A Heuristics Based Approach for Cellular Mobile Network Planning

ABSTRACT Designing and planning of the switching, signaling and support network is a fairly complex process in cellular mobile network. In this paper, the problem of assigning cells to switches in cellular mobile network, which is considered a planning problem, is addressed. The cell to switch assignment problem which falls under the category of the Quadratic Assignment Problem (QAP) is a proven NP– hard problem. Further, the problem is modelled to include an additional constraint in the formulation. The additional constraint is of the maximum number of switch ports that are used for a cell's Base Station Transceiver System (BTS) connectivity to the switch. The addition of the constraint on the number of ports on a switch has immense practical signicance. This paper presents a non– deterministic heuristic based on Simulated Evolution (SimE) iterative algorithm to provide solutions. The methods adopted in this paper are a completely innovative formulation of the problem and involve application of Evolutionary Computing for this complex problem that may be extended to solutions of similar problems in VLSI design, distributed computing and many other applications

Designing Cellular Mobile Networks Using Non{Deterministic Iterative Heuristics

Abstract Network planning in the highly competitive, demand-adaptive and rapidly growing cellular telecommunications industry is a fairly complex and crucial issue. It comprises collective optimization of the supporting, switching, signaling and interconnection networks to minimize costs while observing imposed infrastructure constraints. This work focuses on the problem of assigning cells to switches, which comprise the Base Station Controller and Mobile Switching Center, in a cellular mobile network. As a classic instance of the NP-hard Quadratic Assignment Problem (QAP), deterministic algorithms are incapable of nding optimal solutions in the vast complex search space in polynomial time. Hence, a randomized, heuristic algorithm, such as Simulated Evolution is used in this work to optimize the transmission costs in cellular networks. The results achieved are compared with existing methods available in literature. Key words: Network planning, Cellular Mobile Network, Assignment, Quadratic Assignment Problem, Heuristics, Evolutionary Heuristics, Soft Computing

Network configuration improvement and design aid using artificial intelligence

This dissertation investigates the development of new Global system for mobile communications (GSM) improvement algorithms used to solve the nondeterministic polynomial-time hard (NP-hard) problem of assigning cells to switches. The departure of this project from previous projects is in the area of the GSM network being optimised. Most previous projects tried minimising the signalling load on the network. The main aim in this project is to reduce the operational expenditure as much as possible while still adhering to network element constraints. This is achieved by generating new network configurations with a reduced transmission cost. Since assigning cells to switches in cellular mobile networks is a NP-hard problem, exact methods cannot be used to solve it for real-size networks. In this context, heuristic approaches, evolutionary search algorithms and clustering techniques can, however, be used. This dissertation presents a comprehensive and comparative study of the above-mentioned categories of search techniques adopted specifically for GSM network improvement. The evolutionary search technique evaluated is a genetic algorithm (GA) while the unsupervised learning technique is a Gaussian mixture model (GMM). A number of custom-developed heuristic search techniques with differing goals were also experimented with. The implementation of these algorithms was tested in order to measure the quality of the solutions. Results obtained confirmed the ability of the search techniques to produce network configurations with a reduced operational expenditure while still adhering to network element constraints. The best results found were using the Gaussian mixture model where savings of up to 17% were achieved. The heuristic searches produced promising results in the form of the characteristics they portray, for example, load-balancing. Due to the massive problem space and a suboptimal chromosome representation, the genetic algorithm struggled to find high quality viable solutions. The objective of reducing network cost was achieved by performing cell-to-switch optimisation taking traffic distributions, transmission costs and network element constraints into account. These criteria cannot be divorced from each other since they are all interdependent, omitting any one of them will lead to inefficient and infeasible configurations. Results obtained further indicated that the search space consists out of two components namely, traffic and transmission cost. When optimising, it is very important to consider both components simultaneously, if not, infeasible or suboptimum solutions are generated. It was also found that pre-processing has a major impact on the cluster-forming ability of the GMM. Depending on how the pre-processing technique is set up, it is possible to bias the cluster-formation process in such a way that either transmission cost savings or a reduction in inter base station controller/switching centre traffic volume is given preference. Two of the difficult questions to answer when performing network capacity expansions are where to install the remote base station controllers (BSCs) and how to alter the existing BSC boundaries to accommodate the new BSCs being introduced. Using the techniques developed in this dissertation, these questions can now be answered with confidence.Dissertation (MEng)--University of Pretoria, 2008.Electrical, Electronic and Computer Engineeringunrestricte

