Link Quality-Based Mobile-Controlled Handoff Analysis Using Stochastic Models

Abstract

With limited available frequency spectrum and increasing demand for cellular communication services, the problem of handoff becomes increasingly important. Poorly designed handoff schemes tend to generate very heavy signaling traffic and thereby, a drastic decrease in the quality of service (QoS). In urban mobile cellular radio system, the cell size is small. The handoff procedure has a significant impact on the system performance. Blocking probability of originating calls and forced termination probability of ongoing calls reflects the performance of the system. In this paper, we use mobile-controlled handoff process. MS is moving from one cell to another cell. Relative signal strength and relative residual energy are measured. Important channel quality parameters, for the channels with line of sight (α) and without line of sight (β) are considered. Using these parameters, weights of the channels are determined in three neighboring cells and the servicing cell. The channel weights of four cells are compared with the chosen signal strength threshold value to make a decision of handoff process or to continue service with the same base station (BS). Prioritized hard handoff is preferred in the work. Handoff performance metrics such as arrival rate of originating calls, blocking probability of originating calls, arrival rate of handoff calls, blocking probability of handoff calls, and network parameters such as sender window size, queue length at the servicing link are measured. Performance analysis parameters such as packet loss due to congestion, round-trip delay, and throughput are discussed. It helps in controlling the oscillatory behavior of the switch or router normally used for traffic control at the BS. Using the results and applying an explicit feedback, the link congestion and packet losses can be minimized. It helps for improving the quality of service (QoS) in 3G, 4G, and next-generation mobile communication. Stochastic models are used to analyze the system performance. Using MATLAB programme, result analysis is made through graphs and statistical data.