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In general, LDPC codes are classified into two categories based on their construction methods: algebraic methods and graphical methods. LDPC codes constructed based on finite geometries and finite fields are classified as algebraic LDPC codes, such as the cyclic and quasi-cyclic LDPC codes presented into .
Cyclic codes form an important subclass of linear block codes. These codes are attractive for two reasons: first, encoding and syndrome computation can be implemented easily by using simple shift-registers with linear feedback connections, namely, linear feedback shift-registers (LFSRs); and second, because they have considerable inherent algebraic structure, it is possible to devise various practical algorithms for decoding them. Cyclic codes have been widely used in communication and storage systems for error control. They are particularly efficient for error detection.
Finite fields have been applied to construct error-correcting codes for reliable information transmission and data storage [–] since the late 1950s. These codes are commonly called algebraic codes, which have nice structures and large minimum distances. The most well-known classical algebraic codes are BCH and RS codes presented inandwhich can be decoded with the elegant hard-decision Berlekamp–Massey iterative algorithm.
Polar codes, discovered by Arikan [] in 2009, form a class of codes which provably achieve the capacity for a wide range of channels. Construction, encoding, and decoding of these codes are based on the phenomenon of channel polarization. In this chapter, we introduce polar codes from an algebraic point of view.