A GHz-Wide Receiver for Sparse Spectra

Technology #16973

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Inventors
Professor Dina Katabi
Department of Electrical Engineering-Computer Science, MIT
External Link (www.csail.mit.edu)
Haitham Al-Hassaneih
Department of Electrical Engineering-Computer Science, MIT
Omid Salehi-Abari
Department of Electrical Engineering-Computer Science, MIT
Ezzeldin Hamed
Department of Electrical Engineering-Computer Science, MIT
Lixin Shi
Department of Electrical Engineering-Computer Science, MIT
Managed By
Daniel Dardani
MIT Technology Licensing Officer
Patent Protection

Methods and Apparatus for Monitoring Occupancy of Wideband GHz Spectrum and Sensing and Decoding Respective Frequency Components of Time Varying Signals

US Patent 9,544,167
Publications
GHz-Wide Sensing and Decoding Using the Sparse Fourier Transform
IEEE International Conference on Computer Communications , April 2014

Applications

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.).

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.

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.

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