POCA: pattern-oriented channel assignment scheme for wireless cellular networks

2004 ◽  
Vol 14 (4) ◽  
pp. 273-277
Author(s):  
Rana Ejaz Ahmed ◽  
Robin Cardan
2003 ◽  
Vol 14 (03) ◽  
pp. 439-463 ◽  
Author(s):  
Sasthi C. Ghosh ◽  
Bhabani P. Sinha ◽  
Nabanita Das

Given a hexagonal cellular network with specific demand Vector and frequency separation constraints, we introduce the concept of a critical block of the network, that leads us to an efficient channel assignment scheme for the whole network. A novel idea of partitioning the critical block into several smaller sub-networks with homogeneous demands has been introduced which provides an elegant way of assigning frequencies to the critical block. This idea of partitioning is then extended for assigning frequencies to the rest of the network. The proposed algorithm provides an optimal assignment for all well-known benchmark instances including the most difficult two. It is shown to be superior to the existing frequency assignment algorithms, reported so far, in terms of both bandwidth requirement and computation time.


2010 ◽  
Vol 2010 ◽  
pp. 1-11 ◽  
Author(s):  
Xin Wu ◽  
Arunita Jaekel ◽  
Ataul Bari ◽  
Alioune Ngom

In cellular networks, it is important to determine an optimal channel assignment scheme so that the available channels, which are considered as “limited” resources in cellular networks, are used as efficiently as possible. The objective of the channel assignment scheme is to minimize thecall-blockingand thecall-droppingprobabilities. In this paper, we present two efficient integer linear programming (ILP) formulations, foroptimallyallocating a channel (from a pool of available channels) to an incoming call such that both “hard” and “soft” constraints are satisfied. Our first formulation, ILP1, does not allow channel reassignment of the existing calls, while our second formulation, ILP2, allows such reassignment. Both formulations can handle hard constraints, which includesco-siteandadjacent channelconstraints, in addition to the standardco-channelconstraints. The simplified problem (with only co-channel constraints) can be treated as a special case of our formulation. In addition to the hard constraints, we also consider soft constraints, such as, thepacking condition, resonance condition,andlimiting rearrangements, to further improve the network performance. We present the simulation results on a benchmark 49 cell environment with 70 channels that validate the performance of our approach.


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