On The Multiuser Detection Using a Neural Network in Code-Division Multiple-Access Communications

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• Copyright notice. c1993 IEICE All rights reserved.　 "On The Multiuser Detection Using a Neural Network in Code-Division Multiple-Access Communications"Teruyuki MIYAJIMA,Takaaki HASEGAWA, Misao HANEISHI. IEICE TRANSACTIONS on Communications, 1993 Vol.E76-B No.8 pp. 961-968 許諾No.07RB0055.In this paper we consider multiuser detection using a neural network in a synchronous code-division multiple- access channel. In a code-division multiple-access channel, a matched filter is widely used as a receiver. However, when the relative powers of the interfering signals are large, i.e. the near-far problem, the performances of the matched filter receiver degrade. Although the optimum receiver for multiuser detection is superior to the matched filter receiver in such situations, the optimum receiver is too complex to be implemented. A simple technique to implement the optimum multiuser detection is required. Recurrent neural networks which consist of a number of simple processing units can rapidly provide a collectively-computed solution. Moreover, the network can seek out a minimum in the energy function. On the other hand, the optimum multiuser detection in a synchronous channel is carried out by the maximization of a likelihood function. In this paper, it is shown that the energy function of the neural network is identical to the likelihood function of the optimum multiuser detection and the neural network can be used to implement the optimum multiuser detection. Performance comparisons among the optimum receiver, the matched filter one and the neural network one are carried out by computer simulations. It is shown that the neural network receiver has a capability to achieve near-optimum performance in several situations and local minimum problems are few serious.

• 社団法人電子情報通信学会の論文
• 1993-08-25

著者

• MIYAJIMA Teruyuki

  Faculty of 'Engineering, Ibaraki University,

• Hasegawa Takaaki

  Faculty Of Engineering Saitama University

• Haneishi Misao

  Faculty Of Engineering Saitama University

• Miyajima Teruyuki

  Faculty Of 'engineering Ibaraki University

• Miyajima Teruyuki

  Faculty Of Engineering Saitama University

• 長谷川 孝明

  Faculty of Engineering, Ibaraki University

• 羽石 操

  Faculty of Engineering, Saitama University

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