Link performance enhancement for image transmission with FEC in Wireless Sensor Networks

Wireless Sensor Networks (WSN) is formerly created to support text-based data communication. However, by improving link level mechanism of WSN with Error Control Codng (ECC), reliable multimedia transmission could be realized. This paper addresses the performance issue of transferring multimedia dat...

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Main Authors: Yap, D.F.W., Tiong, S.K., Koh, J., Andito, D.P., Lim, K.C., Yeo, W.K.
Format: Article
Language:en_US
Published: 2017
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Institution: Universiti Tenaga Nasional
Language: en_US
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spelling my.uniten.dspace-58072018-01-03T03:57:50Z Link performance enhancement for image transmission with FEC in Wireless Sensor Networks Yap, D.F.W. Tiong, S.K. Koh, J. Andito, D.P. Lim, K.C. Yeo, W.K. Wireless Sensor Networks (WSN) is formerly created to support text-based data communication. However, by improving link level mechanism of WSN with Error Control Codng (ECC), reliable multimedia transmission could be realized. This paper addresses the performance issue of transferring multimedia data, particularly still image data, using real sensor motes platform. An X-ray image is transferred from one mote to other mote in one hop scenario. Forward Error Correction (FEC) and interleaving technique are used to design the code that capable of handling both erasure and noise in the received packet. The results show that erasure code can effectively combat the effect of random noise in one packet despite its number as well as recover small quantity of lost packet. Fdermore, the scheme can increase the image PSNR (Peak Signal to Noise Ratio) up to 18.41 dB as compared to the uncoded counterpart © 2012 Asian Network for Scientific Information. 2017-12-08T07:26:20Z 2017-12-08T07:26:20Z 2012 Article 10.3923/jas.2012.1465.1473 en_US Journal of Applied Sciences Volume 12, Issue 14, 2012, Pages 1465-1473
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language en_US
description Wireless Sensor Networks (WSN) is formerly created to support text-based data communication. However, by improving link level mechanism of WSN with Error Control Codng (ECC), reliable multimedia transmission could be realized. This paper addresses the performance issue of transferring multimedia data, particularly still image data, using real sensor motes platform. An X-ray image is transferred from one mote to other mote in one hop scenario. Forward Error Correction (FEC) and interleaving technique are used to design the code that capable of handling both erasure and noise in the received packet. The results show that erasure code can effectively combat the effect of random noise in one packet despite its number as well as recover small quantity of lost packet. Fdermore, the scheme can increase the image PSNR (Peak Signal to Noise Ratio) up to 18.41 dB as compared to the uncoded counterpart © 2012 Asian Network for Scientific Information.
format Article
author Yap, D.F.W.
Tiong, S.K.
Koh, J.
Andito, D.P.
Lim, K.C.
Yeo, W.K.
spellingShingle Yap, D.F.W.
Tiong, S.K.
Koh, J.
Andito, D.P.
Lim, K.C.
Yeo, W.K.
Link performance enhancement for image transmission with FEC in Wireless Sensor Networks
author_facet Yap, D.F.W.
Tiong, S.K.
Koh, J.
Andito, D.P.
Lim, K.C.
Yeo, W.K.
author_sort Yap, D.F.W.
title Link performance enhancement for image transmission with FEC in Wireless Sensor Networks
title_short Link performance enhancement for image transmission with FEC in Wireless Sensor Networks
title_full Link performance enhancement for image transmission with FEC in Wireless Sensor Networks
title_fullStr Link performance enhancement for image transmission with FEC in Wireless Sensor Networks
title_full_unstemmed Link performance enhancement for image transmission with FEC in Wireless Sensor Networks
title_sort link performance enhancement for image transmission with fec in wireless sensor networks
publishDate 2017
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