On optimal call admission control in cellular networks
Wireless Networks
Channel Occupancy Times and Handoff Rate for Mobile Computing and PCS Networks
IEEE Transactions on Computers
Vertical handoffs in wireless overlay networks
Mobile Networks and Applications - Special issue: mobile networking in the Internet
Improving call admission policies in wireless networks
Wireless Networks
A decision-theoretic approach to resource allocation in wireless multimedia networks
DIALM '00 Proceedings of the 4th international workshop on Discrete algorithms and methods for mobile computing and communications
IEEE/ACM Transactions on Networking (TON)
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
ISCC '00 Proceedings of the Fifth IEEE Symposium on Computers and Communications (ISCC 2000)
On the complexity of solving Markov decision problems
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Distributed call admission control in mobile/wireless networks
IEEE Journal on Selected Areas in Communications
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In the near future, demand for Heterogeneous Wireless Networking (HWN) is expected to to increase. QoS provisioning in these networks is a challenging issue considering the diversity in wireless networking technologies and the existence of mobile users with different communication requirements. In HWNs with their increased complexity, "the curse of dimensionality" problem makes it impractical to directly apply the decision theoretic optimal control methods that are previously used in homogeneous wireless networks to achieve desired QoS levels. In this paper, optimal call admission control policies for HWNs are considered. A decision theoretic framework for the problem is derived by a dynamic programming formulation. We prove that for a two-tier wireless network architecture, the optimal policy has a two-dimensional threshold-based structure. Further, a novel algorithm called Structured Value Iteration is proposed as a numerically efficient method to determine the optimal policy in terms of its thresholds. Extensive simulation experiments are conducted. The numerical results show that the proposed algorithm is efficient in terms of its time-complexity and in achieving the optimal performance.