Hybrid PSO-GSA Algorithm for Channel Estimation in Massive MIMO System
Keywords:
CSI, Codebook Introduction, MIMO, Mm Wave, PrecodingAbstract
For advanced communication MILLIMETER wave (mmWave) is represented as a buoyant technology against wireless networks because of its prosperous frequency spectral resources in Multiple Input Multiple Output (MIMO). Nevertheless, the mmWave is diagnosed in MIMO remnants as a complex task that appears as the problems such as maximized propagation loss. Hence, this work introduces a novel optimization helped-out estimation technique to calculate the mm-wave channel parameters. On mm-wave massive MIMO system the performance of hybrid precoding, as well as channel estimation, is developed through using optimization procedure in codebook model principles. In reality, existing models are carried out the uniform distribution of azimuth angles in the codebook model, the wherein developed method estimates it as a single objective optimization issue without contravening characteristics of angle. To resolve the aforesaid optimization issue, the Hybrid Particle Swarm Optimization (PSO)- Gravitational Search Algorithm (GSA) technique is developed which hybridizes the idea of PSO and GSA method correspondingly. At last, the developed model performance is evaluated and examined with the conventional methods regarding the Channel State Information (CSI) and error metrics.
References
Rong DaiYang LiuXin Guo,"Channel estimation by reduced dimension decomposition for millimeter wave massive MIMO system",Physical Communication,17 November 2020.
ShalaviM. AtashbarM. Mohassel Feghhi,"Downlink channel estimation of FDD based massive MIMO using spatial partial-common sparsity modeling",Physical Communication,29 May 2020.
Zaid AlbatainehKhaled HayajnehAhmad Dagmseh,"Robust massive MIMO channel estimation for 5G networks using compressive sensing technique",AEU - International Journal of Electronics and Communications, 14 April 2020.
Kamran KalbasiS. Jamaloddin Golestani,"On the relaxed maximum-likelihood blind MIMO channel estimation for orthogonal space-time block codes",Signal Processing13 May 2020.
Jisheng DaiLei ZhouWeichao Xu,"Robust Bayesian learning approach for massive MIMO channel estimation",Signal Processing16 October 2019.
Xiantao ChengChao TangShaoqian Li,"Gaussian-categorical B,ayesian inference for massive MIMO downlink channel estimation",Signal Processing, 3 December 2019.
E. Ayach, S. Rajagopal, S. Abu-Surra, Z. Pi, and R. W. Heath Jr, "Spatially sparse precoding in millimeter wave MIMO systems", submitted to IEEE Transactions on Wireless Communications, arXiv preprint arXiv:1305.2460, 2013.
Rappaport, Y. Qiao, J. Tamir, J. Murdock, and E. Ben-Dor, "Cellular broadband millimeter wave propagation and angle of arrival for adaptive beam steering systems",in Radio and Wireless Symposium (RWS), Santa Clara, CA, pp. 151-154, January 2012.
Farid Tabee Miandoab, Behzad Mozaffari Tazehkand, "A user pairing method to improve the channel capacity for multiuser MIMO channels in downlink mode based on NOMA", Computer Communications, vol. 146, pp. 15-21, 15 October 2019.
Noel MM. A new gradient based particle swarm optimization algorithm for accurate computation of global minimum. Appl Soft Comput, vol. 12, no. 1, pp.353-9, 2012
Rashedi E, Nezamabadi-pour H, Saryazdi S. GSA: A gravitational search algorithm. Inf Sci, vol.179, no. 13, pp. 2232-48,2009.
Meghna Sangtani,"Hybrid Grey Wolf Optimization and Crow Search Algorithm for Power allocation in MIMO-NOMA systems",Journal of Networking and Communication Systems, vol. 3, no. 2, April 2020.
Heyan Zhang,"Secure Routing Protocol using Salp-Particle Swarm Optimization Algorithm",Journal of Networking and Communication Systems, vol 3, no 3, July 2020
Sivaram Rajeyyagari," Automatic Speaker Diarization using Deep LSTM in Audio Lecturing of e-Khool Platform,"Journal of Networking and Communication Systems,vol. 3, no. 4, October 2020
Amol V Dhumane,"Examining User Experience of eLearning Systems using EKhool Learners",Journal of Networking and Communication Systems, vol. 3, no. 4, October 2020
