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Energy-Efficient Power Allocation Over Nakagami-m Fading Channels Under Delay-Outage Constraints

Musavian, Leila and Le-Ngoc, Tho (2014) 'Energy-Efficient Power Allocation Over Nakagami-m Fading Channels Under Delay-Outage Constraints.' IEEE Transactions on Wireless Communications, 13 (8). pp. 4081-4091. ISSN 1536-1276

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This paper presents an energy-efficient power allocation strategy for Nakagami-m flat-fading channels with a delay-outage probability constraint. The operating input transmit power value is limited to Pmax The energy efficiency (EE), expressed in units of b/J/Hz, is represented as the ratio of the effective capacity to the sum of transmission power Pt and circuit power Pc. Since the EE-maximization objective function is quasi-concave, a unique global maximum exists. By using fractional programming, we develop an EE-optimal power allocation strategy that consists of two steps: 1) obtaining the power level Pun, at which the maximum EE can be achieved, and 2) distributing the power optimally based on the minimum of P max and Pun. We prove that while Pun monotonically increases with Pc, the maximum achievable EE is a monotonically decreasing function of Pc. The analysis further allows us to derive the EE of three important cases: non-fading channels, extremely stringent delay-limited systems, and systems with no delay constraints. Simulation results confirm analytical derivations and further show the effects of the circuit power, fading duration, and fading severeness on the achievable EE and effective capacity of a delay-limited fading channel. © 2002-2012 IEEE.

Item Type: Article
Uncontrolled Keywords: Energy efficiency; delay-outage probability constraint; effective capacity; fractional programming; Nakagami fading
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 14 Feb 2017 15:20
Last Modified: 23 Sep 2022 18:43

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