Optimizing satellite broadcast scheduling problem using the competitive Hopfield neural network

Yu Ju Shen, Ming Shi Wang

研究成果: Conference contribution

9 引文 斯高帕斯(Scopus)

摘要

In this paper the competitive Hopfield neural network method for finding a broadcasting schedule in the satellite system will be described. The Satellite Broadcast Scheduling (SBS) Problem is known as an NP-complete problem. Communication links between satellites and ground terminals are provided in a repetition of time slots. The goal of the proposed algorithm is to find the broadcasting schedule of satellites with the maximum number of broadcasting time slots under the constraints. A competitive learning rule provides a highly effective means for obtaining a resonance solution and is capable of reducing the time-consuming effort to obtain coefficients. The proposed method can always satisfy the problem constraints and guarantee the viability of the solutions for the SBS problem. The competitive mechanism simplifies the network complexity. The proposed method is greatly suitable for implementation on a digital machine. Furthermore, the competitive Hopfield neural network method permits temporary energy increases to escape from local minima. Simulation results show that the competitive Hopfield neural network method can improve system performance and with fast convergence and high reliability.

原文English
主出版物標題2007 Wireless Telecommunications Symposium, WTS 2007
DOIs
出版狀態Published - 2007
事件2007 Wireless Telecommunications Symposium, WTS 2007 - Pomona, CA, United States
持續時間: 2007 4月 262007 4月 28

出版系列

名字2007 Wireless Telecommunications Symposium, WTS 2007

Other

Other2007 Wireless Telecommunications Symposium, WTS 2007
國家/地區United States
城市Pomona, CA
期間07-04-2607-04-28

All Science Journal Classification (ASJC) codes

  • 電腦網路與通信
  • 電氣與電子工程
  • 通訊

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