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.

Highlights

  • MotivationsThe financial support of the National Council for Scientific and Technological Development (CNPq) of Brazil under Grants 202340/2011-2 and 303426/2009-8, of the Londrina State University (UEL) and the Paraná State Government, of the EPSRC projects EP/N004558/1 and EP/L018659/1, as well as of the European Research Council’s Advanced Fellow Grant under the Beam-Me-Up project is gratefully acknowledged

  • Since the average arrival rate is equal to the average departure/service rate when the queue is in its steady-state4, the effective capacity (EC) can be physically interpreted as the maximum throughput of a system whose queue is in its steady-state [28], subject to the constraints imposed on the queue length/buffer-overflow probability of

  • In order to observe the relationship between the EEE and the EC, we present Fig. 1 which illustrates the contour plot of the EEE surface with respect to the total transmission power of User 1 and 2 in Scenario 1 of Table II

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Summary

Motivations

The financial support of the National Council for Scientific and Technological Development (CNPq) of Brazil under Grants 202340/2011-2 and 303426/2009-8, of the Londrina State University (UEL) and the Paraná State Government, of the EPSRC projects EP/N004558/1 and EP/L018659/1, as well as of the European Research Council’s Advanced Fellow Grant under the Beam-Me-Up project is gratefully acknowledged. Conventional designs of wireless communication networks have been dominated by improving the attainable spectral efficiency (SE), which was achieved by degrading the. An important research challenge for sustainable future wireless communication systems has been how to achieve significantly higher throughput (bits/second), while simultaneously improving the energy-efficiency (EE). According to the Shannon-Hartley theorem [6], in a pointto-point signal link having a given bandwidth W and additive white Gaussian noise (AWGN) power spectral density (PSD). Of this link is logarithmically proportional to the transmit power P :. In order to achieve a desirable EE-SE tradeoff (EST), radio resources such as the available transmit power and bandwidth (e.g. the subcarriers in orthogonal frequency-division multipleaccess (OFDMA), which has been used in LTE-family of wireless standards), have to be appropriately allocated to

Related Works
Contributions of This Paper
PRELIMINARIES
EC of OFDMA Systems
FORMULATION OF THE DOWNLINK OFDMA EEE MAXIMIZATION PROBLEM
The Original EEE-Maximization Problem
Relaxations of the EEE-Optimal Design
Calculation of the EC for NLOS Rayleigh Fading Channels
AN ALGORITHM FOR SOLVING THE OFDMA EEE-MAXIMIZATION PROBLEM
Dinkelbach’s Method
Dinkelbach-Lagrange Dual Decomposition Algorithm
SIMULATIONS AND NUMERICAL RESULTS
CONCLUSIONS
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