Low complexity neural network structure for implementing the optimum maximum-likelihood multi-user receiver in a DS-CDMA communication system
Khoshbin-Ghomash, H., Ormondroyd, R. F. and Dunn, R. W., 1999. Low complexity neural network structure for implementing the optimum maximum-likelihood multi-user receiver in a DS-CDMA communication system. In: VTC 1999-Fall: IEEE VTS 50th Vehicular Technology Conference. Vol. 50. IEEE, pp. 643-647. (IEEE Vehicular Technology Conference)
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The capacity of direct-sequence code division multiple access systems is interference limited, particularly by multiple-access interference produced by other co-channel users. The optimum multi-user receiver calculates the maximum-likelihood ratio of the detected data for all users simultaneously, but it has a complexity that grows exponentially with the number of users. In this paper, a neural network approach to multi-user detection is considered. It is shown that the performance of this receiver is the same as the maximum-likelihood multi-user receiver but it has a much lower computational complexity.
|Item Type||Book Sections|
|Creators||Khoshbin-Ghomash, H., Ormondroyd, R. F. and Dunn, R. W.|
|Departments||Faculty of Engineering & Design > Electronic & Electrical Engineering|
|Additional Information||IEEE VTS 50th Vehicular Technology Conference, VTC 1999-Fall. 19-22 September 1999. Amsterdam, Netherlands.|
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