Uplink Resource Management in 5G: When a Distributed and Energy-Efficient Solution Meets Power and QoS Constraints

Massive multiple-input multiple-output (mMIMO) is emerging as a cornerstone technology for fifth-generation (5G) communications. It promises to scale up the performance of the conventional communication systems by growing the number of antennas at the base station side. This paper proposes a decentralized, scalable, and energy-efficient radio resource allocation method tailored for the uplink of the upcoming 5G air interface, based on the mMIMO physical layer. The proposed solution elaborates on a game-theoretical approach, which aims at maximizing the energy efficiency of mobile terminals, while guaranteeing the respect of average data rates and power consumptions constraints. This formulation leads to a low-complexity, iterative, and distributed algorithm, which considers (just to mention few relevant issues) the impact of channel time selectivity, delayed feedback from the base station, and physical-layer details of the selected communication technology. An extensive simulation campaign, considering a long-term evolution-advanced-based multicellular system based on mMIMO, is used to evaluate the benefits of the proposed technique. By calculating energy efficiency, user and peak data rates, spectral efficiency, outage probability, and other minor performance indexes, the reported results clearly demonstrate the performance gain that the designed solution offers with respect to baseline strategies.

• Record URL:
  https://doi.org/10.1109/TVT.2016.2627524
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00189545
• Supplemental Notes:
  • Copyright © 2017, IEEE.
• Authors:
  • Grassi, Alessandro
  • Piro, Giuseppe
  • Bacci, Giacomo
  • Boggia, Gennaro
• Publication Date: 2017-6

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 5176-5189
• Serial:
  • IEEE Transactions on Vehicular Technology
  • Volume: 66
  • Issue Number: 6
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 0018-9545
  • Serial URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=25

Subject/Index Terms

• TRT Terms: Algorithms; Antennas; Energy consumption; Game theory; Mobile communication systems; Quality of service; Radio links; Resource allocation; Telecommunications; Wireless communication systems
• Uncontrolled Terms: Multiple-input multiple-output systems (MIMO)
• Subject Areas: Data and Information Technology; Transportation (General);

Filing Info

• Accession Number: 01645016
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 22 2017 4:13PM