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We discuss error floor asympotics and present a method for improving theperformance of low-density parity check (LDPC) codes in the high SNR (errorfloor) region.  The method is based on Tanner graph covers that do not have trapping setsfrom the original code. The advantages of the method are that it is universal,as it can be applied to any LDPC code/channel/decoding algorithm and itimproves performance at the expense of increasing the code length, withoutlosing the code regularity, without changing the decoding algorithm, and, undercertain conditions, without lowering the code rate. The proposed method can bemodified to construct convolutional LDPC codes also.  The method is illustrated by modifying Tanner, MacKay and Margulis codes toimprove performance on the binary symmetric channel (BSC) under the Gallager Bdecoding algorithm. Decoding results on AWGN channel are also presented toillustrate that optimizing codes for one channel/decoding algorithm can lead toperformance improvement on other channels.

Eliminating Trapping Sets in Low-Density Parity Check Codes by using Tanner Graph Covers