The Markov-modulated Poisson process (MMPP) cookbook
Performance Evaluation
Analytical comparison of different GPRS introduction strategies
Proceedings of the 3rd ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems
Adaptive performance management for universal mobile telecommunications system networks
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MASCOTS '98 Proceedings of the 6th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
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IEEE Communications Magazine
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An Erlang-like law for GPRS/EDGE engineering and its first validation on live traffic
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An improved model for GSM/GPRS/EDGE performance evaluation
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Comparative results in GSM/GPRS networks modeling according to Erlang-B and Engset traffic models
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ACM Computing Surveys (CSUR)
Dimensioning rules regarding radio resources in GSM/GPRS networks
WSEAS TRANSACTIONS on COMMUNICATIONS
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WSEAS TRANSACTIONS on COMMUNICATIONS
Radio resources dimensioning according to different allocation strategies in GSM/GPRS networks
CIMMACS'09 Proceedings of the 8th WSEAS International Conference on Computational intelligence, man-machine systems and cybernetics
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Computer Networks: The International Journal of Computer and Telecommunications Networking
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Mixed traffic models for dimensioning radio resources in GSM/GPRS networks
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Computers and Electrical Engineering
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IEEE/ACM Transactions on Networking (TON)
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This paper presents an efficient and accurate analytical model for the radio interface of the general packet radio service (GPRS) in a GSM network. The model is utilized for investigating how many packet data channels should be allocated for GPRS under a given amount of traffic in order to guarantee appropriate quality of service. The presented model constitutes a continuous-time Markov chain. The Markov model represents the sharing of radio channels by circuit switched GSM connections and packet switched GPRS sessions under a dynamic channel allocation scheme. In contrast to previous work, the Markov model explicitly represents the mobility of users by taking into account arrivals of new GSM and GPRS users as well as handovers from neighboring calls. Furthermore, we take into account TCP flow control for the GPRS data packets. To validate the simplifications necessary for making the Markov model amenable to numerical solution, we provide a comparison of the results of the Markov model with a detailed simulator on the network level.