Research On Cross-Layer Wireless Resource Allocation Algorithm

With the rapid development of mobile communication system, the people’s view gradually turn to the developing and research of B3G/4G system work. MIMO and OFDM is one of the most key technologies in B3G/4G system. If MIMO and OFDM technology is used in the air physical interface layer, it can enhance the reliability, effectiveness and anti-jamming ability of the wireless link, and improve the efficiency of the system’s spectrum. In recent years, with the growing number of mobile users, people’s demand on the types of mobile services and service quality increases. How to manage and distribute the limited wireless resources becomes a crucial research issue in the research. Effective and reasonable resources allocation algorithm is the fundamental of wireless resource management. It can ensure users’satisfaction to different services’QoS and achieve the goals of reaching the maximization resource utilization rate and improving system performance.This thesis studied the existing real-time, non-real time and heterogeneous traffics resource scheduling algorithm, and proposed a layered resource allocation algorithm based on differentiating services for heterogeneous traffics in MIMO OFDM system which is called cross layer resources scheduler algorithm for heterogeneous traffics based on the QoS satisfaction criterion and services differentiating (CLRSA). CLRSA utilized cross layer design, a hierarchical scheduler for multiple traffics and presented a scheduling scheme to allocate resources. Groups of services of users are input to upper scheduler, and traffic-flow groups are output, then upper scheduler reasonably allocates resources to these groups according to the types of services.Finally, these traffic-flow groups are input to second scheduler and resources are allocated among users. Correspondingly, a cross layer resources scheduler algorithm for heterogeneous traffics based on the QoS satisfaction fairness criterion is introduced. It is a new fairness criterion based on cross-layer design.With the fairness criterion, resources are divided to users in each service group.This thesis further analyzed heterogeneous traffics resource allocation problems using mathematics, and proposed a weighted swarm intelligence cross-layer resource allocation algorithm with proportional fairness. In the MAC layer, the weighted proportional fairness scheduling provides different packets in users’ queues different weight, and sorts every user’s packets calculating users’weight by means of the weight, then set up the proportional constraints among users’ rates according to the ratio of users’ data to be passed. In the PHY layer, setting maximizing the system weighted capacity sum as optimization target, led swarm intelligence algorithm into the resource allocation.This thesis used MATLAB simulation software, simulated the proposed algorithm’s performance. Comparing with the existing resources allocation algorithm, CLRSA can reasonably allocation resources, achieve global optimization, not only improve system performance, but also achieve the user’s QoS satisfaction requirements and guarantee the fairness among users. The performance analysis of weighted swarm intelligence cross-layer resource allocation algorithm with proportional fairness demonstrate that the scheme can increase the total system rates on the basis of guaranteeing users’ fairness and meeting the service requirement.