Abstract
We propose an improved method for designing unequal error protection (UEP) low-density parity-check (LDPC) codes. The method is based on density evolution. The degree distribution with the best UEP properties is found, under the constraint that the threshold should not exceed the threshold of a non-UEP code plus some threshold offset. For different codeword lengths and different construction algorithms, we search for good threshold offsets for the UEP code design. The choice of the threshold offset is based on the average a posteriori variable node mutual information. Simulations reveal the counter intuitive result that the short-to-medium length codes designed with a suitable threshold offset all outperform the corresponding non-UEP codes in terms of average bit-error rate. The proposed codes are also compared to other UEP-LDPC codes found in the literature.
Highlights
In many communication scenarios, such as wireless networks and transport of multimedia data, sufficient error protection is often a luxury
This paper focuses on the design of unequal error protection (UEP) low-density parity-check (LDPC) codes with improved average bit-error rate (BER)
We show that by searching among degree distributions designed for UEP with worse threshold than the corresponding nonUEP degree distributions, we may find degree distributions with significantly lower error rates for a finite length than the degree distributions with the best possible threshold
Summary
In many communication scenarios, such as wireless networks and transport of multimedia data, sufficient error protection is often a luxury. The irregular UEP-LDPC design schemes described in [1,2,3,4,5,6,7] are based on the irregularity of the variable and/or check node degree distributions. These schemes enhance the UEP properties of the code through density evolution methods. We consider the flexible UEP-LDPC code design proposed in [3], which is based on a hierarchical optimization of the variable node degree distribution for each protection class. We distinguish between code design, by which we mean the design of degree distributions that describe a code ensemble, and code construction, by which we mean the construction of a specific code realization (described by a parity-check matrix)
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