The very limited nature of the GSM spectrum, coupled with the increasing demand by an extending number of subscribers place a strain on the network capacity. This leads to an equally raised number of calls that dropped and hence, subscriber dissatisfaction. Several strategies have been implemented in order to minimize these occurrences, with the most prominent being channel borrowing. Channel borrowing process is a scheme whereby frequencies allocated to other cells are temporarily assigned to cells with higher traffic loading so as to reduce the rate of dropped calls in the busy location, hence improving the grade of service of the entire network. This concept is implemented in such a manner as to ensure that the call quality in the original cell is not jeopardized by the borrowing process and the borrowed frequency is returned as soon as possible. The goal of channel borrowing is to ensure maximal utilization of the available spectrum to an operator in such a manner that the owner cell is not disadvantaged. This article presents a detailed review of various Channel Borrowing Schemes and proposes an Adaptive Channel Borrowing Scheme that efficiently borrows free Channels from nearby Cells deploying features in MATLAB R2012a. The ACB algorithm has suitable characteristics for a novel hybrid channel borrowing algorithm and it is based on real time call statistics using random number generators. It is measured with parameters such as Lending Potentials (LP), Borrowing Potentials (BP) and Borrowing Need (BN). These are traffic driven frequency borrowing parameters adopted in the investigation. From the result, an efficient and reliable means of borrowing additional Channels for temporary use without giving the entire system huge workload, was arrived at. The ACB algorithm has the capacity to maximally utilize the system resources hence, reducing the cost or need for the purchase of additional resources.
This work was carried out under the IoT-Enabled Smart and Connected Communities (SmartCU) research cluster of the Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria.