Capacity of Time-Varying Channels With Causal Channel Side Information

We derive the capacity of time-varying channels with memory that have causal channel side information (CSI) at the sender and receiver. We obtain capacity of block-memoryless and asymptotically block-memoryless channels with block-memoryless or weakly decorrelating side information. Our coding theorems rely on causal generation of the codewords relative to the causal transmitter CSI. The CSI need not be perfect, and we consider the case where the transmitter and receiver have the same causal CSI as well as the case where the transmitter CSI is a deterministic function of the receiver CSI. For block-memoryless and asymptotically block-memoryless channels, our coding strategy averages mutual information density over multiple transmission blocks to achieve the maximum average mutual information. We apply the coding theorem associated with the block-memoryless channel to determine the capacity and optimal input distribution of intersymbol interference (ISI) time-varying channels with causal perfect CSI about the time-varying channel. The capacity of this channel cannot be found through traditional decomposition methods

[1]  R. Gray,et al.  Block coding for discrete stationary d -continuous noisy channels , 1979, IEEE Trans. Inf. Theory.

[2]  Robert M. Gray,et al.  On the asymptotic eigenvalue distribution of Toeplitz matrices , 1972, IEEE Trans. Inf. Theory.

[3]  Pravin Varaiya,et al.  Capacity, mutual information, and coding for finite-state Markov channels , 1996, IEEE Trans. Inf. Theory.

[4]  S. Shamai,et al.  The capacity of discrete-time Rayleigh fading channels , 1997, Proceedings of IEEE International Symposium on Information Theory.

[5]  Toby Berger,et al.  The capacity of finite-State Markov Channels With feedback , 2005, IEEE Transactions on Information Theory.

[6]  Imre Csiszár,et al.  The capacity of the arbitrarily varying channel revisited: Positivity, constraints , 1988, IEEE Trans. Inf. Theory.

[7]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[8]  Andrea J. Goldsmith,et al.  Capacity of Finite State Channels Based on Lyapunov Exponents of Random Matrices , 2006, IEEE Transactions on Information Theory.

[9]  M. Salehi Capacity and coding for memories with real-time noisy defect information at encoder and decoder , 1992 .

[10]  A. Wyner,et al.  Coding Theorem for Stationary, Asymptotically Memoryless, Continuous-time Channels , 1972 .

[11]  Feller William,et al.  An Introduction To Probability Theory And Its Applications , 1950 .

[12]  Andrea J. Goldsmith,et al.  Capacity and optimal resource allocation for fading broadcast channels - Part I: Ergodic capacity , 2001, IEEE Trans. Inf. Theory.

[13]  Jay Cheng,et al.  Capacity of Nakagami-q (Hoyt) fading channels with channel side information , 2003, International Conference on Communication Technology Proceedings, 2003. ICCT 2003..

[14]  Claude E. Shannon,et al.  Channels with Side Information at the Transmitter , 1958, IBM J. Res. Dev..

[15]  M. Medard,et al.  The issue of spreading in multipath time-varying channels , 1995, 1995 IEEE 45th Vehicular Technology Conference. Countdown to the Wireless Twenty-First Century.

[16]  Giuseppe Caire,et al.  Optimum power control over fading channels , 1999, IEEE Trans. Inf. Theory.

[17]  Lizhong Zheng,et al.  Communication on the Grassmann manifold: A geometric approach to the noncoherent multiple-antenna channel , 2002, IEEE Trans. Inf. Theory.

[18]  Ernst Pfaffelhuber,et al.  Channels with asymptotically decreasing memory and anticipation , 1971, IEEE Trans. Inf. Theory.

[19]  J. Wolfowitz Coding Theorems of Information Theory , 1962, Ergebnisse der Mathematik und Ihrer Grenzgebiete.

[20]  V. Kafedziski Capacity of frequency selective fading channels with side information , 1998, Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284).

[21]  Harish Viswanathan Capacity of Markov Channels with Receiver CSI and Delayed Feedback , 1999, IEEE Trans. Inf. Theory.

[22]  David L. Neuhoff,et al.  Channels with almost finite memory , 1979, IEEE Trans. Inf. Theory.

[23]  Shlomo Shamai,et al.  Multiuser capacity in block fading with no channel state information , 2002, IEEE Trans. Inf. Theory.

[24]  Andrea J. Goldsmith,et al.  Capacity of Finite-State Channels with Time-Invariant Deterministic Feedback , 2006, ISIT.

[25]  Toby Berger,et al.  Review of Information Theory: Coding Theorems for Discrete Memoryless Systems (Csiszár, I., and Körner, J.; 1981) , 1984, IEEE Trans. Inf. Theory.

[26]  Shlomo Shamai,et al.  On the capacity of some channels with channel state information , 1999, IEEE Trans. Inf. Theory.

[27]  Thomas Kailath,et al.  Sampling models for linear time-variant filters , 1959 .

[28]  James L. Massey,et al.  Capacity of the discrete-time Gaussian channel with intersymbol interference , 1988, IEEE Trans. Inf. Theory.

[29]  Shlomo Shamai,et al.  Fading channels: How perfect need "Perfect side information" be? , 2002, IEEE Trans. Inf. Theory.

[30]  R. Price,et al.  Statistical theory applied to communication through multipath disturbances. , 1953 .

[31]  Gregory J. Pottie,et al.  Fast adaptive equalization/diversity combining for time-varying dispersive channels , 1998, IEEE Trans. Commun..

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

[33]  Suhas N. Diggavi Analysis of multicarrier transmission in time-varying channels , 1997, Proceedings of ICC'97 - International Conference on Communications.

[34]  M. Medard A coding theorem for multiple-access decorrelating channels , 1998, Proceedings. 1998 IEEE International Symposium on Information Theory (Cat. No.98CH36252).

[35]  Andrea J. Goldsmith,et al.  Capacity limits of MIMO channels , 2003, IEEE J. Sel. Areas Commun..

[36]  A. Goldsmith,et al.  Capacity of Rayleigh fading channels under different adaptive transmission and diversity-combining techniques , 1999, IEEE Transactions on Vehicular Technology.

[37]  G. J. Foschini,et al.  The capacity of linear channels with additive Gaussian noise , 1970, Bell Syst. Tech. J..

[38]  Amos Lapidoth,et al.  The fading number and degrees of freedom in non-coherent MIMO fading channels: a peace pipe , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

[39]  Mikael Skoglund,et al.  On the capacity of a multiple-antenna communication link with channel side information , 2003, IEEE J. Sel. Areas Commun..

[40]  David Tse,et al.  Multiaccess Fading Channels-Part I: Polymatroid Structure, Optimal Resource Allocation and Throughput Capacities , 1998, IEEE Trans. Inf. Theory.

[41]  Amos Lapidoth,et al.  Capacity bounds via duality with applications to multiple-antenna systems on flat-fading channels , 2003, IEEE Trans. Inf. Theory.

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

[43]  Prakash Narayan,et al.  Capacities of time-varying multiple-access channels with side information , 2002, IEEE Trans. Inf. Theory.

[44]  Andrea J. Goldsmith,et al.  Variable-rate variable-power MQAM for fading channels , 1997, IEEE Trans. Commun..

[45]  Babak Hassibi,et al.  On the capacity of MIMO broadcast channels with partial side information , 2005, IEEE Transactions on Information Theory.

[46]  William Feller,et al.  An Introduction to Probability Theory and Its Applications , 1967 .

[47]  David L. Neuhoff,et al.  Indecomposable finite state channels and primative approximation , 1982, IEEE Trans. Inf. Theory.

[48]  David Tse,et al.  Degrees of freedom in underspread mimo fading channels , 2003, IEEE International Symposium on Information Theory, 2003. Proceedings..

[49]  Amiel Feinstein,et al.  Information and information stability of random variables and processes , 1964 .

[50]  G. Taricco,et al.  Capacity of fading channel with no side information , 1997 .

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

[52]  P. Bello Characterization of Randomly Time-Variant Linear Channels , 1963 .

[53]  Sergio Verdú,et al.  A general formula for channel capacity , 1994, IEEE Trans. Inf. Theory.

[54]  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..

[55]  Dennis Goeckel,et al.  Adaptive coding for time-varying channels using outdated fading estimates , 1999, IEEE Trans. Commun..

[56]  Imre Csiszár,et al.  Capacity of the Gaussian arbitrarily varying channel , 1991, IEEE Trans. Inf. Theory.

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

[58]  Muriel Médard,et al.  The effect upon channel capacity in wireless communications of perfect and imperfect knowledge of the channel , 2000, IEEE Trans. Inf. Theory.

[59]  Shlomo Shamai,et al.  Information theoretic considerations for cellular mobile radio , 1994 .

[60]  Steven W. McLaughlin,et al.  Capacity analysis for continuous alphabet channels with side information, part II: MIMO channels , 2004, IEEE Transactions on Information Theory.

[61]  R. Gray Entropy and Information Theory , 1990, Springer New York.

[62]  Muriel Médard The capacity of time varying multiple user channels in wireless communications , 1995 .

[63]  Israel Bar-David,et al.  Capacity and coding for the Gilbert-Elliot channels , 1989, IEEE Trans. Inf. Theory.

[64]  Hu Kuo Ting On the Information Stability of a Sequence of Channels , 1962 .