Research On Key Technologies Of Resource Allocation In Cognitive Radio Networks

With the great improvements of the wireless communication techniques, peoples need higher data transmitting rates, so the scarcity of wireless spectrum resource restricts the sustainable development of wireless communications. Cognitive Radio (CR) technology is a promising technology for wireless communication that is regarded as an effective method to solve the problem of the shortage of wireless spectrum. Secondary Users implement CR technology to sense outside radio surroundings, search for available spectrum resources, access spectrum holes and allocate resources dynamically. Hence, spectrum efficiency is improved and system capacity is increased.This dissertation combines CR with Orthogonal Frequency Division Multiplexing (OFDM), and improves the utilization of spectrum resource effectively. It increases the efficiency of CR Secondary Users to access the spectrum of authorized users. An important issue of providing different Secondary Users with diverse quality-of-service (QoS) requirements in wireless network is how to optimize systematic scheduling by utilizing the available network resource intelligently. At the same time, it also requires how to meet QoS requirements for each communication services. In this dissertation, it totally investigates these problems in Cognitive OFDM system.Firstly, this dissertation introduces the background and framework of CR spectrum allocation strategies, with some allocation models presented. It emphasize on the interference temperature model and the adaptive allocation model in cognitive OFDM, which provides as the theoretical criteria for our proposed algorithms.Secondly, it studies the single user resource allocation schemes in cognitive OFDM networks based on RA and MA criteria. Single user resource allocation do not need sub-carrier allocation, it only involves power and bit allocation. Based on the traditional power and bit allocation algorithms, an improved power and bit allocation algorithm is proposed in Cognitive OFDM. Simulation results demonstrate that the improved algorithm could achieve the optimal solution and reduce the computational complexity.Thirdly, multi-user resource allocation strategies are investigated in cognitive OFDM network based on RA and MA criteria respectively. The problem of resource allocation in multi-user scenario becomes complicated. In order to achieve the optimal solution, the joint optimal algorithm for sub-carriers and power/bits allocation is implemented. Based on traditional optimum algorithm, the improved joint resource allocation algorithm is proposed. Simulation results indicate that the improved joint allocation algorithm could achieve better performance and reduce the computational complexity obviously.Finally, dissertation introduces a novel multimedia heterogeneous cognitive OFDM network. Secondary Users with diverse QoS requirements are divided into DS (Delay-sensitive) users and DT (Delay-tolerant) users. By combine RA and MA criteria, this dissertation constructs the heterogeneous resource allocation mathematical model. Based on the proposed model, the improved resource allocation algorithm is proposed. Simulation results show that, compared with traditional FSA-WF and FSAP-WF algorithms, the improved joint resource allocation algorithm could achieve better performance in channel capacity and system outage probability in cognitive OFDM network.