Research On Dynamic Resources Allocation Of Multi-user CR-OFDM System

With the growth of wireless communication requirement, the spectrum resource scarcity problem is getting more and more serious. So the Cognitive Radio is proposed to solve above problems. And increasing studies focus on the CR technologies for its high frequency utilization efficiency and good performance. Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier transmission technology, which can allocate subcarrier flexiblely. This dissertation integrates the two techniques and focuses on the topics as follows.This dissertation first introduces the concept of Cognitive Radio technology and its development, and then introduces the research background of the Cognitive Radio system based on OFDM.Secondly, this dissertation introduces the basic principle of OFDM as well as the resources allocation algorithm of OFDM system. Based on this, we put forward the framework of CR-OFDM system, and show its advantages.Thridly, combined with the classical 0-1 model and Interference Temperature model, we devise a new type of Dynamic resource allocation model which is applicable for CR-OFDM system--OFDM sub-carrier limited model.Fourly, we study the resource allocation of variable rate multi-user in CR-OFDM system. We propose the optimal algorithm which can get the maximal capacity of the system, the subprime algorithm which take the principle of proportion fairness among the cognitive users and its improved algorithm.We also give the solution of each algorithm.Meanwhile, by the way of simulation method, we analyze the three algorithms on the system capacity, the user fairness and algorithm complexity.At last, the fixed rate cognitive users are introduced to the CR-OFDM system, the issue of resources allocation of multi-user in multi-rate is also proposed.A theorem point that the way to gain maximal capacityis that allocating resources to the fixed rate cognitive users first, and then giving the rest of the resources to the variable rate users.Based on this, we introduce the two-step algorithm and the improved algorithm, then give the simulation which shows the performance of each algorithm.