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.
Highlights
Nowadays in wireless communication systems, massive multiple-input multiple-output (MIMO) has become the subject of an extensive research due to its potential to support higher data rate as compared to their counterpart single-input single-output (SISO) [1]–[3]
The approximate message passing (AMP) algorithm has become an attractive area for research especially in massive MIMO systems due to its inherent reduced complexity
Comparison of bit error rate (BER) performances of Hybrid n-Bit Heuristic AssistedVBLAST (HHAV), AMP (4-iteration), AMP(G), AMP(T), and Vertical Bell-Labs Layered Space Time (VBLAST) schemes in terms of number of users and number of receiving antennas is shown in table2
Summary
Nowadays in wireless communication systems, massive MIMO has become the subject of an extensive research due to its potential to support higher data rate as compared to their counterpart single-input single-output (SISO) [1]–[3]. In massive-MIMO, detection is a complicated process It requires an extensive search over the space in order to find the closest received symbols in terms of euclidean distances for an optimal solution. MMSE equalizer works like ZF when SNR has higher value, whereas MMSE considers noise and signal variance when the SNR has lower values to avoid noise amplification Both ZF and MMSE (linear detectors) are quite simple to implement as compared to ML detection scheme with inferior BER performances. The rest of the paper is structured as follows: In Section-II, system model is presented and the performances of the existing robust detection algorithm for massive MIMO decoder is analyzed. Section-III presents the simulation results and compares the BER performances of the existing detection algorithm with proposed scheme. Lim+1 stands for ith element of a vector at mth +1 iteration. d (.), and represent the damping function and damping factor respectively
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
