Sign Up to like & get
recommendations!
1
Published in 2017 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2016.2630707
Abstract: This paper is about deriving lower bounds on the error exponents for the two-user interference channel under the random coding regime for several ensembles. Specifically, we first analyze the standard random coding ensemble, where the…
read more here.
Keywords:
exponents two;
error exponents;
random coding;
interference ... See more keywords
Sign Up to like & get
recommendations!
1
Published in 2019 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2018.2875541
Abstract: We analyze a class of vector multiple access channels with additive noise, where the sum of the dimensions of the transmitted signals matches that of the received signal. We first focus on the case without…
read more here.
Keywords:
vector multiple;
error exponents;
multiple access;
error ... See more keywords
Sign Up to like & get
recommendations!
1
Published in 2020 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2019.2942624
Abstract: In continuation to an earlier work, where error exponents of typical random codes were studied in the context of general block coding, with no underlying structure, here we carry out a parallel study on typical…
read more here.
Keywords:
error exponents;
exponents typical;
error;
typical random ... See more keywords
Sign Up to like & get
recommendations!
1
Published in 2021 at "Entropy"
DOI: 10.3390/e23020253
Abstract: This paper deals with the specific construction of binary low-density parity-check (LDPC) codes. We derive lower bounds on the error exponents for these codes transmitted over the memoryless binary symmetric channel (BSC) for both the…
read more here.
Keywords:
low complexity;
error exponents;
complexity decoding;
ldpc codes ... See more keywords
Sign Up to like & get
recommendations!
1
Published in 2022 at "Entropy"
DOI: 10.3390/e24050635
Abstract: We consider a binary classification problem for a test sequence to determine from which source the sequence is generated. The system classifies the test sequence based on empirically observed (training) sequences obtained from unknown sources…
read more here.
Keywords:
error;
source;
binary classification;
error exponents ... See more keywords