Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.759872
Title: Cloud Radio Access Network in constrained fronthaul
Author: Lei, Rui
ISNI:       0000 0004 7431 8900
Awarding Body: University of York
Current Institution: University of York
Date of Award: 2017
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Abstract:
The Cloud Radio Access Network (C-RAN) has been proposed for the provision of advanced fourth and fifth generation wireless communication services. The C-RAN system have been shown to reduce costs, and can provide high spectral efficiency and energy efficiency. The fronthaul in such networks, defined as the transmission links between Remote Radio Units (RRUs) and a central Baseband Unit (BBU), usually has high fronthaul load and constrained capacity. In this thesis, we explore and investigate the basic C-RAN system structure, based on which we propose two developed C-RAN systems. With each system we evaluate the Bit Error Ratio (BER) performance and transmission efficiency in multiple scenarios, and give advanced solutions to reduce the fronthaul load. We also analyse the effect of quantization on BPSK and QPSK modulation schemes, with different detection methods. Error control in fronthaul transmission is considered as erroneous frames may be received at the BBU. Error Detection Coding and Error Correction Coding approaches can be applied to the fronthaul network. They may increase the fronthaul latency, but great improve the end-to-end BER performance. Source compression techniques such as Slepian-Wolf (SW) coding can compress two correlated sources separately and de-compress them jointly. Since each RRU serves many user terminals, and some of them may also be served by another neighbour RRU, which results similarly in correlation of the received data between two RRUs. In this thesis, we applied the SW code to the C-RAN system and evaluate the compression rate achieved in fronthaul networks.
Supervisor: Burr, Alister ; Cumanan, Kanapathippillai Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.759872  DOI: Not available
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