Research On Resource Allocation Of Heterogeneous Services And Joint Optimization In Cognitive Radio Networks

Cognitive Radio (CR) has emerged as a key technology to realize dynam-ic spectrum access and solve the problem of spectrum scarcity, by sensing the spectrum environment. In CR networks, through the design of effective re-source allocation algorithm to further improve the spectral efficiency of the unlicensed networks, has become a research focus in academia. With the rapid development of user equipment, the CR networks need to provide heteroge-neous services with various Quality of Service (QoS). However, most of the existing studies only focus on how to improve the spectrum utilization in CR networks, while ignoring the provision of QoS for users. Moreover, the imper-fect detection and relay nodes in CR networks, making the optimization vari-ables become multi-dimensional. Traditional algorithms optimize the multi-dimensional variables independently, leading to a decline in the capacity of CR networks. Thus, it is necessary to study the heterogeneous services oriented re-source allocation and joint optimization algorithms to meet the QoS of different users and solve the complex optimization problem in CR networks.To achieve the objectives stated above, this dissertation, combining the Or-thogonal Frequency Division Multiplexing (OFDM) and relaying technology, first study the resource allocation schemes for two scenarios:heterogeneous services per user and one service per user but with different QoS. Then, the way of joint optimization in CR networks and cognitive relay network are s-tudied, solving the optimization problem with multiple variables. Main work and contributions of this dissertation are summarized in the following:Firstly, the optimal resource allocation for heterogeneous services per sec-ondary user (SU) in CR networks is studied. Based on utility theory, the opti- mal theoretical solutions of subcarrier assignment and sharing are derived for homogeneous best-effort services per user scenario. Moreover, delay sensitive (DS) service is labeled with different scheduling priority. Two algorithms, cor-responding to per port power constraint and total power constraint respectively, are proposed based on the derived theories to solve the problem of hetero-geneous services per user. The system-level simulation results show that the proposed algorithm outperforms traditional algorithm in terms of throughput and fairness criterion.Secondly, for the resource allocation problem of different user requesting different QoS services, a cross layer optimization problem is firstly formulated to maximize throughput of Delay Tolerant (DT) service in physical layer, and meet the delay requirement of DS service in the MAC layer. Then, with the queue theory, the delay requirements of DS service are transformed into con-stant rate requirements. In the end, based on the convex theory, a dual decom-position method is proposed. Simulation results show that the system perfor-mance achieved by using the proposed algorithm outperforms that of traditional algorithms, such as random subcarrier assignment and round robin subcarrier assignment algorithms.Thirdly, considering the imperfection of spectrum sensing of CR network-s, the joint optimization of detection threshold and resource allocation with the goal of maximizing the total downlink capacity of SUs in CR networks is stud-ied. The optimization problem is formulated considering three sets of variables, i.e., detection threshold, sub-carriers and power, with constraints on the Prima-ry Users’(PUs’) rate loss and the power budget of the CR base station. Two schemes, referred to as offline and online algorithms respectively, are proposed to solve the optimization problem. While the offline algorithm finds the global optimal solution with high complexity, the online algorithm provides a close-to-optimal solution with much lower complexity and real-time capability. The performance of the proposed schemes is evaluated by extensive simulations and compared with the conventional static threshold selection algorithm. Fourthly, the problem of resource allocation in CR relay system is con-sidered. The objective is to maximize the system capacity while taking into account the power constraints of relay node and CR base station, the interfer-ence to the PUs constraint as well as the fairness constraint among SUs. The optimization problem is formulated as a mixed integer programming problem under constraints, which is not convex. An efficient but low complexity algo-rithm is proposed by dividing the problem into two stages. The effectiveness of the proposed algorithm in both Amplify-and-Forward (AF) and Decode-and-Forward (DF) CR relay systems are verified through extensive numerical results.Finally, conclusions and future work are summarized in the end of this dissertation.