Energy-efficient resource allocation for heterogeneous services in OFDMA downlink networks: Systematic perspective

Quansheng Xu, Xi Li, Hong Ji, Xiaojiang Du

Research output: Contribution to journalArticlepeer-review

71 Scopus citations

Abstract

In the area of energy-efficient (EE) resource allocation, only limited work has been done on consideration of both transmitter and receiver energy consumption. In this paper, we propose a novel EE resource-allocation scheme for orthogonal frequency-division multiple-access (OFDMA) networks, where both transmitter energy consumption and receiver energy consumption are considered. In addition, different quality-of-service (QoS) requirements, including minimum-rate guarantee service and best effort service, are taken into account. The time slot, subcarrier (frequency), and power-allocation policies are jointly considered to optimize system EE. With all these considerations, the EE resource-allocation problem is formulated as a mixed combinatorial and nonconvex optimization problem, which is extremely difficult to solve. To reduce the computational complexity, we tackle this problem in three steps. First, for a given power allocation, we obtain the time-frequency resource unit (RU) allocation policy via binary quantum-behaved particle swarm optimization (BQPSO) algorithm. Second, under the assumption of known RU allocation, we transform the original optimization problem into an equivalent concave optimization problem and obtain the optimal power-allocation policy through the Lagrange dual approach. Third, an iteration algorithm is developed to obtain the joint time-frequency power-resource-allocation strategy. We validate the convergence and effectiveness of the proposed scheme by extensive simulations.

Original languageEnglish
Article number6774977
Pages (from-to)2071-2082
Number of pages12
JournalIEEE Transactions on Vehicular Technology
Volume63
Issue number5
DOIs
StatePublished - Jun 2014

Keywords

  • Energy efficiency (EE)
  • heterogeneous service
  • mixed combinatorial and nonconvex optimization
  • orthogonal frequency-division multiple-access (OFDMA) network
  • resource allocation

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