Location Area Planning and Cell-to-Switch Assignment in Cellular Networks

Location area (LA) planning plays an important role in cellular networks because of the tradeoff caused by paging and registration signalling. The upper boundary for the size of an LA is the service area of a mobile services switching center (MSC). In that extreme case, the cost of paging is at its maximum but no registration is needed. On the other hand, if each cell is an LA, the paging cost is minimal but the cost of registration is the largest. Between these extremes lie one or more partitions of the MSC service area that minimize the total cost of paging and registration. In this paper, we seek to determine the location areas in an optimum fashion. Cell to switch assignments are also determined to achieve the minimization of the network cost. For that purpose, we use the available network information to formulate a realistic optimization problem, and propose an algorithm based on simulated annealing (SA) for its solution. Then, we investigate the quality of the SA-based technique by comparing it to greedy search, random generation methods, and a heuristic algorithm.Peer ReviewedPostprint (published version

Location area planning and cell-to-switch assignment in cellular networks

Abstract—Location area (LA) planning plays an important role in cellular networks because of the tradeoff caused by paging and registration signalling. The upper boundary for the size of an LA is the service area of a mobile services switching center (MSC). In that extreme case, the cost of paging is at its maximum but no registration is needed. On the other hand, if each cell is an LA, the paging cost is minimal but the cost of registration is the largest. Between these extremes lie one or more partitions of the MSC service area that minimize the total cost of paging and registration. In this paper, we seek to determine the location areas in an optimum fashion. Cell to switch assignments are also determined to achieve the minimization of the network cost. For that purpose, we use the available network information to formulate a realistic optimization problem, and propose an algorithm based on simulated annealing (SA) for its solution. Then, we investigate the quality of the SA-based technique by comparing it to greedy search, random generation methods, and a heuristic algorithm. Index Terms—Location area (LA), location management, location tracking, location update, paging area, simulated annealing. I

Location area planning and cell-to-switch assignment in cellular networks

Location area (LA) planning plays an important role in cellular networks because of the tradeoff caused by paging and registration signalling. The upper boundary for the size of an LA is the service area of a mobile services switching center (MSC). In that extreme case, the cost of paging is at its maximum but no registration is needed. On the other hand, if each cell is an LA, the paging cost is minimal but the cost of registration is the largest. Between these extremes lie one or more partitions of the MSC service area that minimize the total cost of paging and registration. In this paper, we seek to determine the location areas in an optimum fashion. Cell to switch assignments are also determined to achieve the minimization of the network cost. For that purpose, we use the available network information to formulate a realistic optimization problem, and propose an algorithm based on simulated annealing (SA) for its solution. Then, we investigate the quality of the SA-based technique by comparing it to greedy search, random generation methods, and a heuristic algorithm.Peer ReviewedPostprint (published version

Location area planning and cell-to-switch assignment in cellular networks

Location area (LA) planning plays an important role in cellular networks because of the tradeoff caused by paging and registration signalling. The upper boundary for the size of an LA is the service area of a mobile services switching center (MSC). In that extreme case, the cost of paging is at its maximum but no registration is needed. On the other hand, if each cell is an LA, the paging cost is minimal but the cost of registration is the largest. Between these extremes lie one or more partitions of the MSC service area that minimize the total cost of paging and registration. In this paper, we seek to determine the location areas in an optimum fashion. Cell to switch assignments are also determined to achieve the minimization of the network cost. For that purpose, we use the available network information to formulate a realistic optimization problem, and propose an algorithm based on simulated annealing (SA) for its solution. Then, we investigate the quality of the SA-based technique by comparing it to greedy search, random generation methods, and a heuristic algorithm.Peer Reviewe

Self-tuning algorithms for the assignment of packet control units and handover parameters in GERAN

Esta tesis aborda el problema de la optimización automática de parámetros en redes de acceso radio basadas en GSM-EDGE Radio Access Network (GERAN). Dada la extensión del conjunto de parámetros que se puede optimizar, este trabajo se centra en dos de los procesos encargados de la gestión de la movilidad: el proceso de (re)selección de celda para servicios por conmutación de paquetes y el proceso de traspaso para servicios de voz por conmutación de circuitos