High-SNR Capacity of Wireless Communication Channels in the Noncoherent Setting: A Primer

This paper, mostly tutorial in nature, deals with the problem of characterizing the capacity of fading channels in the high signal-to-noise ratio (SNR) regime. We focus on the practically relevant noncoherent setting, where neither transmitter nor receiver know the channel realizations, but both are aware of the channel law. We present, in an intuitive and accessible form, two tools, first proposed by Lapidoth & Moser (2003), of fundamental importance to high-SNR capacity analysis: the duality approach and the escape-to-infinity property of capacity-achieving distributions. Furthermore, we apply these tools to refine some of the results that appeared previously in the literature and to simplify the corresponding proofs.

[1]  Yuhong Yang Elements of Information Theory (2nd ed.). