COMMON PILOT CHANNEL POWER CONTROL FOR 3G CELLULAR NETWORKS TRAFFIC LOAD BALANCING BASED ON FUZZY LOGIC CONTROL

Abstract

Mobile communication has increasingly become popular and in addition there has been an accelerated penetration of smart phones which has led to a significant increase in the use of mobile data services. Network congestion control remains important and of high priority, especially given the growing size, demand, and speed of cellular networks. One way of dealing with this problem has been automatic base transceiver station (BTS) optimization. Recent research in this area has come up with Capacity and Coverage Optimization techniques based on self-organizing networks (SON). However, control of the Common Pilot Power Channel (CPICH) power in order to increase the cell capacity still presents a major challenge. In this research the problem of traffic load balancing in third generation (3G) cellular networks was addressed using rule-based fuzzy logic to control the CPICH power and as a result optimize the cell capacity. The CPICH power is an essential parameter and is used by engineers to enhance network performance and coverage, and increase the network‟s capacity and coverage. One of the reasons for choosing fuzzy logic controllers is its logical resemblance to a human operator. It operates on the foundations of a knowledge base derived from an expert operator‟s knowledge. The autonomous operation will reduce the frequent attention and effort required by the radio optimization engineer to carry out traffic load balancing tasks which are currently done mostly manually. In the study fuzzy logic was used in the detection of high load 3G cells that do not have enough cell resources available and could benefit from CPICH power adjustment as a radio optimization engineer would normally do manually. A fuzzy logic controller (FLC) was then designed with the downlink cell load, received total wideband power (RTWP) and the neighboring cells‟ load as the inputs. The output of the FLC was the CPICH power setting which determined whether to increase or decrease the coverage footprint of the cell hence influencing the cell downlink power utilization. The effect of varying the CPICH power on the downlink cell utilization based on fuzzy logic was investigated and the proposed FLC based cell capacity enhancement approach was evaluated through a comparison with a cell with constant proportion CPICH power. Simulation results showed that the fuzzy logic based CPICH power control achieved a significant improvement in the downlink cell utilization which in turn improved the cell performance.