Design of Intelligent Transmitter Receiver Integrated Unit and Channel Estimation Using Deep Learning Networks for Wireless Communication

Abstract

Contemporary wireless communication channels are overcrowded with newlineexcessive traffic and necessitate a substantial quantity of bandwidth. This scarcity of newlinebandwidth is a result of the rapid expansion of 4G/5G communication services like newlinevideo conference applications, Over-The-Top (OTT) media streaming services, video newlinegaming services, and so on. These services demand wireless communication links newlinewith a high level of reliability. However, the wireless channels are noisy, distortionprone, and affected by adverse dynamic environmental influences. Additionally, these newlinechannels are subjected to frequency shift, phase distortion, multipath fading, newlineinterchannel interference, and nonlinear attenuation. In this scenario, Channel newlineEstimation (CE) and providing matching countermeasures are inevitable requirements newlinefor the reliable and efficient performance of modern wireless communication systems. newlineThe first contribution to the proposed work is A Review of Wireless Channel newlineEstimation Techniques: Challenges and Solutions . This comprehensive review newlinecovers both the conventional-based method and Deep Learning based methods. The newlineconventional-based method are reviewed under three sub-groups, namely, PilotAssisted CE, Blind CE, and Decision Directed CE (DDCE). In the iterative versions newline