Energy-Efficient Spectrum Selection and Resource Allocation under Different System Topologies in Cognitive Small Cell Networks

• Main Authors: Chen, Jun-Quan, 陳俊全
• Other Authors: Feng, Kai-Ten
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/00216543299680899936

碩士 === 國立交通大學 === 電信工程研究所 === 104 === The adoption of small cell 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 small cell networks, which adopt cognitive radio (CR), centralized controlled by small cell gateway (SC-GW) is further proposed to enhance the system performance by accessing more licensed spectrums. In this thesis, we introduce four types of system topology, and then probe into spectrum selection and resource allocation policies based on each of them. With consideration of hardware limitation of both small cell access points (SAPs) and UEs, a sound spectrum selection mechanism is indispensable. Therefore, the spectrum selection with limited number of antennas (SSLNA), which is applied to most system topologies, is proposed to derive the target spectrum. According to spectrum selection policies, energy-efficient joint resource block (RB) and power allocation scheme (EJRP) with perfect information feedback (EJRP-P), EJRP with imperfect information feedback (EJRP-I), and EJRP with no information feedback (EJRP-N) are proposed to improve the system energy efficiency. To avoid large amount of communicational load and complex computation for both SC-GW and SAPs, the energy efficient optimization problem is transformed into a two-layer problem solved respectively by SC-GW and SAPs when EJRP-P or EJRP-I is adopted. Furthermore, energy-efficient joint spectrum selection and resource allocation (EJSR), which is applied to centralized system, perform better than others because SC-GW collects all information and jointly solves spectrum selection and resource allocation policies.