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Article

Group Sparse Precoding for Cloud-RAN with Multiple User Antennas

Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, College of Electronic Information and Optical Engineering, Nankai University, 38 Tongyan Road, Tianjin 300350, China
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Entropy 2018, 20(2), 144; https://doi.org/10.3390/e20020144
Received: 6 November 2017 / Revised: 2 February 2018 / Accepted: 19 February 2018 / Published: 23 February 2018
(This article belongs to the Section Information Theory, Probability and Statistics)
Cloud radio access network (C-RAN) has become a promising network architecture to support the massive data traffic in the next generation cellular networks. In a C-RAN, a massive number of low-cost remote antenna ports (RAPs) are connected to a single baseband unit (BBU) pool via high-speed low-latency fronthaul links, which enables efficient resource allocation and interference management. As the RAPs are geographically distributed, group sparse beamforming schemes attract extensive studies, where a subset of RAPs is assigned to be active and a high spectral efficiency can be achieved. However, most studies assume that each user is equipped with a single antenna. How to design the group sparse precoder for the multiple antenna users remains little understood, as it requires the joint optimization of the mutual coupling transmit and receive beamformers. This paper formulates an optimal joint RAP selection and precoding design problem in a C-RAN with multiple antennas at each user. Specifically, we assume a fixed transmit power constraint for each RAP, and investigate the optimal tradeoff between the sum rate and the number of active RAPs. Motivated by the compressive sensing theory, this paper formulates the group sparse precoding problem by inducing the 0 -norm as a penalty and then uses the reweighted 1 heuristic to find a solution. By adopting the idea of block diagonalization precoding, the problem can be formulated as a convex optimization, and an efficient algorithm is proposed based on its Lagrangian dual. Simulation results verify that our proposed algorithm can achieve almost the same sum rate as that obtained from an exhaustive search. View Full-Text
Keywords: cloud radio access network; sparse beamforming; block diagonalization; group-sparsity; antenna selection cloud radio access network; sparse beamforming; block diagonalization; group-sparsity; antenna selection
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MDPI and ACS Style

Liu, Z.; Zhao, Y.; Wu, H.; Ding, S. Group Sparse Precoding for Cloud-RAN with Multiple User Antennas. Entropy 2018, 20, 144. https://doi.org/10.3390/e20020144

AMA Style

Liu Z, Zhao Y, Wu H, Ding S. Group Sparse Precoding for Cloud-RAN with Multiple User Antennas. Entropy. 2018; 20(2):144. https://doi.org/10.3390/e20020144

Chicago/Turabian Style

Liu, Zhiyang, Yingxin Zhao, Hong Wu, and Shuxue Ding. 2018. "Group Sparse Precoding for Cloud-RAN with Multiple User Antennas" Entropy 20, no. 2: 144. https://doi.org/10.3390/e20020144

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