面向C-RAN的群稀疏线性预编码

doi:10.3969/j.issn.1001-506X.2020.01.29

Abstract

Abstract:

Cloud radio access network (C-RAN) is a network architecture that centralized signal processing. C-RAN can dynamically adjust the user communication rate by dynamically selecting remote radio heads (RRHs). Rate performance is a key part of user quality of service (QoS). As the number of RRHs increases, the rate performance can be improved at the expense of higher energy consumption. Therefore, the tradeoff between rate performance and power consumption is focused. In this paper, an optimization algorithm is proposed. In this algorithm, the contradiction between the rate maximization and the number of RRHs minimum is coordinated through the trade-off coefficient. To solve the non-convex problem, the re-weighted $\ell_1$ norm to approximate the $\ell_0$ norm is used, and the weighted minimum mean square error (WMMSE) method is used to convert the non-convex sum rate express to a convex function. Finally, a modified subgradient method is used to update the precoding matrix. The simulation results show that the method reduces the complexity and achieves near-optimal performance.

Key words: cloud radio access network (C-RAN), quality of service (QoS), weighted minimum mean square error (WMMSE), precoding

CLC Number:

TN929.53

Guanxiang DING, Zhiyang LIU, Hong WU, Yingxin ZHAO. Group sparse linear precoding for C-RAN[J]. Systems Engineering and Electronics, 2020, 42(1): 217-222.

Figures/Tables 6

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References 28

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Group sparse linear precoding for C-RAN

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