In this paper, we propose a neural network algorithm that uses the expanded maximum neuron model to solve the channel assignment problem of cellular radio networks, which is an NP-complete combinatorial optimization problem. The channel assignment problem demands minimizing the total interference be
On-line algorithms for the channel assignment problem in cellular networks
โ Scribed by Pilu Crescenzi; Giorgio Gambosi; Paolo Penna
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 364 KB
- Volume
- 137
- Category
- Article
- ISSN
- 0166-218X
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โฆ Synopsis
We consider the on-line channel assignment problem in the case of cellular networks and we formalize this problem as an on-line load balancing problem for temporary tasks with restricted assignment. For the latter problem, we provide a general solution (denoted as the cluster algorithm) and we characterize its competitive ratio in terms of the combinatorial properties of the graph representing the network. We then compare the cluster algorithm with the greedy one when applied to the channel assignment problem: it turns out that the competitive ratio of the cluster algorithm is strictly better than the competitive ratio of the greedy algorithm. The cluster method is general enough to be applied to other on-line load balancing problems and, for some topologies, it can be proved to be optimal.
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