TY - JOUR
T1 - Compressive network coding for error control in wireless sensor networks
AU - Chen, Siguang
AU - Wu, Meng
AU - Wang, Kun
AU - Sun, Zhixin
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2014/10/17
Y1 - 2014/10/17
N2 - Since the observed signals of nearby sensors are known to be correlated, this paper firstly investigates the connection between network coding and compression concept of compressed sensing and then makes an in-depth combination between these two powerful concepts for error control in wireless sensor networks. Thus, a joint scheme is developed to achieve the maximum gain by exploiting the temporal and spatial correlations simultaneously. This scheme overcomes drawbacks of network coding theory by injecting the corresponding distributed compressed sensing concept into network coding, i.e., the scheme possesses good compression gain and graceful degradation of precision in the reconstruction process. Meanwhile, it can tolerate finite erasures and errors as well as reconstruct the original information as precise as possible when the rank of error matrix (induced by erasures and errors) doesn’t exceed the upper boundary. Finally, the reliability analysis and numeric results show that the compressive network coding scheme (i.e., the joint scheme) outperforms the conventional network coding scheme in robustness and performance. © 2014, Springer Science+Business Media New York.
AB - Since the observed signals of nearby sensors are known to be correlated, this paper firstly investigates the connection between network coding and compression concept of compressed sensing and then makes an in-depth combination between these two powerful concepts for error control in wireless sensor networks. Thus, a joint scheme is developed to achieve the maximum gain by exploiting the temporal and spatial correlations simultaneously. This scheme overcomes drawbacks of network coding theory by injecting the corresponding distributed compressed sensing concept into network coding, i.e., the scheme possesses good compression gain and graceful degradation of precision in the reconstruction process. Meanwhile, it can tolerate finite erasures and errors as well as reconstruct the original information as precise as possible when the rank of error matrix (induced by erasures and errors) doesn’t exceed the upper boundary. Finally, the reliability analysis and numeric results show that the compressive network coding scheme (i.e., the joint scheme) outperforms the conventional network coding scheme in robustness and performance. © 2014, Springer Science+Business Media New York.
KW - Compressed sensing
KW - Error control
KW - Network coding
KW - Wireless sensor networks
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U2 - 10.1007/s11276-014-0764-4
DO - 10.1007/s11276-014-0764-4
M3 - RGC 21 - Publication in refereed journal
SN - 1022-0038
VL - 20
SP - 2605
EP - 2615
JO - Wireless Networks
JF - Wireless Networks
IS - 8
ER -