Artificial Neural Network Approach to Mobile Location Estimation in GSM Network

The increase in utilisation of mobile location-based services (LBS) for commercial, safety and security purposes among others are the key drivers for improving location estimation accuracy to better serve those purposes. Hence, developing mobile location estimation with high accuracy has been an issue of a major research concern as so many methods have been proposed. Among these methods include Cell ID, global positioning system (GPS), fingerprinting, statistical, geometrical, angle, time based and recently artificial intelligence methods. The GPS techniques have offered superior measurement accuracy to others but suffer accuracy degradation in indoor and dense urban area due to non-line of sight (NLOS) propagation. This paper proposes the application of Levenberg Marquardt (LMA) training algorithm on new robust multilayered perceptron (MLP) neural network architecture for mobile positioning fitting for the urban area in the considered GSM network using received signal strength (RSS). The key performance metrics such as accuracy, cost, reliability and coverage are the major points considered in this paper. The technique was evaluated through a simulation using real data from field measurement and the results obtained proved the proposed model provides a practical positioning that meet Federal Communication Commission (FCC) accuracy requirement

An optimum dynamic priority-based call admission control scheme for universal mobile telecommunications system

The dynamism associated with quality of service (QoS) requirement for traffic emanating from smarter end users devices founded on the internet of things (IoTs) drive, places a huge demand on modern telecommunication infrastructure. Most telecom networks, currently utilize robust call admission control (CAC) policies to ameliorate this challenge. However, the need for smarter CAC has becomes imperative owing to the sensitivity of traffic currently being supported. In this work, we developed a prioritized CAC algorithm for third Generation (3G) wireless cellular network. Based on the dynamic priority CAC (DP-CAC) model, we proposed an optimal dynamic priority CAC (ODP-CAC) scheme for Universal Mobile Telecommunication System (UMTS). We then carried out simulation under heavy traffic load while also exploiting renegotiation among different call traffic classes. Also, we introduced queuing techniques to enhance the new calls success probability while still maintaining a good handoff failure across the network. Results show that ODP-CAC provides an improved performance with regards to the probability of call drop for new calls, network load utilization and grade of service with average percentage value of 15.7%, 5.4% and 0.35% respectively

APPLICATION OF SELF-ORGANIZING MAP TO INTELLIGENT ANALYSIS OF CELLULAR NETWORKS

ABSTRACT In this work, the efficacy and scalability of the self-organizing map (SOM) algorithm, which is a class of artificial neural network (ANN), over traditional methods of analyzing cellular network variables was shown using key performance indicators (KPIs) data collected from an operational network service provider in Nigeria. Performance trends of various cells over a period of time were evaluated and rules of significance measure extracted which could form the basis for network optimization

Load-shared redundant interface for LTE access network

Technological and industrial revolution has led to rapid increase in the request for various services in Long Term Evolution (LTE). These requests characterize different network traffic and are handled adequately in order to maintain a defined level of quality of service (QoS). The number and type of services requested are probabilistic and complex to handle. Conventionally, sustained increase in network traffic is handled by cell splitting techniques with proper network management schemes and/or increase in resources allocated to a cell. However, cell splitting is constrained by the availability of site location, energy consumption, frequent handoff, equipment cost etc., and the increase in resources is inconceivable due limited available communication resources. To solve these challenges, this work proposed a solution that leads the installation and activation of a load-shared redundant network interface as a complement to LTE base station. The interface was managed by load balancing technique, frequency reuse and carrier diversification. The work was simulated with Network Simulator 3 (ns-3.24) and tested with video traffic. The results obtained showed that the proposed scenario conserved 15.2% energy while achieving similar performance in terms of delay, throughput and loss ratio with the cell division technique