Statistical solution to the capacity problem in direct-sequence code-division multiple-access communication systems |
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Authors: | Eshima, Nobuoki Kohda, Tohru Tabata, Minoru |
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Affiliation: | Department of Statistics, Oita University, 1-1 Idaiga-Oka, Hasama, Oita 879-5593, Japan |
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Abstract: | Tohru KohdaDepartment of Computer Science and Communication Engineering, Kyushu University, Fukuoka 812-8581, JapanMinoru TabataDepartment of Mathematical Sciences, Osaka Prefecture University, Osaka 599-8531, Japan Email: eshima{at}med.oita-u.ac.jpReceived on September 21, 2005; Accepted on May 2, 2006 Capacity in the direct-sequence code-division multiple-access(DS/CDMA) communication system was considered according to thecode acquisition performance with the conventional serial-searchmethod, because code acquisition needs a difficult operation.Since capacity in DS/CDMA systems is defined by the maximumnumber of users that can simultaneously transmit their signalswith the same carrier frequencies, assuring a larger capacityis very important in DS/CDMA systems with respect to the economyof frequency source. This paper reconsiders the capacity problemthrough a statistical approach to code acquisition. First, aDS/CDMA system model is reviewed. Second, properties of thecounting method for code acquisition are discussed. It is provedthat the method can acquire the target user's code under anynumber of interference users that simultaneously transmit theirsignals, and that the method can guarantee a considerable precisionin code acquisition. Third, an observation time necessary forcode acquisition is given from a statistical discussion, andthe original counting method is modified into a simpler one.It is concluded that the capacity of the DS/CDMA communicationsystem can be set by the bit error-rate-based capacityor signal-to-noise ratio-based capacity, i.e. post-acquisition-basedcriterion, rather than the acquisition-based capacity. |
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Keywords: | acquisition-based capacity bit error-rate-based capacity code acquisition DS/CDMA system statistical decision theory. |
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