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In this paper, we propose a linear complexity encoding method for arbitrary LDPC codes. We start from a simple graph-based encoding method Â¿label-and-decide.Â¿ We prove that the Â¿label-and-decideÂ¿ method is applicable to Tanner graphs with a hierarchical structure-pseudo-trees-and that the resulting encoding complexity is linear with the code block length. Next, we define a second type of Tanner graphs-the encoding stopping set. The encoding stopping set is encoded in linear complexity by a revised label-and-decide algorithm-the Â¿label-decide-recompute.Â¿ Finally, we prove that any Tanner graph can be partitioned into encoding stopping sets and pseudo-trees. By encoding each encoding stopping set or pseudo-tree sequentially, we develop a linear complexity encoding method for general low-density parity-check (LDPC) codes where the encoding complexity is proved to be less than 4 Â·M Â·((kÂ¿- 1), where M is the number of independent rows in the parity-check matrix and kÂ¿ represents the mean row weight of the parity-check matrix.