PAVAN: a policy framework for content availabilty in vehicular ad-hoc networks
Proceedings of the 1st ACM international workshop on Vehicular ad hoc networks
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NGI'09 Proceedings of the 5th Euro-NGI conference on Next Generation Internet networks
Optimal state estimation in the presence of communication costs and packet drops
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Adaptive Sampling for Linear State Estimation
SIAM Journal on Control and Optimization
| Hi-index | 754.84 |
This paper explores optimization of paging and registration policies in cellular networks. Motion is modeled as a discrete-time Markov process, and minimization of the discounted, infinite-horizon average cost is addressed. The structure of jointly optimal paging and registration policies is investigated through the use of dynamic programming for partially observed Markov processes. It is shown that there exist policies with a certain simple form that are jointly optimal. An iterative algorithm for policies with the simple form is proposed and investigated. The algorithm alternates between paging policy optimization, and registration policy optimization. It finds a pair of individually optimal policies. Majorization theory and Riesz's rearrangement inequality are used to show that jointly optimal paging and registration policies are given for symmetric or Gaussian random walk models by the nearest-location-first paging policy and distance threshold registration policies.