• DocumentCode
    77036
  • Title

    Sparse Signal Processing Concepts for Efficient 5G System Design

  • Author

    Wunder, Gerhard ; Boche, Holger ; Strohmer, Thomas ; Jung, Peter

  • Author_Institution
    Tech. Univ. Berlin, Berlin, Germany
  • Volume
    3
  • fYear
    2015
  • fDate
    2015
  • Firstpage
    195
  • Lastpage
    208
  • Abstract
    As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges, and what are the key drivers is part of intensive, ongoing discussions. Partly due to the advent of compressive sensing, methods that can optimally exploit sparsity in signals have received tremendous attention in recent years. In this paper, we will describe a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems. Signal sparsity and the associated rich collection of tools and algorithms will thus be a viable source for innovation in 5G wireless system design. We will also describe applications of this sparse signal processing paradigm in Multiple Input Multiple Output random access, cloud radio access networks, compressive channel-source network coding, and embedded security. We will also emphasize an important open problem that may arise in 5G system design, for which sparsity will potentially play a key role in their solution.
  • Keywords
    5G mobile communication; MIMO communication; combined source-channel coding; compressed sensing; network coding; radio access networks; random processes; 5G wireless system design; MIMO random access; cloud radio access networks; compressive channel-source network coding; compressive sensing; embedded security; multiple input multiple output; signal sparsity; sparse signal processing; 4G mobile communication; 5G mobile communication; Compressed sensing; Mobile communication; Network security; Signal processing; Sparse matrices; Wireless communication; Cloud Radio Acess Networks; Compressed Sensing; Compressed sensing; Massive Random Access; cloud radio acess networks; embedded security; massive random access; source coding;
  • fLanguage
    English
  • Journal_Title
    Access, IEEE
  • Publisher
    ieee
  • ISSN
    2169-3536
  • Type

    jour

  • DOI
    10.1109/ACCESS.2015.2407194
  • Filename
    7047686