Capacity and error probability in single-tone and multitone multiple access over an impulsive channel

Single-tone and multitone are two modulation methods which can combine multiple digital users over a single channel, and decode them independently, corresponding to time-division and frequency-division multiple access, respectively. When the channel noise is impulsive, its distribution at the receiver decision point, and therefore its effect on the users, depends strongly on the type of modulation. We quantify this effect using information theoretic measures: capacity and error-exponent, where the latter is represented by its cut-off rate parameter. For low to moderate impulse power, the cut-off rate associated with multitone is greater than the cut-off rate associated with single-tone-in contrast to the relation between the corresponding Shannon capacities. This leads to anomalous behavior of the error-versus-information-rate performance. We show that this behavior relates to the tendency toward Gaussianity of the noise after multitone demodulation. We also provide specific evaluation of this phenomena for advanced data transmission over the cable TV (hybrid fiber coax) channel.

[1]  Sergio VerdÂ,et al.  Fading Channels: InformationTheoretic and Communications Aspects , 2000 .

[2]  Amir Dembo,et al.  Information theoretic inequalities , 1991, IEEE Trans. Inf. Theory.

[3]  Imre Csiszár Generalized cutoff rates and Renyi's information measures , 1995, IEEE Trans. Inf. Theory.

[4]  J. Miller,et al.  The Detection of Signals in Impulsive Noise Modeled as a Mixture Process , 1976, IEEE Trans. Commun..

[5]  S. Shamai,et al.  Error probabilities for the block-fading Gaussian channel , 1995 .

[6]  Shlomo Shamai,et al.  Worst-case power-constrained noise for binary-input channels , 1992, IEEE Trans. Inf. Theory.

[7]  Andrew J. Viterbi,et al.  Principles of Digital Communication and Coding , 1979 .

[8]  Uri Erez,et al.  Error exponents of modulo-additive noise channels with side information at the transmitter , 2001, IEEE Trans. Inf. Theory.

[9]  Shlomo Shamai,et al.  Fading Channels: Information-Theoretic and Communication Aspects , 1998, IEEE Trans. Inf. Theory.

[10]  Hikmet Sari,et al.  Orthogonal frequency-division multiple access and its application to CATV networks , 1998, Eur. Trans. Telecommun..

[11]  R. Gallager Information Theory and Reliable Communication , 1968 .

[12]  J.A.C. Bingham,et al.  Multicarrier modulation for data transmission: an idea whose time has come , 1990, IEEE Communications Magazine.

[13]  L. F. Lind,et al.  EFFICIENT METHOD FOR MODELLING IMPULSE NOISE IN A COMMUNICATION SYSTEM , 1996 .

[14]  Shlomo Shamai,et al.  Error Exponents And Outage Probabilities For The Block-Fading Gaussian Channel , 1991, IEEE International Symposium on Personal, Indoor and Mobile Radio Communications..

[15]  Irving Kalet,et al.  The multitone channel , 1989, IEEE Trans. Commun..

[16]  John G. Proakis,et al.  Digital Communications , 1983 .

[17]  Wayne E. Stark,et al.  Channels with block interference , 1984, IEEE Trans. Inf. Theory.

[18]  Sergio Verdu,et al.  Multiuser Detection , 1998 .

[19]  A. Barron ENTROPY AND THE CENTRAL LIMIT THEOREM , 1986 .

[20]  Tricia J. Willink,et al.  Optimization and performance evaluation of multicarrier transmission , 1997, IEEE Trans. Inf. Theory.

[21]  Pravin Varaiya,et al.  Capacity of fading channels with channel side information , 1997, IEEE Trans. Inf. Theory.

[22]  Gregory W. Wornell Spread-response precoding for communication over fading channels , 1996, IEEE Trans. Inf. Theory.