Scalable Uplink Signal Detection in C-RANs via Randomized Gaussian Message Passing

doi:10.1109/TWC.2017.2706680

	Scalable Uplink Signal Detection in C-RANs via Randomized Gaussian Message Passing
	Congmin Fan 1; Xiaojun Yuan2,3 ; Ying Jun Zhang 4
	2017-08-01
发表期刊	IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (IF:8.9[JCR-2023],8.6[5-Year])
ISSN	1558-2248
卷号	16 期号:8
发表状态	已发表
DOI	10.1109/TWC.2017.2706680
摘要	Cloud radio access network (C-RAN) is a promising architecture for unprecedented capacity enhancement in next-generation wireless networks thanks to the centralization and virtualization of base station processing. However, centralized signal processing in C-RANs involves high computational complexity that quickly becomes unaffordable when the network grows to a huge size. First, this paper endeavors to design a scalable uplink signal detection algorithm, in the sense that both the complexity per unit network area and the total computation time remain constant when the network size grows. To this end, we formulate the signal detection in C-RAN as an inference problem over a bipartite random geometric graph. By passing messages among neighboring nodes, message passing (a.k.a. belief propagation) provides an efficient way to solve the inference problem over a sparse graph. However, the traditional message-passing algorithm is not guaranteed to converge, because the corresponding bipartite random geometric graph is locally dense and contains many short loops. As a major contribution of this paper, we propose a randomized Gaussian message passing (RGMP) algorithm to improve the convergence. Instead of exchanging messages simultaneously or in a fixed order, we propose to exchange messages asynchronously in a random order. The proposed RGMP algorithm demonstrates significantly better convergence performance than conventional message passing. The randomness of the message updating schedule also simplifies the analysis, and allows the derivation of the convergence conditions for the RGMP algorithm. In addition, we generalize the RGMP algorithm to a blockwise RGMP (B-RGMP) algorithm, which allows parallel implementation. The average computation time of B-RGMP remains constant when the network size increases.
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收录类别	SCI ; EI
来源库	IEEE
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/4526
专题	信息科学与技术学院信息科学与技术学院_PI研究组_袁晓军组
作者单位	1.Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong 2.National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, China 3.School of Information Science and Technology, ShanghaiTech University, Shanghai, China 4.Institute of Network Coding (Shenzhen), Shenzhen Research Institute, The Chinese University of Hong Kong, Hong Kong
推荐引用方式 GB/T 7714	Congmin Fan,Xiaojun Yuan,Ying Jun Zhang. Scalable Uplink Signal Detection in C-RANs via Randomized Gaussian Message Passing[J]. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS,2017,16(8).
APA	Congmin Fan,Xiaojun Yuan,&Ying Jun Zhang.(2017).Scalable Uplink Signal Detection in C-RANs via Randomized Gaussian Message Passing.IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS,16(8).
MLA	Congmin Fan,et al."Scalable Uplink Signal Detection in C-RANs via Randomized Gaussian Message Passing".IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 16.8(2017).