论文部分内容阅读
The cloud radio access network(C-RAN) promises significant gain to the data rate over the LTEadvanced by transferring the burdensome baseband signal processing from the remote radio heads(RRHs) to the baseband unit via the front-haul. However, scalable improvement of the overall throughput may not be maintained due to limited front-haul capacity. In this paper, we study the throughput maximization problem by selecting the active RRHs. In particular, we develop an optimum algorithm which selects a subset of active RRHs that maximize the system throughput under the front-haul constraint. In addition, the asymptotically optimum number of RRHs is derived in closed-form for low and high signal-to-noise ratio(SNR) regimes. It is demonstrated that the proposed RRH selection scheme outperforms any other existing schemes with substantial gain of achievable throughput for any given number of RRHs and any predetermined front-haul capacity constraints.
The cloud radio access network (C-RAN) promises significant gain to the data rate over the LTE advanced by transferring the burdensome baseband signal processing from the remote radio heads (RRHs) to the baseband unit via the front-haul. However, scalable improvement of the overall throughput may not be due due to limited front-haul capacity. In this paper, we study the throughput maximization problem by selecting the active RRHs. In particular, we develop an optimum algorithm which selects a subset of active RRHs that maximize the system throughput is the front-haul constraint. In addition, the asymptotically optimum number of RRHs is derived in a closed-form for low and high signal-to-noise ratio (SNR) regimes. It is described that the proposed RRH selection scheme outperforms any other existing schemes with substantial gain of achievable throughput for any given number of RRHs and any predetermined front-haul capacity constraints.