Radio Resource Allocation With High Definition Video Transmission

With the development of wireless communication systems, radio resource allocation plays animportant role in guaranteeing the QoS of users. However, the effective radio resource allocationtechniques not only rely on effective resource allocation algorithm, it also puts forward higherrequirements with channel state information based limited feedback scheme. Since imperfect channelestimation, quantization or transmission errors in feedback channels have great effect on obtaining theaccurate channel state information quickly and radio resources allocation results. Therefore,considering the different requirements to resource allocation of wireless communication systems, thisthesis investigates limited feedback schemes. Then this thesis focuses on the radio resource allocationwith high definition video transmission in the OFDM based system. The main contents can besummarized as follows:Firstly, the thesis proposes the dynamic region based limited feedback scheme for efficient powerallocation in OFDM systems. The proposed limited feedback scheme is compared with the ordermapping based limited feedback scheme under the same environment from three aspects. They are thefeedback information amount, the accuracy and the spectral efficiency, respectively. The numericalresults show that the proposed limited feedback scheme can improve both the accuracy of feedbackchannel gain information and the spectral efficiency with less feedback information amount. It is veryimportant to adaptive power allocation.Secondly, according to the subcarrier chunk based resource allocation scheme, this thesis focuseson the radio resource allocation problem to jointly optimize the subcarrier chunk assignment andpower allocation in multi-relay OFDMA systems. The optimization formulation is to maximize thetotal system throughput with transmission requirement constraints and is considered as a mixedinteger optimization problem. Then, a dual minimization based joint resource allocation algorithm isproposed. The proposed dual minimization based algorithm is shown to be optimal. The simulationresults validate the performance gains offered by the proposed joint resource allocation algorithm.Thirdly, considering the practical need, according to the joint resource allocation algorithm, thisthesis also develops a low complexity but near-optimal resource allocation algorithm. It hasadvantages: low computational complexity, high speed of calculation and the results are near to theoptimal results.