Noisy chaotic neural network for resource allocation in high-speed train OFDMA system

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• 作者：Yisheng Zhao ; Hong Ji ; Zhonghui Chen
• 关键词：resource allocation ; high ; speed train ; orthogonal frequency ; division multiple access (OFDMA) ; noisy chaotic neural network
• 刊名：Transactions of Tianjin University
• 出版年：2014
• 出版时间：October 2014
• 年：2014
• 卷：20
• 期：5
• 页码：368-374
• 全文大小：579 KB
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• 作者单位：Yisheng Zhao (1)
  Hong Ji (1)
  Zhonghui Chen (2)
  
  1. Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, 100876, China
  2. College of Physics and Information Engineering, Fuzhou University, Fuzhou, 350116, China
  
• ISSN：1995-8196

文摘

High-speed train communication system is a typical high-mobility wireless communication network. Resource allocation problem has a great impact on the system performance. However, conventional resource allocation approaches in cellular network cannot be directly applied to this kind of special communication environment. A multi-domain resource allocation strategy was proposed in the orthogonal frequency-division multiple access (OFDMA) of high-speed. By analyzing the effect of Doppler shift, sub-channels, antennas, time slots and power were jointly considered to maximize the energy efficiency under the constraint of total transmission power. For the purpose of reducing the computational complexity, noisy chaotic neural network algorithm was used to solve the above optimization problem. Simulation results showed that the proposed resource allocation method had a better performance than the traditional strategy.