Project outcome:

Topic by topic:

Problems currently covered by the project are as follows.
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  1. Signal acquisition
  2. Compressed-sensing driven methods for signal acquisition
     
    Related papers:      Frequency Selective Compressed Sensing
                                         The paper is available on arXiv

                                         Generation and Analysis of Constrained Random Sampling Patterns
                                         The paper is available on arXiv
     
    Related software:     PaTeS ,   RxCS

  3. Architecture of digital receivers.
  4. New architectures of compressed-sensing-based direct conversion receiver.
     
    Related paper:         Compressed Sensing Based Direct Conversion Receiver With Interference Reducing Sampling Strategy
                                          The paper is available on arXiv
     
    Related software:     RxCS

     

Publications:

  1. Frequency Selective Compressed Sensing       
    [preprint available on arXiv.org]

    The paper was submitted to a journal for possible publication.
    The reproducible research materials are available here

  2. Generation and Analysis of Constrained Random Sampling Patterns       
    [preprint available on arXiv.org]

    The paper was submitted to a journal for possible publication.

  3. Compressed Sensing Based Direct Conversion Receiver With Interference Reducing Sampling Strategy       
    [available on arXiv.org]

    IEEE International Conference on Sensing, Communications and Networking (SECON) 2014, Singapore, 30 June – 3rd July 2014.

 

Software:

  1. RxCS toolbox.     [on GitHub]   Python toolbox dedicated to simulate compressed sensing methods in radio receivers.
  2. PaTeS toolbox.   [on GitHub]   Python toolbox dedicated for random sampling pattern analysis and testing.
  3. melancholia.       [on GitHub]   Python module which prints a Numpy array to a file or a variable in a human-readable way.


Page last updated: 19th February 2015 (by Jacek)