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Resource allocation for high-speed railway downlink MIMO-OFDM system using quantum-behaved particle swarm optimization

机译:基于量子行为粒子群算法的高速铁路下行MIMO-OFDM系统资源分配

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Resource allocation problem in high-speed railway wireless communication networks is one of the key issues to improve the efficiency of resource utilization. However, traditional resource allocation methods cannot be directly applied to this special communication system. In this paper, we propose a resource allocation approach for high-speed railway downlink orthogonal frequency-division multiplexing (OFDM) system with multiple-input multiple-output (MIMO) antennas. Sub-carriers, antennas, time slots, and power are jointly considered, which is formulated as a mixed-integer nonlinear programming problem. The effect of the moving speed on Doppler shift is analyzed to calculate the inter-carrier interference power. The objective is to maximize the throughput under the constraint of total transmission power. In order to reduce computational complexity, suboptimal solution to the optimization problem is obtained by quantum-behaved particle swarm optimization. Simulation results show that the proposed resource allocation strategy has a better performance compared with an existing one.
机译:高速铁路无线通信网络中的资源分配问题是提高资源利用效率的关键问题之一。但是,传统的资源分配方法无法直接应用于该特殊通信系统。在本文中,我们提出了一种具有多输入多输出(MIMO)天线的高速铁路下行链路正交频分复用(OFDM)系统的资源分配方法。共同考虑子载波,天线,时隙和功率,其被配制成混合整数非线性编程问题。分析了移动速度对多普勒偏移的影响,以计算载波间干扰功率。目标是在总传输功率的约束下最大化吞吐量。为了降低计算复杂性,通过量子行为粒子群优化获得优化问题的次优方法。仿真结果表明,与现有的,建议的资源分配策略具有更好的性能。

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