We study the impact of incorporating handoff prediction information in the session admission control process in mobile cellular networks. We evaluate the performance of optimal policies obtained with and without the predictive information, while taking into account possible prediction errors. Two different approaches to compute the optimal admission policy were studied: dynamic programming and reinforcement learning. Numerical results show significant performance gains when the predictive information is used in the admission process.
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Vicent PLA, Jose Manuel GIMENEZ-GUZMAN, Jorge MARTINEZ, Vicente CASARES-GINER, "Optimal Bandwidth Reservation in Multiservice Mobile Cellular Networks with Movement Prediction" in IEICE TRANSACTIONS on Communications,
vol. E88-B, no. 10, pp. 4138-4141, October 2005, doi: 10.1093/ietcom/e88-b.10.4138.
Abstract: We study the impact of incorporating handoff prediction information in the session admission control process in mobile cellular networks. We evaluate the performance of optimal policies obtained with and without the predictive information, while taking into account possible prediction errors. Two different approaches to compute the optimal admission policy were studied: dynamic programming and reinforcement learning. Numerical results show significant performance gains when the predictive information is used in the admission process.
URL: https://globals.ieice.org/en_transactions/communications/10.1093/ietcom/e88-b.10.4138/_p
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@ARTICLE{e88-b_10_4138,
author={Vicent PLA, Jose Manuel GIMENEZ-GUZMAN, Jorge MARTINEZ, Vicente CASARES-GINER, },
journal={IEICE TRANSACTIONS on Communications},
title={Optimal Bandwidth Reservation in Multiservice Mobile Cellular Networks with Movement Prediction},
year={2005},
volume={E88-B},
number={10},
pages={4138-4141},
abstract={We study the impact of incorporating handoff prediction information in the session admission control process in mobile cellular networks. We evaluate the performance of optimal policies obtained with and without the predictive information, while taking into account possible prediction errors. Two different approaches to compute the optimal admission policy were studied: dynamic programming and reinforcement learning. Numerical results show significant performance gains when the predictive information is used in the admission process.},
keywords={},
doi={10.1093/ietcom/e88-b.10.4138},
ISSN={},
month={October},}
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TY - JOUR
TI - Optimal Bandwidth Reservation in Multiservice Mobile Cellular Networks with Movement Prediction
T2 - IEICE TRANSACTIONS on Communications
SP - 4138
EP - 4141
AU - Vicent PLA
AU - Jose Manuel GIMENEZ-GUZMAN
AU - Jorge MARTINEZ
AU - Vicente CASARES-GINER
PY - 2005
DO - 10.1093/ietcom/e88-b.10.4138
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E88-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2005
AB - We study the impact of incorporating handoff prediction information in the session admission control process in mobile cellular networks. We evaluate the performance of optimal policies obtained with and without the predictive information, while taking into account possible prediction errors. Two different approaches to compute the optimal admission policy were studied: dynamic programming and reinforcement learning. Numerical results show significant performance gains when the predictive information is used in the admission process.
ER -