4.7 Article

Downlink Energy Efficiency of Power Allocation and Wireless Backhaul Bandwidth Allocation in Heterogeneous Small Cell Networks

Journal

IEEE TRANSACTIONS ON COMMUNICATIONS
Volume 66, Issue 4, Pages 1705-1716

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2017.2763623

Keywords

Bandwidth allocation; energy efficiency; heterogeneous network; power allocation; small cell; wireless backhaul

Funding

  1. National Natural Science Foundation of China [61471025, 61771044]
  2. Young Elite Scientist Sponsorship Program by CAST [2016QNRC001]
  3. Research Foundation of Ministry of Education of China
  4. China Mobile [MCM2018-1-8]
  5. Beijing Municipal Natural Science Foundation [L172025]
  6. Fundamental Research Funds for the Central Universities [FRF-GF-17-A6]

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The widespread application of wireless services and dense devices access has triggered huge energy consumption. Because of the environmental and financial considerations, energy-efficient design in wireless networks has become an inevitable trend. To the best of our knowledge, energy-efficient orthogonal frequency division multiple access (OFDMA) heterogeneous small cell optimization comprehensively considering energy efficiency maximization, power allocation, wireless backhaul bandwidth allocation, and user quality of service is a novel approach and research direction, and it has not been investigated. In this paper, we study the energy-efficient power allocation and wireless backhaul bandwidth allocation in OFDMA heterogeneous small cell networks. Different from the existing resource allocation schemes that maximize the throughput, the studied scheme maximizes energy efficiency by allocating both transmit power of each small cell base station to users and bandwidth for backhauling, according to the channel state information and the circuit power consumption. The problem is first formulated as a non-convex nonlinear programming problem and then it is decomposed into two convex subproblems. A near optimal iterative resource allocation algorithm is designed to solve the resource allocation problem. A suboptimal low-complexity approach is also developed by exploring the inherent structure and property of the energy-efficient design. Simulation results demonstrate the effectiveness of the proposed algorithms by comparing with the existing schemes.

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