5G and Beyond: On the Significance of Wireless Channel Estimation

Wireless channel is one of the most important components of any wireless communication system. Accurate wireless channel knowledge at the transmitter ensures that correct amount of data is being transmitted to the intended users/devices in the system. This wireless channel knowledge, known as Channel State Information (CSI), is acquired at the transmitter through the feedback sent by the users/devices. The transmitter, then, uses this CSI to adjust the transmission, both in terms of data rate and direction, to the intended users/devices. In this paper, we investigated why accurate Wireless Channel Estimation (WCE) is even more critical for contemporary wireless technologies such as 5G and beyond? We first modelled the wireless channel between a transmitter and multiple receivers having multiple antennas using independent and identically distributed Gaussian random processes and calculated channel strengths and angle of transmission using ground as our azimuth reference. We then used a Simple Random Estimation (SRE) technique at the transmitter to estimate the same wireless channel. Our numerical results show that a small perturbation in WCE leads to significant deviations in channel strengths and directions. These estimation errors at the transmitter result in data loss as well as poor Quality of Service (QoS) to the users/devices. This study leads us to develop innovative wireless channel estimation techniques using Machine Learning (ML) at the transmitter that will reduce the amount of CSI feedback and improves the over all transmission in terms of both channel strengths and direction of transmission in our future work. Comment: given the purpose of this paper is to discuss channel estimation but in this paper we are not using specific baseline channel estimation techniques. Our main purpose is to show the channel error using SRE and future need to minimise this channel error.