Using a genetic algorithm approach to solve the dynamic channel-assignment problem

Abstract

The Channel Assignment Problem is an NP-complete problem to assign a minimum number of channels under certain constraints to requested calls in a cellular radio system. Examples of the many approaches to solve this problem include using neural-networks, simulated annealing, graph colouring, genetic algorithms, and heuristic searches. We present a new heuristic algorithm that consists of three stages: 1) determine-lower-bound cell regular interval assignment; 2) greedy region assignment; and 3) genetic algorithm assignment. Through simulation, we show that our heuristic algorithm achieves lower bound solutions for 11 of the 13 instances of the well known Philadelphia benchmark problem. Our algorithm also has the advantage of being able to find optimum solutions faster than existing approaches that use neural networks.

Multihop Cellular Networks: Dynamic Channel Assignment and Routing Protocol for Improving Performance

“…In reference [6] the genetic algorithm is provided as a solution to the problem of channel assignment and the algorithm is used to maximize the frequency channel reuse among the cells in the cellular Networks. Channels can be reused among the cells as long as the distance among those cells is sufficiently large.…”

The E3 architecture: enabling future cellular networks with cognitive and self‐x capabilities

“…Research in the field of interworking of diverse systems has been mainly targeted at gathering inputs from numerous entities within a network and taking decisions appropriate for performance optimization [8]. Apart from this, related research areas have included reconfigurable radio resource management [10][11][12], as well as spectrum management [13][14][15][16] and radio enablers, in a multi-radio environment. These have been achieved by (a) monitoring and analysing the statistical performance and the associated quality of service (QoS) levels provided by the network elements, (b) inter-working with service provider mechanisms, (c) performing dynamic network planning as a result of resource management strategies, and (d) introducing into the network new radio enablers providing information on available RATs, operators, frequencies allocated to RATs, etc.…”

Architecture and Performance of an Island Genetic Algorithm-Based Cognitive Network

“…The genetic algorithm has been successfully applied to channel allocation problems in the past [11]- [13]. Chakraborty and Chakraborty [11] use a centralized GA to compute a fixed channel allocation.…”

“…Matsui et al [12] apply a distributed GA to a fixed channel allocation problem. Fu et al [13] combine a greedy algorithm with a centralized GA to perform dynamic channel allocation. All of these applications are for cellular networks.…”