Hybrid n-Bit Heuristic Assisted-VBLAST
Abstract
Being increasingly spectral and energy efficient, massive multiple-input multiple-output (MIMO) is envisaged as a potential technology for fifth generation (5G) wireless communication networks. Radio spectrum has become a scarce resource in wireless communications and consequently imposes excessive cost on the high data rate transmission. Several linear and non linear detection techniques such as Zero-Forcing (ZF), Minimum Mean Square Error (MMSE), and Vertical Bell-Labs Layered Space Time (VBLAST) have been introduced. The purpose of such schemes is to mitigate the signal detection problems which are based on trade-offs between the bit error rate (BER) performance and computational complexities. The challenge in the design of massive-MIMO systems is developing less complex and efficient detection algorithms. The problem in building a receiver for massive-MIMO is to de-correlate the spatial signatures on the receiver antenna array. In this paper, we propose a novel algorithm viz: Hybrid n-Bit Heuristic Assisted-VBLAST (HHAV) to perform an optimum decoding. We have simulated this structure in dynamic Rayleigh fading channel. We have also evaluated the AMP algorithm with two threshold functions which include AMP with ternary distribution (AMPT) and AMP with Gaussian distribution (AMPG). Numerical results confirm that HHAV algorithm performs significantly better than the in vogue aforementioned detection systems as introduced in recent years.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2949247
IEEE ACCESS
Keywords
DocType
Volume
Massive MIMO,VBLAST,approximate message passing,AMPT,AMPG,5G
Journal
7
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Muhammad Haroon Siddiqui100.68
Kiran Khurshid200.68
Imran Rashid394.63
Adnan Ahmed Khan4287.09
Khubaib Ahmed Qureshi501.01