Reconfigurable Digital Channelizer Design Using Factored Markov Decision Processes

TL;DR

This paper introduces a new reconfigurable digital channelizer design using Markov Decision Processes, enabling dynamic adaptation to changing environments and optimizing multiple performance goals.

Contribution

It presents a novel system-level modeling approach combined with MDP techniques for optimizing reconfigurable digital channelizers in stochastic environments.

Findings

Demonstrates robustness of the proposed method through extensive simulations.

Shows improved adaptation compared to previous state-of-the-art approaches.

Provides a systematic framework for dynamic reconfiguration in digital channelizers.

Abstract

In this work, a novel digital channelizer design is developed through the use of a compact, system-level modeling approach. The model efficiently captures key properties of a digital channelizer system and its time-varying operation. The model applies powerful Markov Decision Process (MDP) techniques in new ways for design optimization of reconfigurable channelization processing. The result is a promising methodology for design and implementation of digital channelizers that adapt dynamically to changing use cases and stochastic environments while optimizing simultaneously for multiple conflicting performance goals. The method is used to employ an MDP to generate a runtime reconfiguration policy for a time-varying environment. Through extensive simulations, the robustness of the adaptation is demonstrated in comparison with the prior state of the art.