COMPARISON OF CALL DROP MINIMIZATION TECHNIQUES IN WCDMA WIRELESS COMMUNICATION NETWORK

COMPARISON OF CALL DROP MINIMIZATION TECHNIQUES IN WCDMA WIRELESS COMMUNICATION NETWORK

ABSTRACT

One of the research challenges in cellular networks is the design of an efficient model that can reduce callblocking probability and improve the quality of service (QoS) provided to mobile users. One most important parameter for assessing the quality of service (QoS) in a network is the probability of dropped calls, which has so far not been deeply studied within the context of established cellular networks. Call/packet dropping refers to the event described as the termination of calls in progress before either involved party intentionally ends the call. There are numerous drop call causes in cellular networks with majority of them occurring in the Um interfaces mainly due to lack of radio resources created by electromagnetic causes and user mobility (i.e. handover). Another important contributor of drop call rate is the traffic load in which, the call arrival rate and holding time play significant roles. Drop call probability is defined as the probability that a call is terminated due to one or all of trohe above-mentioned causes and is basically estimated from drop call rate by applying the Poisson probability distribution function. This work performs deep analysis and evaluates the comprehensive differences between the various techniques employ to reduce the effect of call drop algorithms in Wireless Code Division Multiple Access (WCDMA) networks. MATLAB simulation model of a simple WCDMA system with radio resource algorithms is implemented and analyzed to make a clear comparison between the algorithms in terms of outage probability, bit error rate (BER) and channel capacity which does not have an exact limit in WCDMA technique. The results showed that the hard handoff scheme offers a better outage probability amongst the call drop minimization schemes considered and the implementation possibility of all the schemes depends on their individual performances and network demands.