A Thesis Submitted in Partial Fulfillment of the Requirement for the Degree of Master of Science in Digital Systems

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Bahari, Mohammad Hossein | 2017

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 50732 (05)
University: Sharif University of Technology
Department: Electrical Engineering
Advisor(s): Shabany, Mahdi
Abstract:
Massive-MIMO and C-RAN are the two technologies which will be among most important parts of fifth generation (5G) stsrems. They will find widespread uses in future years. However, data transfer rate between these two technologies is a challenging problem. Also channel estimation is crucial in massive-MIMO systems. In this research, the problem of estimating the channel and the problems with the data transfer rate between these two technologies are investigated. We propose using 1-bit quantizers to solve the rate problem and also an algorithm with perfect performance in aspect of error rate is proposed. The mentioned algorithm is implemented on GPUs, which are available at C-RANs and resulted in 200x enhanced execution time. Due to the low latency performance of the design, we claim that it is proper to be used in C-RANs
Keywords:
Implementation ; Cloud Radio Access Network ; Graphics Procssing Unit (GPU) ; Massive Multiple-Input Multiple-Output Systems ; Channel Estimation ; Joint Channel and Data Estimation

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