For the integration network of a cellular network and a wireless local area network （WLAN）, a priority-based dynamic load transfer （PDLT） algorithm is proposed. The dynamic vertical handoffs by call admission cont...
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For the integration network of a cellular network and a wireless local area network （WLAN）, a priority-based dynamic load transfer （PDLT） algorithm is proposed. The dynamic vertical handoffs by call admission control are jointly determined by the network conditions and the traffic characteristics in combination with the location-condition of mobile terminals. When there is no bandwidth resource available in the cellular network or WLAN, the proposed PDLT algorithm allows an incoming voice call or data call within the overlapping area of the cellular network and the WLAN to be directed to the spare network; meanwhile, by dynamically computing the occupancy of the bandwidth resource, the proposed PDLT algorithm also allows an ongoing voice call or data communication to be transferred to the network with a sufficient bandwidth resource according to the given threshold to balance the number of voice/data calls in the two networks. The analysis results of a two-dimensional Markov model and the simulation results show that the PDLT algorithm can effectively enhance the whole integrated network＇ s traffic, reduce the blocking probability of new calls and increase the data throughput, and thus decrease the response time for various services.
In order to improve the performance of voice conversion, the fundamental frequency （F0） transformation methods are investigated, and an efficient F0 transformation algorithm is proposed. First, unlike the traditiona...
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In order to improve the performance of voice conversion, the fundamental frequency （F0） transformation methods are investigated, and an efficient F0 transformation algorithm is proposed. First, unlike the traditional linear transformation methods, the relationships between F0s and spectral parameters are explored. In each component of the Gaussian mixture model （GMM）, the F0s are predicted from the converted spectral parameters using the support vector regression （SVR） method. Then, in order to reduce the over- smoothing caused by the statistical average of the GMM, a mixed transformation method combining SVR with the traditional mean-variance linear （MVL） conversion is presented. Meanwhile, the adaptive median filter, prevalent in image processing, is adopted to solve the discontinuity problem caused by the frame-wise transformation. Objective and subjective experiments are carried out to evaluate the performance of the proposed method. The results demonstrate that the proposed method outperforms the traditional F0 transformation methods in terms of the similarity and the quality.
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