TY - GEN
T1 - Semiconstrained systems
AU - Elishco, Ohad
AU - Meyerovitch, Tom
AU - Schwartz, Moshe
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/28
Y1 - 2015/9/28
N2 - When transmitting information over a noisy channel, two approaches are common: assuming the channel errors are independent of the transmitted content and devising an error-correcting code, or assuming the errors are data dependent and devising a constrained-coding scheme that eliminates all offending data patterns. In this paper we analyze a middle road, which we call a semiconstrained system. In such a model, which is an extension of the channel with cost constraints, we do not eliminate the error-causing sequences entirely, but rather restrict the frequency in which they appear. We address several key issues in this study. The first is proving closed-form bounds on the capacity which allow us to bound the asymptotics of the capacity. In particular, we bound the rate at which the capacity of the semiconstrained (0, k)-RLL tends to 1 as k grows. The second key issue is devising efficient encoding and decoding procedures that asymptotically achieve capacity with vanishing error. Finally, we consider delicate issues involving the continuity of the capacity and a relaxation of the definition of semiconstrained systems.
AB - When transmitting information over a noisy channel, two approaches are common: assuming the channel errors are independent of the transmitted content and devising an error-correcting code, or assuming the errors are data dependent and devising a constrained-coding scheme that eliminates all offending data patterns. In this paper we analyze a middle road, which we call a semiconstrained system. In such a model, which is an extension of the channel with cost constraints, we do not eliminate the error-causing sequences entirely, but rather restrict the frequency in which they appear. We address several key issues in this study. The first is proving closed-form bounds on the capacity which allow us to bound the asymptotics of the capacity. In particular, we bound the rate at which the capacity of the semiconstrained (0, k)-RLL tends to 1 as k grows. The second key issue is devising efficient encoding and decoding procedures that asymptotically achieve capacity with vanishing error. Finally, we consider delicate issues involving the continuity of the capacity and a relaxation of the definition of semiconstrained systems.
UR - http://www.scopus.com/inward/record.url?scp=84969869937&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2015.7282454
DO - 10.1109/ISIT.2015.7282454
M3 - Conference contribution
AN - SCOPUS:84969869937
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 246
EP - 250
BT - Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015
PB - Institute of Electrical and Electronics Engineers
T2 - IEEE International Symposium on Information Theory, ISIT 2015
Y2 - 14 June 2015 through 19 June 2015
ER -