Paper Info
Title
A Framework for Design and Implementation of Adaptive Digital Predistortion Systems
Abstract
Digital predistortion (DPD) has important applications in wireless communication for smart systems, such as, for example, in Internet of Things (IoT) applications for smart cities. DPD is used in wireless communication transmitters to counteract distortions that arise from nonlinearities, such as those related to amplifier characteristics and local oscillator leakage. In this paper, we propose an algorithm-architecture-integrated framework for design and implementation of adaptive DPD systems. The proposed framework provides energy-efficient, real-time DPD performance, and enables efficient reconfiguration of DPD architectures so that communication can be dynamically optimized based on time-varying communication requirements. Our adaptive DPD design framework applies Markov Decision Processes (MDPs) in novel ways to generate optimized runtime control policies for DPD systems. We present a GPU-based adaptive DPD system that is derived using our design framework, and demonstrate its efficiency through extensive experiments.
Year
DOI
Venue
2019
10.1109/AICAS.2019.8771476
2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)
Keywords
Field
DocType
Smart systems,dataflow modeling,digital predistortion,Markov decision processes
Computer architecture,Smart system,Wireless,Computer science,Internet of Things,Markov decision process,Local oscillator,Predistortion,Control reconfiguration,Amplifier
Conference
ISBN
Citations 
PageRank 
978-1-5386-7885-5
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Lin Li132.08
Peter Deaville200.34
Adrian E. Sapio311.70
Lauri Anttila474561.19
Mikko Valkama51567175.51
Marilyn Wolf611431.09
Shuvra S. Bhattacharyya71416162.67