Energy efficient OFDMA networks maintaining statistical QoS guarantees for delay-sensitive traffic

TL;DR

This paper proposes an energy-efficient resource allocation scheme for OFDMA networks that maintains statistical QoS guarantees for delay-sensitive traffic, using effective capacity and fractional programming techniques.

Contribution

It introduces a novel tradeoff analysis between effective energy-efficiency and effective capacity, and develops an iterative algorithm for optimal power allocation under QoS constraints.

Findings

The proposed scheme converges quickly within few iterations.

Optimal power allocation decays exponentially with circuitry power and QoS-exponent.

Power amplifier inefficiency affects energy efficiency linearly.

Abstract

An energy-efficient design is proposed under specific statistical quality-of-service (QoS) guarantees for delay-sensitive traffic in the downlink orthogonal frequency-division multiple-access (OFDMA) networks. This design is based on Wu's $\textit{effective capacity}$ (EC) concept [1], which characterizes the maximum throughput of a system subject to statistical delay-QoS requirements at the data-link layer. In the particular context considered, our main contributions consist of quantifying the $\textit{effective energy-efficiency}$ (EEE)-versus-EC tradeoff and characterizing the delay-sensitive traffic as a function of the QoS-exponent $\theta$, which expresses the exponential decay rate of the delay-QoS violation probabilities. Upon exploiting the properties of fractional programming, the originally quasi-concave EEE optimization problem having a fractional form is transformed into a subtractive optimization problem by applying Dinkelbach's method. As a result, an iterative inner-outer loop based resource allocation algorithm is conceived for efficiently solving the transformed EEE optimization problem. Our simulation results demonstrate that the proposed scheme converges within a few Dinkelbach algorithm's iterations to the desired solution accuracy. Furthermore, the impact of the circuitry power, of the QoS-exponent and of the power amplifier inefficiency is characterized numerically. These results reveal that the optimally allocated power maximizing the EEE decays exponentially with respect to both the circuitry power and the QoS-exponent, whilst decaying linearly with respect to the power amplifier inefficiency.