A cloud radio access network (Cloud-RAN) is a network architecture that holds
the promise of meeting the explosive growth of mobile data traffic. In this
architecture, all the baseband signal processing is shifted to a single
baseband unit (BBU) pool, which enables efficient resource allocation and
interference management. Meanwhile, conventional powerful base stations can be
replaced by low-cost low-power remote radio heads (RRHs), producing a green and
low-cost infrastructure. However, as all the RRHs need to be connected to the
BBU pool through optical transport links, the transport network power
consumption becomes significant. In this paper, we propose a new framework to
design a green Cloud-RAN, which is formulated as a joint RRH selection and
power minimization beamforming problem. To efficiently solve this problem, we
first propose a greedy selection algorithm, which is shown to provide near-
optimal performance. To further reduce the complexity, a novel group sparse
beamforming method is proposed by inducing the group-sparsity of beamformers
using the weighted $\ell_1/\ell_2$-norm minimization, where the group sparsity
pattern indicates those RRHs that can be switched off. Simulation results will
show that the proposed algorithms significantly reduce the network power
consumption and demonstrate the importance of considering the transport link
power consumption.

该研究提出了一种新的框架来设计绿色 Cloud-RAN，包括 RRH 选择和功率最小化波束成形问题，通过引入群组稀疏性和加权的 l1/l2 范数最小化来解决这个问题，结果显示，该算法显着降低了网络功耗并减少了传输链接的功耗。