We consider the decoding of LDPC codes in presence of non-Gaussian noise, especially a set of E-mixture models. For each of these models, the optimal LLRs are presented. We study the performance degradation due to the use of incorrectLLR in presence of a given noise model. Without modifying the existing LDPC decoder, we propose robust initial LLR which require minimum knowledge about the underlying noise modeland are computationally less complex. Since BER simulations are computationally heavy, we use density evolution to compare the thresholds of different LLRs.

K. Giridhar

Department of Electrical Engineering

Density evolution

ITERATIVE DECODER

LDPC CODES

LDPC decoder

Mixture model

Noise models

Non-Gaussian noise

Performance degradation

Gaussian noise (electronic)

Information theory

Simulators

Decoding

Fulltext

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Robust initial LLRs for iterative decoders in presence of non-Gaussian noise

IEEE International Symposium on Information Theory - Proceedings

Interference alignment, as proposed in [1], is a joint multi-base-station precoding technique where each interfering base-station determines its precoder so as to obtain aligned interfering signals at each user. Determination of such precoders requires complete channel state information of all the interfering links to be present at all the base-stations. In this paper, we present a modified form of interference alignment based on locally-available channel state information at the user equipment. We consider the downlink of a wireless system where basestations and user equipments are equiped with two antennas each and scheduling of users is done based on Fractional Frequency Reuse. Assuming an MMSE receiver at the user equipment, an expression for the optimal precoder to be used by the interfering base-stations is derived so that there is zero interference after MMSE equalization. We also give an example for the case where there is uncancelled interference despite the use of these precoders. The effect of this uncancelled interference is overcome by the use of a robust LLR developed in [2]. Simulation results that demonstrate the performance of the proposed technique are presented. ©2010 IEEE.

Proceedings of 16th National Conference on Communications, NCC 2010

Robust LLR aided low feedback precoding for interference alignment

Robust initial llrs for iterative decoders in presence of non-gaussian noise

We look at the performance of turbo coded OFDM systems in the presence of narrowband interference (NBI) and co-channel interference (CCI). In systems employing standards such as the IEEE 802.16d/e, CCI behaves like NBI with the number of affected subcarriers ranging from 10% to 30%. Hence we treat symbol detection in such systems as detection in contaminated Gaussian (CG) noise and propose a robust log-likelihood ratio (LLR) computation for it. The proposed LLR computation method exploits the fact that NBI/CCI has a CG probability density function (pdf) but does not assume knowledge of the NBI power, NBI pdf and the fraction of subcarriers affected by NBI. Simulation results indicate that the proposed method performs very close to the optimal method which would have complete knowledge of the CG pdf parameters. ©2008 IEEE.

Journal	IEEE International Symposium on Information Theory - Proceedings
ISSN	21578102
Open Access	Yes