Code assignment for hidden terminal interference avoidance in multihop packet radio networks
IEEE/ACM Transactions on Networking (TON)
Worst-case performance of cellular channel assignment policies
Wireless Networks - Special issue on performance evaluation methods for wireless networks
Assigning codes in wireless networks: bounds and scaling properties
Wireless Networks
Dynamic channel assignment with cumulative co-channel interference
ACM SIGMOBILE Mobile Computing and Communications Review
A multifrequency MAC specially designed for wireless sensor network applications
ACM Transactions on Embedded Computing Systems (TECS)
Resource management in cellular communication using particle swarm optimization
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
A dynamic channel assignment in GSM telecommunication network using modified genetic algorithm
Proceedings of the 6th Euro American Conference on Telematics and Information Systems
Automatic call management in a cellular mobile network by fuzzy threshold logic
International Journal of Knowledge-based and Intelligent Engineering Systems - Intelligent Information Processing: Techniques and Applications
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As the use of mobile communications systems grows, the need arises for new and more efficient channel allocation techniques. The total number of available channels on a real-world network is in fact a scarce resource, and many assignment heuristics suffer from a clear lack of flexibility (this is the case of Fixed Channel Allocation), or from high computational and communication complexity (as with channel borrowing techniques). Performance can be improved by representing the system with an objective function whose minimum is associated with a good configuration; the various constraints appear as penalty terms in the function. The problem is thus reduced to the search for a minimum, that is often performed via heuristic algorithms like Hopfield neural networks, simulated annealing or reinforcement learning. These strategies usually require a central process to have global information and decide for all cells. We consider an objective-function formulation of the channel assignment problem that has been previously solved by search heuristics; we prove that the search time for the global minimum of the objective function is O(n log n), and therefore there is no need for search techniques. Finally we show that the algorithm that arises from this formulation can be modified so that global knowledge and synchronization are no longer required, and we give its distributed version. By simulating a cellular network with mobile hosts on a hexagonal cell pattern with uniform call distribution, we show that our technique actually performs better than the best known algorithms.