LATENCY REDUCTION IN 5G COMMUNICATION: A CHANNEL ESTIMATION ALGORITHM

Abstract

The evolution of wireless communication illustrates tremendous expansion in terms of data rate, latency, coverage, and other network performances. From the humble beginning of the first generation of communication, which had about 10 kbps, it has progressed to the fifth generation (5G) of communication that can easily achieve 10 Gbps of data rate. Several cutting-edge technologies lie behind the 5G wireless communication to improve the connection quality of the network. For instance, mmWave uses high frequencies to increase bandwidth, while beamforming focuses the spread signal in a single direction. Additionally, Massive MIMO, which stands for Multiple Input Multiple Output, enhances energy and spectral efficiency. However, using all these outstanding technologies leads to signal degradation or reception issues despite these impressive advancements in the wireless communication field. To address these challenges, proper channel estimation is required to obtain the right signal. Numerous channel estimation techniques are offered by scientists. In this thesis work, different channel estimation techniques and types are investigated, and channel estimation algorithms are represented. Additionally, the impact of channel estimation parameters to the latency of the communication network is explored. The paper presents a broad comparison of various channel estimation methods. Also, the performance of several pilot-based channel estimation methods in terms of accuracy and time execution is explored. The outcomes of the thesis contribute to the development of channel estimation algorithms focused on a reduction of latency in 5G communication.