A GHz-Wide Receiver for Sparse Spectra

Some major applications for this technology are found in real time spectrum monitoring, dynamic spectrum allocation, spectrum sensing, cognitive radio, and concurrent decoding of diverse signals (cellular, WiFi, Blue Tooth, etc.).  

Researchers

Dina Katabi / Haitham Al-Hassanieh / Omid Salehi-Abari / Ezzeldin Hamed / Lixin Shi

Departments: Dept of Electrical Engineering & Computer Science
Technology Areas: Communication Systems: Wireless / Computer Science: Networking & Signals
Impact Areas: Connected World

  • methods and apparatus for monitoring occupancy of wideband ghz spectrum and sensing and decoding respective frequency components of time-varying signa
    United States of America | Granted | 9,544,167

Technology

This technology allows the use of low cost commercially available transceiver components operating in a narrow bandwidth to generate a receiver with a bandwidth much wider than the sum of the components. The result is a wideband receiver at the cost structure of a narrowband WiFi receiver. The technology utilizes a new sparse FFT (sFFT) algorithm tailored for spectrum acquisition. The algorithm allows capturing and recovering a sparse signal using a significantly lower sampling rate than that dictated by the Nyquist criterion. Additionally, for non-sparse signals, the invention uses dynamic spectrum sensing to measure changes in the spectrum. This differential signal is sparse, and allows accurate spectrum sensing even for more highly occupied spectral regions.  

Problem Addressed

Monitoring and sensing a broadband spectrum (GHz) currently requires the use of either high speed ADCs and very long FFT with custom hardware that consumes significant power, or sequentially scanning one narrow band at a time that is slow and prone to missing short term signals.  

Advantages

  • GHz wide receiver at the cost structure of a narrowband WiFi receiver
  • Uses cheap, low-power, off-the-shelf hardware
  • Transceiver can sense a signal as well as decode it
  • Differential algorithm allows fast sensing even of a non-sparse spectrum
  • Low false positive and false negative rates even for non-sparse signals  

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