Contact
Pfaffenwaldring 47
70569 Stuttgart
Germany
Subject
Channel Coding: Spatially Coupled LDPC Codes
Nowadays, block LDPC codes are widely used as forward error correction (FEC)
in several important standards such as the DVB-S2, the WiMAX and the IEEE 802.11n standard. LDPC
codes are usually decoded by the low-complexity belief-propagation algorithm (BP). In general this
decoder is very powerful and simple to construct for every arbitrary LDPC code. It allows to build
a soft-in/soft-out (SOSI) decoder with a highly parallel architecture. However, the practical codes
with respect to hardware complexity, number of decoding iterations and the finite-length
performance suffer from a gap between the BP performance and the maximum a posteriori (MAP)
performance, which results in a gap to the channel capacity.
Spatially coupled low-density parity-check (SC-LDPC) codes can achieve the
channel capacity under low-complexity belief propagation (BP) decoding, which means they reach the
MAP performance under low-complexity BP decoding. These codes usually show a very low error floor,
which makes them a promising candidate for modern communication standards. For practical finite
coupling lengths however, there is a non-negligible rate-loss because of termination effects.
In order to simulate such low error probabilities, we currently develop a simulation cluster based on graphic cards (GPU) and the Nvidia CUDA programming language. This setup allows to simulate an arbitrary LDPC code with bit error rates (BER) up to 10 -9 - 10 - 10 within a feasible period of time.
One goal of my research is to investigate and understand the effects of
spatial coupling and use this knowledge to design codes close to the capacity with very good
properties and a low decoding complexity.
Winter term 2015/2016: Exercises Modern Error Correction