INDRABHAN SUPDU BORSE
@ssvpsengg.ac.in
Associate Professor
SSVPS B.S.Deore College of Engineering Dhule
EDUCATION
M.E (Computer Engineering) Ph.D in Computer Engineeering)
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Engineering, Engineering, Computer Networks and Communications, Electrical and Electronic Engineering
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
Indrabhan Borse and Hitendra Patil
Conscientia Beam
Future generation cellular communications will require increased data rates and transmission using millimeter waves (MMWs), which are an emerging concept to meet this need. The MMW frequencies offer the potential for orders of magnitude capacity improvements. However, MMW network connections are more susceptible to blocking, and they suffer from rapid quality differential. The major limitation of offering multiconnectivity in MMWs is the necessity of tracking the direction of every link with its suitable timing and power. Beamforming enables wireless communications, even with higher frequency bands such as the MMW frequency band. The main purpose of this article is to develop an adaptive beamforming approach for 5G millimeter-wave networks. MMW communication efficiency is improved by enhancing the narrowband weights of adaptive beamforming. Here, the Shark Smell Optimization (SSO) and Bird Swarm Algorithm (BSA) are combined to improve the weight update approach of the new Salp-Bird Swarm Optimization (S-BSO) to achieve adaptiveness in beamforming. To demonstrate the effectiveness of the suggested Salp-Bird Swarm Optimization (S-BSO), an experimental comparison is carried out with the current models.
Indrabhan Borse and Hitendra D. Patil
IEEE
Millimeter wave (MMW) communication systems are emerging model for satisfying the increased necessity of high data rate of future generation cellular communications. The MMW frequencies give the prospective of increment in magnitude orders in terms of capacity. Though, MMW network links suffers from faster differentiation in quality and vulnerable to blockage. The main intent of this paper is to develop an adaptive beamforming technique of uplink communication in 5G millimeter wave cellular network. This paper optimizes the weight of narrowband in adaptive beamforming for enhancing the performance of MMW communication. Here, the adaptiveness in the beamforning is also accomplished by modifying the weight updating strategy of adaptive beamforming, which is performed by the hybrid meta-heuristic algorithm called Salp-Bird Swarm optimization (S-BSO) using Shark Smell optimization (SSO) and Bird Swarm Algorithm (BSA). The comparison is done over the existing models to prove the effective performance of the proposed adaptive beamforming.
RECENT SCHOLAR PUBLICATIONS
MOST CITED SCHOLAR PUBLICATIONS
Publications
1. A Novel Adaptive Beamforming Model for 5G Millimeter Wave Uplink Communication System
2. Holographic Beam forming for High Speed Network in 5G Communication
3. A Survey of 5G network using Millimeter wave