Title : 
Cycle analysis of time-invariant LDPC convolutional codes
         
        
            Author : 
Zhou, Hua ; Goertz, Norbert
         
        
            Author_Institution : 
Inst. of Commun. & Radio-Freq. Eng., Vienna Univ. of Technol., Vienna, Austria
         
        
        
        
        
        
            Abstract : 
Time-invariant low-density parity-check convolutional codes (LDPCccs) can be constructed from a polynomial form of a parity-check matrix that defines quasi-cyclic LDPC block codes based on circulant matrices. Based on this polynomial matrix, we discuss the relationships between the polynomial domain and the time domain parity-check and syndrome former matrices with respect to cycle properties. We present a novel, simple way to describe cycles in the polynomial version of the syndrome former matrix and we exploit this concept in a new cycle counting algorithm.
         
        
            Keywords : 
convolutional codes; parity check codes; circulant matrices; cycle analysis; cycle counting algorithm; parity-check matrix; polynomial domain; polynomial form; polynomial matrix; polynomial version; quasi-cyclic LDPC block codes; syndrome former matrices; syndrome former matrix; time domain parity-check; time-invariant LDPC convolutional codes; time-invariant low-density parity-check convolutional codes; Block codes; Carbon capture and storage; Convolutional codes; Decoding; Encoding; Equations; Galois fields; Parity check codes; Polynomials; Radio frequency;
         
        
        
        
            Conference_Titel : 
Telecommunications (ICT), 2010 IEEE 17th International Conference on
         
        
            Conference_Location : 
Doha
         
        
            Print_ISBN : 
978-1-4244-5246-0
         
        
            Electronic_ISBN : 
978-1-4244-5247-7
         
        
        
            DOI : 
10.1109/ICTEL.2010.5478744