To meet the increasing demand of high-data-rate services of high-speed railway (HSR) passengers, cloud radio access network (C-RAN) is proposed. This paper investigates the tradeoff between energy efficiency (EE) performance and capacity in C-RAN of HSR. Considering that the train location can be predicted, we propose a predictable path loss based time domain power allocation method (PPTPA) to improve EE performance of HSR communication system. First, we consider that the communication system of HSR only bears the passenger information services (PISs). The energy-efficient power allocation problem with delay constraint is studied. The formulated problem is nonconvex. To deal with it, an equivalent convex problem is reformulated. Based on PPTPA, we propose an iterative algorithm to improve the EE performance. Second, we consider that the PISs and the train control services (TCSs) are all bore. A capacity optimization problem with joint EE and services transmission delay constraints is formulated. Based on PPTPA, we propose a hybrid power allocation scheme to improve the capacity of the system. Finally, we analyze the effect of small-scale fading on EE performance. The effectiveness of the proposed power allocation algorithm is validated by HSR channel measurement trace based emulation results and extensive simulation results.
Performance Analysis and Power Allocation for NOMA-assisted Cloud Radio Access Network
