TY - GEN
T1 - Capacity of the Gaussian Arbitrarily-Varying Channel with List Decoding
AU - Hosseinigoki, Fatemeh
AU - Kosut, Oliver
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/15
Y1 - 2018/8/15
N2 - This paper considers list-decoding for the Gaussian arbitrarily-varying channel under the average probability of error criterion, where both the legitimate transmission and the state (or adversarial signal) are power limited. For list size L, the capacity is equivalent to the capacity of a standard Gaussian with the noise power raised by the adversary power, if the ratio of the adversary power to the transmitter power is less than L; otherwise, the capacity is zero. The converse proof involves showing that with enough power, an adversary can confuse the decoder by transmitting a superposition of several codewords while satisfying its power constraint with positive probability. The achievability proof uses a novel variant of the Csiszar-Narayan method for the arbitrarily-varying channel.
AB - This paper considers list-decoding for the Gaussian arbitrarily-varying channel under the average probability of error criterion, where both the legitimate transmission and the state (or adversarial signal) are power limited. For list size L, the capacity is equivalent to the capacity of a standard Gaussian with the noise power raised by the adversary power, if the ratio of the adversary power to the transmitter power is less than L; otherwise, the capacity is zero. The converse proof involves showing that with enough power, an adversary can confuse the decoder by transmitting a superposition of several codewords while satisfying its power constraint with positive probability. The achievability proof uses a novel variant of the Csiszar-Narayan method for the arbitrarily-varying channel.
KW - Capacity
KW - Gaussian arbitrarily-varying channel
KW - List-decoding
UR - http://www.scopus.com/inward/record.url?scp=85052475774&partnerID=8YFLogxK
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U2 - 10.1109/ISIT.2018.8437866
DO - 10.1109/ISIT.2018.8437866
M3 - Conference contribution
AN - SCOPUS:85052475774
SN - 9781538647806
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 471
EP - 475
BT - 2018 IEEE International Symposium on Information Theory, ISIT 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Symposium on Information Theory, ISIT 2018
Y2 - 17 June 2018 through 22 June 2018
ER -