New Technique for Improving Performance of LDPC Codes in the Presence of Trapping Sets

Esa Alghonaim, Aiman Helmi El-Maleh, Mohamed Adnan Landolsi

Trapping sets are considered the primary factor for degrading the performance of low-density parity-check (LDPC) codes in the error-floor region. The effect of trapping sets on the performance of an LDPC code becomes worse as the code size decreases. One approach to tackle this problem is to minimize trapping sets during LDPC code design. However, while trapping sets can be reduced, their complete elimination is infeasible due to the presence of cycles in the underlying LDPC code bipartite graph. In this work, we introduce a new technique based on trapping sets neutralization to minimize the negative effect of trapping sets under belief propagation (BP) decoding. Simulation results for random, progressive edge growth (PEG) and MacKay LDPC codes demonstrate the effectiveness of the proposed technique. The hardware cost of the proposed technique is also shown to be minimal.

Jing Sun, O.Y. Takeshita, Michael P. Fitz

Stefan Laendner, Thorsten Hehn, Olgica Milenković +1 more

Esa Alghonaim

Low Density Parity Check (LDPC) codes are considered to be one of the best classes of error-correcting codes. This thesis deals with two major issues in LDPC codes: decoder design to enhance error correction performance and efficient decoder implementation. Five techniques have been introduced in this thesis. First, an efficient platform for LDPC code design and performance evaluation is developed. This platform implements parallel simulation algorithms to efficiently evaluate the performance of the proposed algorithms for LDPC decoders and code design. Second, an innovative technique is introduced to improve the performance of LDPC decoding in the error-floor region. Special structures in the code graph, called trapping sets, are considered to be the major source of decoding errors in the error-floor region. The proposed technique is based on eliminating the negative effect of trapping sets during LDPC decoding. As a third contribution, a novel approach to improve the decoder performance and/or throughput is introduced. This approach is based on utilizing LDPC decoder idle times by introducing two queues: one at the decoder input and the other at the decoder output. This architecture enables the decoder to run extra iterations beyond the conventional maximum allowable iterations. The fourth proposed technique reduces the bit error rate of LDPC decoders. This technique is based on tracking the number of failed parity check equations in the intermediate decoding iterations, rather than only relying on the final decoder output (after reaching the maximum number of iterations). The last proposed technique deals with the construction of interconnect efficient fully-parallel LDPC codes with high error correction performance. Fully-parallel implementation is very hard due to the complexity of processing elements interconnections. The proposed technique is based on constructing LDPC codes with less complex interconnections and with low impact on the error correction performance. This goal is achieved by putting a constraint on the maximum connection length between any two processing elements.

Yu Yi, Hye Kyung Jang, Moon Ho Lee +1 more

S. Suresh Kumar, Manju Rajaram

Low-density parity-check with Length-compatible and low error floors (LDPC-LCLEF) on the binary symmetric channel is presented in this paper. These codes can support a wide range of lengths for a given rate and also the Tanner graphs are free of small trapping sets. This can be obtained by applying the schemes of shortening and puncturing to good LDPC codes and the trapping sets are selected using the trapping set ontology based on their relative harmfulness for the given decoding algorithm. The conventional approach does not guarantee to have a good performance as the degree distributions may be wildly varied. In this paper, a modified algorithm is presented to generate LDPC codes of a given rate with almost their degree distributions are same as the mother code degree distribution. Also the relative harmfulness for different trapping sets are evaluated and decoding failures of one trapping set in presence or absence of other trapping sets are analyzed. To facilitate this discussion, a new description of structured LDPC codes with arrays of permutation matrices as parity-check matrices is given. Numerical results show that the LDPC code constructed by this approach performed much better than the conventional approach.