Title
Compressed error and erasure correcting codes via rank-metric codes in random network coding
Abstract
The error control of random network coding has recently received a lot of attention because its solution can increase robustness and reliability of data transmission. To achieve this, additional overhead is needed for error correction. In this paper, we design a compressed error and erasure correcting scheme to decrease the additional overhead of error correction. This scheme reduces the computation overhead dramatically by employing an efficient algorithm to detect and delete linearly dependent received packets in the destination node. It also simplifies the hardware operations when the scheme reduces the received matrix Y to form Ek(Y) instead of E(Y) in the decoding process. If at most r original packets get combined in k packets of one batch, the payload of one packet can increase from M − k to M − O(rlog qk) for the application of compressed code, where M is the packet length. In particular, the decoding complexity of compressed code is O(rm) operations in an extension field , which does not enhance the overall decoding complexity of the system. Finally, we also compare our scheme's performance with existing works. The numerical results and analyses illustrate the security and performance of our scheme. Copyright © 2011 John Wiley & Sons, Ltd.
Year
DOI
Venue
2012
10.1002/dac.1316
Int. J. Communication Systems
Keywords
Field
DocType
computation overhead,error correction,packet length,decoding complexity,error control,overall decoding complexity,k packet,rank-metric code,random network coding,additional overhead,decoding process,r original packet,decoding,security,network coding
Linear network coding,Concatenated error correction code,Computer science,Network packet,Algorithm,Error detection and correction,Robustness (computer science),Decoding methods,Erasure code,Erasure
Journal
Volume
Issue
ISSN
25
11
1074-5351
Citations 
PageRank 
References 
7
0.62
20
Authors
3
Name
Order
Citations
PageRank
Siguang Chen16312.91
Meng Wu2312.49
Weifeng Lu3224.78