Stochastic Learning Algorithms for Adaptive Modulation

TitleStochastic Learning Algorithms for Adaptive Modulation
Publication TypeConference Paper
Year of Publication2006
AuthorsMisra, A., V. Krishnamurthy, and R. Schober
Conference NameAcoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
PaginationIV -IV
Date Publishedmay.
Keywordsadaptive modulation, error correction codes, error correction coding, fading channels, flat fading channels, learning (artificial intelligence), learning based feedback control optimization, reenforcement learning algorithms, stochastic learning algorithms, stochastic systems, telecommunication computing, wireless communications devices

In this paper we present re-enforcement learning algorithms for adaptive modulation in flat fading channels for reconfigurable, agile wireless communications devices. We derive the dynamical stochastic control model, convexity properties of the stated optimization problem, learning based feedback control optimization and numerical simulations of the designed system. We show how this technique can be applied independently of channel model, error correction coding, and modulation constellation options. In addition, we demonstrate the algorithm's learning and tracking capabilities


a place of mind, The University of British Columbia

Electrical and Computer Engineering
2332 Main Mall
Vancouver, BC Canada V6T 1Z4
Tel +1.604.822.2872
Fax +1.604.822.5949

Emergency Procedures | Accessibility | Contact UBC | © Copyright 2021 The University of British Columbia