| Summary: | 博士 === 國立交通大學 === 電機與控制工程系所 === 97 === The next generation wireless communication systems are expected to provide high rate transmission in the applications of digital audio broadcast, digital video broadcast and wireless internet access but regardless to the users’ mobility and location. The major challenges we are confronted with include the harsh channel conditions, QoS (Quality of Services) requirements such as BER (Bit Error Rate) and users’ data rate request, scarce resources such as power and spectrum, and the knowledge of the most updated state of the mobile users or devices. Orthogonal frequency-division multiplexing (OFDM) technology is recently recognized as one of the leading candidates for supporting the next generation wireless communication systems due to its ability to combat inter-symbol-interference (ISI) over harsh channel conditions. This stimulates the development of both intelligent and efficient resource management algorithms to achieve efficient utilization of power and spectrum while providing QoS requirements in the multiuser OFDM communication system. Therefore in this dissertation, we will present two computationally efficient methods to solve the Adaptive Subcarrier Assignment and Bit Allocation (ASABA) problem of multiuser OFDM system using Ordinal Optimization (OO) approach.
Our first method consists of four OO stages to find a good enough solution to the ASABA problem. In the first three stages, we use surrogate models to select a subset of estimated good enough feasible solutions from the candidate solution set so as to reduce the search space of subcarrier assignment until l (=3) good enough subcarrier assignment patterns are obtained. Then in the fourth stage, we use the exact objective function to evaluate the l subcarrier assignment patterns, and the best one associated with the corresponding optimal bit allocation is the good enough solution that we seek. The four-stage OO approach ensures the quality of the obtained solution, however at the cost of solving a continuous version of the considered problem in the first stage. To resolve this computational complexity problem, we propose a hardware implementable Dual Projected Gradient (DPG) method to exploit deep submicron technology so as to obtain the optimal continuous solution extremely fast.
Due to the large dimension of the ASABA problem, implementing the first stage in hardware is almost impossible for area concern. Therefore in the first stage of our second method, we develop an approximate objective function to evaluate the performance of a subcarrier assignment pattern and use a genetic algorithm to efficiently search through the huge solution space to find I (=200) good solutions.
Numerical results and comparisons with various existing algorithms are provided to demonstrate the potential of the proposed techniques. It is shown that the proposed resource allocation methods substantially improve the system’s power efficiencies and are more computationally efficient. Moreover, the first method can meet the real-time application requirement and the second method is suitable for large dimensional ASABA problems.
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