Study On Resource Allocation Algorithm In Wireless Network Based On OFDMA

With the increasing needsfor wireless service, especially multimedia service, how toefficiently make use of the limited wireless resources has become a great challenge in thedevelopment of wireless communication technology. Accordingly, OFDMA(OrthogonalFrequency Division Multiple Access) becomes a mainstream technology for theBroadband Wireless Access with its excellent performance of anti-fading and highspectrum efficiency. However, in the OFDMA-based wireless networks, the problems ofthe unfair spectrum allocation and the large difference in QoS (quality of service) stillexist. Therefore, anefficient resources allocation strategy can further improve thespectrum efficiency and increase total utilitiesor system throughput.This thesis aims to maximize the system utility or capacity in different types ofOFDMA-based wireless networks. Considering the fairness of resource allocation as wellas different QoS requirement among users, two feasible and efficient subcarrier andpower allocation models are proposed byusing Lagrange duality theory and IWD(intelligent water dropalgorithm) separately. The contributions of this thesis are listed asfollows:①This thesis proposes a multiuser-based distributed resource allocation frameworkfor the cognition radio(CR) ad hoc networks by using OFDMA modulation. The thesisjointly considers the constraints of QoS, maximum power and minimum rates in thenetwork to maximize the system capacity, and obtains optimal subcarrier and powerallocation. In the model, Lagrange duality theory is used to decompose the existingproblems into simpler sub-problems. The probability that a subcarrier is occupied and theminimum number of subcarrier occupation are introduced to ensure the fairness ofresource allocation. Incremental subgradient method is used to guarantee the fastconvergence of our algorithm. By the extensive experiment, the thesis compares networkperformance between constraints with fairness and without fairness, andverifies thenecessity for fairness resource allocation. What’s more, our simulationresults confirm thatthe proposed algorithm outperforms the existing algorithms in terms of throughput,spectrum efficiency and the fairness of resource allocation.②This thesis takes into account of the difference of channel conditions among usersand the fairness of subcarrier allocation, and proposesa joint subcarrier and powerallocation model for OFDMA based uplinks in cellular networks. In this model, subcarrier allocation is divided into two phases: In the first phase, subcarrier allocationensures that each user can obtain certain number of subcarrier while in the second phasethe total utility is further improved. Furthermore, by considering the limited powers andquality of service of users, the thesis obtains the optimal power allocation based oniterative water-filling algorithm. In particular, our proposed algorithm is based on thelatest swarm intelligent algorithm—intelligent water drop algorithm, which eliminates theimposed restriction on that the utility function must be concave. Simulation results showthat our algorithm outperforms existing resource allocation in terms of convergence, totalutilities and fairness of resource allocation.