Spectral estimation for long-term evolution transceivers using low-complex filter banks

Thomas Schlechter, Christoph Juritsch, Mario Huemer

Research output: Contribution to journalArticlepeer-review

Abstract

For mobile user equipments (UEs), a careful power management is essential. Despite this fact, quite an amount of energy is wasted in today's UEs’ analogue (AFEs) and digital frontends (DFEs). These are engineered for extracting the wanted signal from a spectral environment defined in the corresponding communication standards with their extremely tough requirements. These requirements define a worst-case scenario still ensuring reliable communication. In a typical receiving process the actual requirements can be considered as less critical. Knowledge about the actual environmental spectral conditions allows to reconfigure both frontends to the actual needs and to save energy. In this paper, the authors present a highly efficient generic spectrum sensing approach, which allows to collect information about the actual spectral environment of an UE. This information can be used to reconfigure both the AFE and DFE, thus endowing them with increased intelligence. A low-complex multiplier free filter bank extended by an efficient power calculation unit will be introduced. They also present simulation results, which illustrate the performance of the spectrum sensing approach and a complexity comparison with different well-known implementations is given. Furthermore, estimates on the chip area and power consumption based on a 65 nm CMOS technology database are provided, considering the Smarti4G chip as a reference.
Original languageEnglish
Pages (from-to)265-274
JournalIET - The Journal of Engineering
Volume2014
Issue number6
DOIs
Publication statusPublished - May 2014

Keywords

  • channel bank filters
  • radio transceivers
  • telecommunication power management
  • Long Term Evolution
  • telecommunication network reliability
  • radio spectrum management
  • long-term evolution transceivers
  • communication reliability
  • spectrum sensing approach

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