5 research outputs found
Design of LDPC Code Ensembles with Fast Convergence Properties
The design of low-density parity-check (LDPC) code ensembles optimized for a
finite number of decoder iterations is investigated. Our approach employs EXIT
chart analysis and differential evolution to design such ensembles for the
binary erasure channel and additive white Gaussian noise channel. The error
rates of codes optimized for various numbers of decoder iterations are compared
and it is seen that in the cases considered, the best performance for a given
number of decoder iterations is achieved by codes which are optimized for this
particular number. The design of generalized LDPC (GLDPC) codes is also
considered, showing that these structures can offer better performance than
LDPC codes for low-iteration-number designs. Finally, it is illustrated that
LDPC codes which are optimized for a small number of iterations exhibit
significant deviations in terms of degree distribution and weight enumerators
with respect to LDPC codes returned by more conventional design tools.Comment: 6 pages, 5 figures, Submitted to the 3rd International Black Sea
Conference on Communications and Networking (IEEE BlackSeaCom 2015
Optimizing the Decoding Complexity of PEG-Based Methods with an Improved Hybrid Iterative/Gaussian Elimination Decoding Algorithm
This paper focuses on optimizing the decoding complexity of the progressive-edge-growth-based (PEG-based) method for the extended grouping of radio frequency identification (RFID) tags using a hybrid iterative/Gaussian elimination decoding algorithm. To further reduce the decoding time, the hybrid decoding is improved by including an early stopping criterion to avoid unnecessary iterations of iterative decoding for undecodable blocks. Various simulations have been carried out to analyse and assess the performance achieved with the PEG-based method under the improved hybrid decoding, both in terms of missing recovery capabilities and decoding complexities. Simulation results are presented, demonstrating that the improved hybrid decoding achieves the optimal missing recovery capabilities of full Gaussian elimination decoding at a lower complexity, as some of the missing tag identifiers are recovered iteratively