Tradeoff Analysis of Delay-Power-CSIT Quality of Dynamic BackPressure Algorithm for Energy Efficient OFDM Systems

TL;DR

This paper investigates the fundamental tradeoff between delay and power in OFDM systems using a dynamic backpressure algorithm, accounting for imperfect channel information and circuit power, and derives an asymptotic power-delay scaling law.

Contribution

It provides a novel analysis of the power-delay tradeoff under realistic conditions and derives an asymptotic power scaling law for the dynamic backpressure algorithm.

Findings

Power scales as P = O(Dexp(1/D)) at small delay regimes.

Imperfect CSIT and circuit power affect the power-delay tradeoff coefficients.

The analysis uses sample-path approach and renewal theory for delay decomposition.

Abstract

In this paper, we analyze the fundamental power-delay tradeoff in point-to-point OFDM systems under imperfect channel state information quality and non-ideal circuit power. We consider the dynamic back- pressure (DBP) algorithm, where the transmitter determines the rate and power control actions based on the instantaneous channel state information (CSIT) and the queue state information (QSI). We exploit a general fluid queue dynamics using a continuous time dynamic equation. Using the sample-path approach and renewal theory, we decompose the average delay in terms of multiple unfinished works along a sample path, and derive an upper bound on the average delay under the DBP power control, which is asymptotically accurate at small delay regime. We show that despite imperfect CSIT quality and non-ideal circuit power, the average power (P) of the DBP policy scales with delay (D) as P = O(Dexp(1/D)) at small delay regime. While the impacts of CSIT quality and circuit power appears as the coefficients of the scaling law, they may be significant in some operating regimes.