Abstract
Objective: A massive Multiple Input and Multiple Output (MIMO) receiver utilizes the proposed detection algorithm to reduce the complexity. Methods: The existing research work namely Noise and Relevancy aware Low Complexity Detection (NRLCD) algorithm for massive MIMO receiver utilizes normalized cross correlation based pruning strategy to viably evacuate uncorrelated signals. However, the existing research work still has more complexity with increasingly number of iterations to find more relevant signal vector. In this research paper, it is proposed to investigate execution of massive MIMO system utilizing Continuous Phase Modulation (CPM) modulation which is used to carry out signal modulation. Then, Hybrid Particle Swarm Optimization-and-Branch-and-Bound (Hybrid PSO-BB) algorithm is proposed for low complexity detection. Findings: CPM demonstrated to give superior performance over Quadrature Amplitude Modulation (QAM) technique with the presence of phase noises. Hybrid PSO-BB is anticipated; in which the best attainable solution were found and renewed using PSO. The performance assessment of the proposed research work and existing methods is done under Adaptive Additive Gaussian Channel (AWGN) using MATLAB Communication tool box. Improvements: From the simulation results, it is inferred that the Hybrid PSO-BB algorithm is superior to the existing methods in-terms of Bit Error Rate (BER) performance and complexity. Keywords: Bit Error Rate (BER), Continuous Phase Modulation (CPM), Low Complexity, Massive Multiple Input and Multiple Output (MIMO), Particle Swarm Optimization (PSO)
Highlights
Multiple Input and Multiple Output (MIMO) technology improves the capacity of wireless networks and the reliability of data transmission through wireless media networks[1,2,3]
PRUNing based Maximum Likelihood Detection using Low Complexity Detection Algorithm (PRUN-MLD -LCDA) is used to find the more relevant signal vectors based on the cross correlation based pruning technique[7]
The Hybrid PSO-BB detection algorithm is proposed for massive MIMO system to detect the received signals with low complexity
Summary
Multiple Input and Multiple Output (MIMO) technology improves the capacity of wireless networks and the reliability of data transmission through wireless media networks[1,2,3]. Massive MIMO uses large antennas at both ends and provides better performance without requiring additional bandwidth or traditional power[5]. CPM modulation has constant envelope signals with good power and spectral efficiency[8] It is having these favourable features, but still it is limited to have low complexity[9]. The Laurent decomposition method reduces the number of states required to describe the CPM signal. This method is commonly applied in the literatures to design low complexity MIMO receiver and used to derive the data aided frequency detectors[13,14,15].
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