Master'sOpen Access

Channel Estimation for Millimeter Wave Cellular Systems

2018
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Advisor: Ali Hakan (Co-Supervisor) Ulusoy

Abstract (EN)

The imagination of our future on wireless base networks is beyond science fiction. By emerging 2020, most of the wireless communication systems are going to suffer by the vast increase in the number of traffic in their network which leads to the lower data rate and higher latency. The current cellular network provides the stable connection for the demanding users, but in near future this technology will need a drastic improvement as it crosses its capabilities when users want more data. Therefore, 4G is going to be replaced by 5G. 5G technology, which is currently under development, is going to achieve a couple of objectives such as higher spectral efficiency, preferable battery life for handsets, higher capacity, improvement in the coverage area and lower latency. For this technology, to be realistic and operative as it is promised, some upcoming technologies such as massive MIMO, millimeter wave, beamforming and small cells are going to aid 5G system. Millimeter wave along with massive MIMO provides a high data rate within a large coverage area. Additionally, beamforming manages the massive transmission of data to all over the medium and directs the data to a specific user. In every wireless network, there are losses due to the propagation of medium, also known as channel. The channel is usually estimated by the signal processing module to assist the receiver in order to eliminate channel’s severe domination. For each generation of wireless cellular networks, a model by all the factors that have an impact on the signal will be presented as a fixed modeled and then channel is estimated and compared to the modeled version to have constancy. 5G network channel should be carefully estimated due to the use of high frequency band and the massive number of antennas. In this thesis, our focus is on estimation of channel through some training procedures. We try to pre-code the incoming input signal with some code words to reach as close as possible to the actual channel. Accordingly, BER, MSE and spectral efficiency will be illustrated to provide the channel performance and stability of the mm-wave systems. Keywords: 5G, Beamforming, Channel estimation, Precoding, Massive MIMO, Millimeter Wave and Small Cells.

Author

Dr. Sepehr Ashtari Nakhaei

How to Cite

Sepehr Ashtari Nakhaei (Master Thesis). Channel Estimation for Millimeter Wave Cellular Systems, 2018, Eastern Mediterranean University, Department of Electrical and Electronic Engineering.

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