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Efficient Sparse Signal Transmission over a Lossy Link Using Compressive Sensing.

Liantao Wu1, Kai Yu2, Dongyu Cao3

  • 1State Key Laboratory of Industrial Control Technology, Zhejiang University, Zheda Road 38th, Hangzhou 310027, China. wuliantao@zju.edu.cn.

Sensors (Basel, Switzerland)
|August 20, 2015
PubMed
Summary
This summary is machine-generated.

Compressive sensing (CS) enables efficient sparse signal transmission over lossy links by reconstructing data from packet loss, outperforming traditional methods in accuracy and energy efficiency.

Keywords:
compressive sensinglossy wireless linkpacket length controlsparse signal transmission

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Area of Science:

  • Signal Processing
  • Information Theory
  • Communication Systems

Background:

  • Data transmission over lossy links incurs high costs due to error protection overheads.
  • Sparse signals possess inherent structures that can be exploited for efficient transmission.

Purpose of the Study:

  • To investigate the application of compressive sensing (CS) for efficient sparse signal transmission over lossy communication links.
  • To evaluate CS performance without traditional data compression or error protection.

Main Methods:

  • Modeling natural packet loss as a random sampling process.
  • Utilizing CS-based reconstruction at the receiver.
  • Incorporating interleaving to mitigate burst data loss.
  • Analyzing the impact of packet lengths on transmission efficiency.

Main Results:

  • CS enables signal reconstruction from lossy transmissions.
  • Packet length significantly impacts transmission efficiency under various channel conditions.
  • Interleaving effectively reduces the impact of burst data loss.
  • CS demonstrated superior accuracy and reduced energy consumption compared to Automatic Repeat Request (ARQ) interpolation.

Conclusions:

  • Compressive sensing offers an efficient alternative for transmitting sparse signals over lossy links.
  • Optimizing packet length is crucial for maximizing transmission efficiency.
  • CS-based methods provide significant advantages over traditional ARQ techniques in terms of accuracy and energy savings.