Stochastic learning algorithms for adaptive modulation

TitleStochastic learning algorithms for adaptive modulation
Publication TypeConference Paper
Year of Publication2005
AuthorsMisra, A., V. Krishnamurthy, and S. Schober
Conference NameSignal Processing Advances in Wireless Communications, 2005 IEEE 6th Workshop on
Pagination756 - 760
Date Publishedjun.
Keywordsadaptive codes, adaptive modulation, adaptive modulation-coding system, approximation theory, error correction codes, error correction coding, learning (artificial intelligence), learning algorithm, modulation coding, modulation constellation, perturbation stochastic approximation, perturbation techniques, radiocommunication, wireless communications system

Adaptive modulation has been widely studied as a means of increasing the capacity of wireless communications systems. In this paper, we present stochastic learning algorithms for the design of next-generation adaptive modulation systems. In the past, the design of adaptive modulation systems has relied on analytic and functional approximation approaches. We present a stochastic optimization algorithm for the design of adaptive modulation and coding systems. Specifically we use simultaneous perturbation stochastic approximation to adapt the parameters of the adaptive modulation system to achieve higher performance. This technique can be applied independently of channel model, error correction coding, and modulation constellation options. We show the effectiveness of this technique and discuss directions of future improvement.


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