| Summary: | 碩士 === 國立臺灣科技大學 === 電子工程系 === 107 === In this thesis, we consider the problem of joint antenna selection, user scheduling, and power allocation in massive multiple-input-multiple-output (MIMO) wireless communication systems. The massive MIMO systems comprise of a large number of antennas at the base station which increase the complexity and need more hardware components such as RF chains. In recent years, energy efficiency has become a critical design metric for green communication systems. The energy efficiency is defined as the system sum-rate divided by the total power consumption to evaluate the sum-rate per unit energy the systems can provide. In order to maximize the system sum-rate or energy efficiency, we propose a new genetic algorithm to simultaneously perform antenna selection, user scheduling, and power allocation. This algorithm divides the chromosome into two parts. The first part is an integer string, representing the chosen antennas and the user selected. The other part is a real number string, representing the allocated power. In addition, new crossover and mutation operations are employed for this new type of chromosome. Simulation results show that the proposed method can achieve better performance compared with the state-of-the-art methods.
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