Capacity analysis of time-varying flat-fading channels using particle methods

We consider the problem of computing the information rate of a first-order approximation of Clarkepsilas time-varying flat-fading channel model, and apply the recently-developed particle-filter method for estimating the information rate of a continuous-valued channel with memory. We compare the results with various bounds, both classic and recent, and we find that the information rates obtained using the particle method fall between recently-established tight bounds. We also investigate the effects of the numbers of particles and of simulated time-steps on the estimated information rate. Such results are useful in providing an upper bound on the data rates achievable in a wireless communication system.

[1]  Parastoo Sadeghi,et al.  Optimizing Information Rate Bounds for Channels with Memory , 2007, 2007 IEEE International Symposium on Information Theory.

[2]  J.E. Mazo,et al.  Digital communications , 1985, Proceedings of the IEEE.

[3]  Justin Dauwels,et al.  Computation of Information Rates by Particle Methods , 2004, IEEE Transactions on Information Theory.

[4]  R. Clarke A statistical theory of mobile-radio reception , 1968 .

[5]  P. Rapajic,et al.  Capacity performance analysis of coherent detection in correlated fading channels using finite state Markov models , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.

[6]  Kareem E. Baddour,et al.  Autoregressive models for fading channel simulation , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[7]  Paul H. Siegel,et al.  On the achievable information rates of finite state ISI channels , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[8]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[9]  John Cocke,et al.  Optimal decoding of linear codes for minimizing symbol error rate (Corresp.) , 1974, IEEE Trans. Inf. Theory.

[10]  Parastoo Sadeghi Modelling, information capacity, and estimation of time-varying channels in mobile communication systems , 2006 .

[11]  Brendan J. Frey,et al.  Factor graphs and the sum-product algorithm , 2001, IEEE Trans. Inf. Theory.

[12]  G. Forney,et al.  Codes on graphs: normal realizations , 2000, 2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060).

[13]  Richard D. Wesel,et al.  Joint iterative channel estimation and decoding in flat correlated Rayleigh fading , 2001, IEEE J. Sel. Areas Commun..

[14]  Hans-Andrea Loeliger,et al.  Computation of Information Rates from Finite-State Source/Channel Models , 2002 .

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

[16]  Richard A. Davis,et al.  Time Series: Theory and Methods , 2013 .

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

[18]  Alexander M. Haimovich,et al.  Information rates of time varying Rayleigh fading channels , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[19]  G.D. Forney,et al.  Codes on graphs: Normal realizations , 2000, IEEE Trans. Inf. Theory.

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

[21]  V. Sharma,et al.  Entropy and channel capacity in the regenerative setup with applications to Markov channels , 2001, Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252).

[22]  Hans-Andrea Loeliger,et al.  On the information rate of binary-input channels with memory , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[23]  Upamanyu Madhow,et al.  On fixed input distributions for noncoherent communication over high-SNR Rayleigh-fading channels , 2004, IEEE Transactions on Information Theory.

[24]  Parastoo Sadeghi,et al.  Capacity analysis for finite-state Markov mapping of flat-fading channels , 2005, IEEE Transactions on Communications.

[25]  U. Grenander,et al.  Toeplitz Forms And Their Applications , 1958 .

[26]  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.