Integer and combinatorial optimization
Integer and combinatorial optimization
Worst-case performance of cellular channel assignment policies
Wireless Networks - Special issue on performance evaluation methods for wireless networks
Dynamic channel assignment in wireless communication networks
International Journal of Network Management
Reactive GRASP with path relinking for channel assignment in mobile phone networks
DIALM '01 Proceedings of the 5th international workshop on Discrete algorithms and methods for mobile computing and communications
An efficient approach for distributed channel allocation in cellular mobile networks
DIALM '01 Proceedings of the 5th international workshop on Discrete algorithms and methods for mobile computing and communications
A distributed algorithm for dynamic channel allocation
Mobile Networks and Applications - Analysis and Design of Multi-Service Wireless Networks
Cellular channel assignment: a new localized and distributed strategy
Mobile Networks and Applications - Dial m for mobility: discrete algorithms and methods for mobile computing and communication
Channel assignment schemes for cellular mobile telecommunication systems: A comprehensive survey
IEEE Communications Surveys & Tutorials
Static and dynamic channel assignment using neural networks
IEEE Journal on Selected Areas in Communications
Wireless dynamic channel assignment performance under packet data traffic
IEEE Journal on Selected Areas in Communications
On the impact of introducing advanced devices into a cognitive radio network
SECON'09 Proceedings of the 6th Annual IEEE communications society conference on Sensor, Mesh and Ad Hoc Communications and Networks
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This paper studies the problem of centralized dynamic channel assignment (DCA) in wireless cellular systems under space and time-varying channel demand. The objective is to minimize the number of channels required to satisfy demand while also satisfying co-channel interference constraints. Cumulative co-channel interference constraints govern channel reuse, via a threshold decision criterion based on the carrier-to-interference ratio. The paper makes two contributions. First, it provides an empirical bound on the difference between the minimal number of channels required based only on geographic reuse distance versus the cumulative interference case in the context of linearly increasing demand. The bound is characterized using only the reuse distance. It is obtained with an Integer Programming (IP) based strategy that uses channel assignments for one demand state to assign channels for the next state. Geographic locality constraints are applied to limit reassignments. The impact of cumulative interference constraints is observed to be small for small geographic localities. Second, the paper presents a new, fast DCA heuristic that is based on the characteristic channel reuse patterns used by the IP-based strategy. The heuristic and IP-based method yield similar results for the zero blocking condition. The DCA heuristic is applied to the problem of estimating the blocking probabilities of call arrivals modeled by a two state discrete-time Markov chain and uniformly distributed holding times. The blocking performance for an ensemble of spatial load imbalance distributions is uniquely characterized using the heuristic and IP solutions.