Energy-Efficient Spectrum Selection and Resource Allocation in Downlink Cognitive Femtocell Networks

Abstract

The adoption of femtocell networks is considered as a promising solution to resolve the poor received signal strength problem experienced by the user equipment (UE) located in the coverage hole or in indoor environment. The architecture of femtocell networks, which adopt cognitive radio (CR), centralized controlled by femtocell gateway (F-GW) is further proposed to enhance the system performance by accessing more licensed spectrums. However, more deployed femtocells lead to additional energy consumption and it has become a crucial challenge for mobile operators. In this paper, the spectrum selection with limited number of antennas (SSLNA) is proposed to derive the target spectrum with consideration of hardware limitation of both femtocell access points (FAPs) and UEs. Based on the spectrum selection policies, the energy-efficient joint resource block (RB) and power allocation (EJRPA) scheme is proposed to improve the system energy efficiency. To avoid large amount of communicational load and complex computation for both F-GW and FAPs, the energy efficiency optimization problem is transformed into a two-layer problem solved respectively by F-GW and FAPs when the EJRPA is adopted. Simulation results show that better system energy efficiency can be achieved by adopting the proposed schemes.