A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
ACM Computing Surveys (CSUR)
Microwave Mobile Communications
Microwave Mobile Communications
Wireless Communications & Mobile Computing
Tool development for post processing analysis of WCDMA measurements
ICCOM'07 Proceedings of the 11th Conference on 11th WSEAS International Conference on Communications - Volume 11
Rethinking Stream Ciphers: Can Extracting be Better than Expanding?
Wireless Personal Communications: An International Journal
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This paper presents a technique which is based on pattern recognition techniques, in order to estimate Mobile Terminal (MT) velocity. The proposed technique applies on received signal strength (RSS) measurements and more precisely on information extracted from Iub air interface, in wIDeband code-division multiple access (WCDMA) systems for transmission control purposes. Pattern recognition is performed by HIDden Markov Model (HMM), which is trained with downlink signal strength measurements for specific areas, employing Clustering LARge Applications (CLARA) like a clustering method. Accurate results from a single probe vehicle show the potential of the method, when applied to large scale of MTs.