Researches On Handoff Strategies For Multi-service Mobile Cellular Communication System

Mobile cellular radio systems have been attracting great interests of researchers. This thesis deals with some major issues in systems, i.e. handoff models and handoff schemes. A new handoff model for the finite user based on the cellular traffic, and an integrated multi-service handoff strategy for the multi-service mobile cellular communication system are proposed. Furthermore, their performance measures are analyzed.After brief introduction of mobile cellular systems, several conventional handoff schemes, namely non-priority reservation, priority reservation, and queuing priority reservation and integrated voice/data services schemes, are summarized in Chapter 2. Several existing traffic models are also discussed in this chapter.We first study the finite user based cellular traffic new model and its performance in Chapter 3. Erlang B model handles the traffic problem efficiently when the total user number is infinite, but it may not be true when the total user number is not close to be infinite. This chapter proposes the model with finite user. According to the model, equations are proposed to describe the model and the performances are analyzed. An approximation of blocking probability under this effect is derived. The simulation result shows that these equations become same with Erlang B model when user pool is infinite on the blocking probability and the average online user number, and that there will be difference on blocking probability with a small change of system load, when users move between microcells, but stay in the same macrocell.Next, in Chapter 4, we propose an improved handoff strategy with combination of channel reservation and preemptive priority for integrated real-time and non real-time service cellular mobile systems. Average transmission delay of non real-time service, blocking probability of real-time service and forced termination probability of real-time service performances are analyzed.Simulation results show that the forced termination probability of real-time service is significantly reduced with our strategy without sacrificing non real-time service QoS much. Our strategy improves the channel utilization and provides better QoS for mobile users by adjusting the priority adaptively.Finally, in Chapter 5, conclusions of the study are briefly summarized. And future directions for the study are also indicated.