Hybrid PSO-GSA Algorithm for Channel Estimation in Massive MIMO System


  • Manjunath Gangadhar Kallur Residence Universitaire Les Collinettes, France


CSI, Codebook Introduction, MIMO, Mm Wave, Precoding


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.


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How to Cite

Manjunath Gangadhar Kallur. (2021). Hybrid PSO-GSA Algorithm for Channel Estimation in Massive MIMO System. Journal of Networking and Communication Systems, 4(3). Retrieved from https://publisher.resbee.org/admin/index.php/jnacs/article/view/17