Distributive Power Control Algorithm for Multicarrier Interference Network over Time-Varying Fading Channels - Tracking Performance Analysis and Optimization
Yong Cheng, Vincent K. N. Lau

TL;DR
This paper analyzes the convergence and tracking performance of a distributed power control algorithm in multicarrier interference networks with time-varying channels, proposing optimizations for better accuracy and implementation.
Contribution
It introduces a novel analysis of the DSGPA under FSMC channels, deriving optimal scaling matrices for improved tracking error performance.
Findings
DSGPA converges to a limit region, not a point.
Tracking errors decrease with increasing average sojourn time.
Proposed method outperforms baseline schemes.
Abstract
Distributed power control over interference limited network has received an increasing intensity of interest over the past few years. Distributed solutions (like the iterative water-filling, gradient projection, etc.) have been intensively investigated under \emph{quasi-static} channels. However, as such distributed solutions involve iterative updating and explicit message passing, it is unrealistic to assume that the wireless channel remains unchanged during the iterations. Unfortunately, the behavior of those distributed solutions under \emph{time-varying} channels is in general unknown. In this paper, we shall investigate the distributed scaled gradient projection algorithm (DSGPA) in a pairs multicarrier interference network under a finite-state Markov channel (FSMC) model. We shall analyze the \emph{convergence property} as well as \emph{tracking performance} of the proposed…
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