Title :
Variable-Word-Length Coding for Energy-Aware Signal Transmission
Author :
Kadrolkar, Abhijit ; Gao, Robert X. ; Yan, Ruqiang ; Gong, Weibo
Author_Institution :
Dept. of Mech. & Ind. Eng., Univ. of Massachusetts Amherst, Amherst, MA, USA
fDate :
4/1/2012 12:00:00 AM
Abstract :
This paper presents an energy-efficient method for data transmission through improved data compression. This is achieved by a new signal source coding method based on the Walsh transform. This research is motivated by the need for extended service life of wireless sensor networks, where individual sensor nodes are energy constrained. Theoretical background is introduced, and its effectiveness is established through simulations and experiments. The simulations are conducted using electrocardiogram (ECG) and bearing vibration signals, and the results are comparatively evaluated against the Haar transform coding, discrete cosine transform (DCT) coding, pulse code modulation, and fixed-word-length Walsh coding. Experimental verification is performed by implementing the algorithm on a wireless test bed. Results indicate that up to 58% energy reduction can be achieved for wireless transmission of ECG signals, as compared to other commonly used coding methods. For bearing vibration signal transmission, the energy consumed during transmission is comparable to that of the near-optimal DCT coding.
Keywords :
Haar transforms; Walsh functions; biomedical communication; data compression; discrete cosine transforms; electrocardiography; pulse code modulation; transform coding; variable length codes; wireless sensor networks; ECG signal wireless transmission; Haar transform coding; Walsh transform; bearing vibration signals; data compression; data transmission; discrete cosine transform coding; electrocardiogram; energy reduction; energy-aware signal transmission; energy-efficient method; fixed-word-length Walsh coding; of wireless sensor networks; pulse code modulation; sensor nodes; signal source coding method; variable-word-length coding; vibration signal transmission; Approximation methods; Data communication; Discrete cosine transforms; Encoding; Wireless communication; Wireless sensor networks; Data compression; Walsh transform; energy-aware signal transmission; wireless sensor networks;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2011.2176229