Optimization Of Cooperative Spectrum Sensing And Resource Allocation Based On Energy Efficiency In Cognitive Radio Network

In a society of information nowadays, informationization affects the life of people in every possible field. Fast development of wireless communication technology provides more possibilities about information, and also brings new problems about the spectrum resource. As a non-renewable resource, spectrum becomes increasingly scarce. Cognitive radio, as a promising technology to improve the spectral efficiency, is proposed. By improving the utilization of license spectrum band, it can solve the shortage of spectrum.This thesis studies the optimization problems of cooperative spectrum sensing in cognitive radio on energy efficiency. Joint design of various network parameters can improve the performance of system’s energy efficiency and performance. Optimization of M2 M communication network is also discussed. The main contents of this thesis can be summarized as follows:1. The joint optimizing problems in cognitive radio with single channel and multiple secondary users based on energy efficiency are studied. Firstly, an optimization problem about the network energy efficiency with weighting factor is proposed. Different length of sensing time and number of sensing nodes affects the energy efficiency. This thesis discusses the relationship between sensing time and energy efficiency with fixed number of sensing nodes and the relationship between sensing nodes and energy efficiency with fixed sensing time. By analyzing the relationships, a viable algorithm is advised. Secondly, special situations of weighting factors are discussed. Through the numerical results, we can find that with the fusion of “OR”, “AND” and “K out of N”, the results fits our analysis very well. The performance of energy efficiency can be obviously improved by adjusting the length of sensing time and number of sensing nodes.2. The optimizing problem in cognitive radio with multiple channels and multiple secondary users based on energy efficiency is studied. An optimization problem aimed to maximum the energy efficiency of network with parameters of sensing time and sensing threshold is proposed. The existence of optimal number in this problem is proofed when we fix one parameters. And a feasible algorithm is proposed to achieve the optimal point of energy efficiency. Then, the complex situations are discussed. The available probability of channel for secondary users is not always the same. In this condition, possible modified algorithm is proposed. Numerical results show us that we can improve the performance of energy efficiency by adjusting the optimization parameters.3. The optimizing problem in cognitive radio with single multiple channels and multiple secondary users based on energy efficiency is studied. Firstly, an optimization problem on energy efficiency with parameters of sensing time and sensing threshold is proposed. After analyzing the relationships between energy efficiency when one of the parameters is fixed, the improvement of performance by clustering channels is discussed. And an algorithm with clustering channels to improve the energy efficiency is proposed. Then we study the effects of clustering sensing nodes into small clusters. By analyzing the performance of energy efficiency, an algorithm of clustering sensing nodes to improve the performance of energy efficiency is proposed. Numerical results show us that suitable clustering designs can improve the performance of network.4. Energy efficiency optimization of M2 M communication network is studied. In the single cellular mode, it exist a lot of data transmissions between M2 M devices. This thesis proposes an optimization model of energy efficiency based on clustering. By assigning devices into clusters, we can improve the energy efficiency of network.