Abstract
This paper proposes a novel solution to the dynamic channel allocation problem in cellular telecommunication networks featuring user mobility and call handoffs. We investigate the performance of a number of reinforcement learning algorithms including Q-learning and SARSA, and show via simulations that a reduced-state version of SARSA incorporating a limited channel reassignment mechanism provides superior performance in terms of new call and handoff blocking probability and a significant reduction in memory requirements.
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Lilith, N., Dogançay, K. (2004). Reduced-State SARSA with Channel Reassignment for Dynamic Channel Allocation in Cellular Mobile Networks. In: de Souza, J.N., Dini, P., Lorenz, P. (eds) Telecommunications and Networking - ICT 2004. ICT 2004. Lecture Notes in Computer Science, vol 3124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27824-5_172
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DOI: https://doi.org/10.1007/978-3-540-27824-5_172
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22571-3
Online ISBN: 978-3-540-27824-5
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