Reference : Adaptive Cloud Radio Access Networks: Compression and Optimization
Scientific journals : Article
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/10993/31074
Adaptive Cloud Radio Access Networks: Compression and Optimization
English
Vu, Thang Xuan mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Nguyen, Hieu Duy [> >]
Quek, Tony Q.S. [> >]
Sun, Sumei [> >]
2017
IEEE Transactions on Signal Processing
IEEE
65
1
228-241
Yes
1053-587X
[en] Rayleigh fading ; optimization ; Cloud radio access networks ; adaptive compression
[en] Future mobile networks are facing with exponential data growth due to the proliferation of diverse mobile equipment and data-hungry applications. Among promising technology candidates to overcome this problem, cloud radio access network (CRAN) has received much attention. In this work, we investigate the design of fronthaul in C-RAN uplink by focusing on the compression and optimization in fronthaul uplinks based on the statistics of wireless fading channels. First, we derive the system block error rate (BLER) under Rayleigh fading channels. In particular, upper and lower bounds of the BLER union bound are obtained in closed-form. From these bounds, we gain insight in terms of diversity order and limits of the BLER. Next, we propose adaptive compression schemes to minimize the fronthaul transmission rate subject to a BLER constraint. Furthermore, a fronthaul rate allocation is proposed to minimize the system BLER. It is shown that the uniform rate allocation approaches the optimal scheme as the total fronthauls’ bandwidth increases. Lastly, numerical results are presented to demonstrate the effectiveness of our proposed optimizations.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/31074
10.1109/TSP.2016.2617826

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