Distributed dynamic channel allocation for mobile computing
Proceedings of the fourteenth annual ACM symposium on Principles of distributed computing
Online channel allocation in FDMA networks with reuse constraints
Information Processing Letters
Colouring proximity graphs in the plane
Discrete Mathematics
Distributed online frequency assignment in cellular networks
Journal of Algorithms
Graph labeling and radio channel assignment
Journal of Graph Theory
Channel assignment schemes for cellular mobile telecommunication systems: A comprehensive survey
IEEE Communications Surveys & Tutorials
Channel assignment and graph multicoloring
Handbook of wireless networks and mobile computing
On-line algorithms for the channel assignment problem in cellular networks
Discrete Applied Mathematics
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We consider the problem of channel assignment in cellular networks with arbitrary reuse distance. A simple and commonly used strategy is called fixed channel assignment, in which base stations can only use channels from fixed sets that are pre-computed to avoid interference with neighbors. On the other hand, dynamic channel assignment makes all radio channels available to all calls in principle: a station may use any channels that are currently unused in any neighboring cells with whom there might be a possibility of interference. In between are borrowing strategies, where a fixed number of channels is reserved per node, but borrowing of idle channels is allowed. While it has been shown that dynamic channel assignment can work better than fixed channel assignment in some situations, its worst case performance, in terms of the number of channels used, has not been studied. We show upper bounds and lower bounds for the competitive ratio of a previously proposed and widely studied version of dynamic channel assignment, which we refer to as the greedy algorithm, for arbitrary reuse distance r. Our main result is that this type of dynamic assignment, though generally regarded to provide higher capacity than fixed assignment or borrowing approach, has in fact, a poorer worst-case performance. For any r, the greedy algorithm is shown to have performance ratio at most 6. For r = 2, we give tight bounds on its performance, and for r = 2 or 3, we show that previously proposed borrowing strategies actually do better in the worst case. We also show a simple borrowing strategy for arbitrary reuse distance and prove bounds on its performance.