Low Complexity Hybrid PSO-BB Detection Algorithm for Massive MIMO System M. Kasiselvanathan* and N. Sathish Kumar Department of ECE, Sri Ramakrishna Engineering College, Vattamalaipalayam - 641022, Coimbatore, Tamil Nadu, India; drkasiselvanathanvkm@gmail.com, nsk20022002@gmail.com 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. 1. Introduction Multiple Input and Multiple Output (MIMO) technology improves the capacity of wireless networks and the reliability of data transmission through wireless media networks 1 - 3 . Single-Input Single-Output (SISO) technology uses the only one transmitter and one receiver to support limited wireless services of upper information rates. To achieve high transmission rate, SISO technology must have large bandwidth and signal to noise ratio 4 . Massive MIMO uses large antennas at both ends and provides better performance without requiring additional bandwidth or traditional power 5 . A Random Restart RTS (R3TS) algorithm was proposed to attain the improved BER performance when it is compared with the traditional RTS algorithm using higher-order QAM modulation 6 . PRUNing based Maximum Likelihood Detection using Low Complexity Detection Algorithm (PRUN-MLD -LCDA) is used to fnd the more relevant signal vectors based on the cross correlation based pruning technique 7 . CPM modulation has constant envelope signals with good power and spectral efciency 8 . It is having these favourable features, but still it is limited to have low complexity 9 . To reduce the complexity in the received signals, some key features are performed to introduce the CPM signals with Rimoldi decomposition and Walsh decomposition 10, 11 . In both Rimoldi decomposition and Walsh decomposition, number components have been reduced to represent the signal space and it these decomposition methods do not reduce the number of states. Te Laurent decomposition is introduced to allow decomposing the CPM signal as a superposition of *Author for correspondence Indian Journal of Science and Technology, Vol 12(20), DOI: 10.17485/ijst/2019/v12i20/143826, May 2019 ISSN (Print) : 0974-6846 ISSN (Online) : 0974-5645 Keywords: Bit Error Rate (BER), Continuous Phase Modulation (CPM), Low Complexity, Massive Multiple Input and Multiple Output (MIMO), Particle Swarm Optimization (PSO)