Paper Info
Title
Novel blind encoder identification of Reed-Solomon codes with low computational complexity
Abstract
Adaptive modulation and coding (AMC) is commonly used in wireless systems to dynamically change the modulation and coding schemes (MCSs) in subsequent frames such that the spectral efficiency can be adapted to various channel conditions. The spectrum and energy efficiency would decrease if the adopted MCS option at the transmitter needs to be dynamically transmitted to the receiver through a secure control channel. To combat this problem, in this paper, we would like to propose a novel blind channel-encoder identification scheme with low computational complexity for Reed-Solomon (RS) codes over Galois field GF(q), which could also be applied to other similar non-binary channel codes as well. Our proposed new scheme involves the estimation of the channel parameters using the expectation-maximization (EM) algorithm, the calculation of the log-likelihood ratio vectors (LLRVs) of the syndrome a posteriori probabilities over GF(q), and the identification of the non-binary RS encoder in use subject to the maximum average log-likelihood ratio (LLR) over the pre-selected candidate encoder set. Simulation results justify the effectiveness of this new mechanism.
Year
DOI
Venue
2013
10.1109/GLOCOM.2013.6831580
GLOBECOM
Keywords
Field
DocType
blind encoder identification,expectation-maximisation algorithm,reed solomon codes,expectation-maximization algorithm,reed-solomon codes,maximum average log-likelihood ratio,preselected candidate encoder set,galois field,log-likelihood ratio,expectation maximization,computational complexity,syndrome a posteriori probabilities,low computational complexity,adaptive modulation,channel-encoder identification scheme,amc,adaptive modulation and coding,probability,log-likelihood ratio vectors,transmitters,vectors,encoding,signal to noise ratio,modulation
Control channel,Link adaptation,Identification scheme,Computer science,Signal-to-noise ratio,Algorithm,Reed–Solomon error correction,Theoretical computer science,Real-time computing,Encoder,Spectral efficiency,Computational complexity theory
Conference
ISSN
Citations 
PageRank 
2334-0983
0
0.34
References 
Authors
6
3
Name
Order
Citations
PageRank
Hongting Zhang1204.06
Hsiao-chun Wu295997.99
Hong Jiang3516.30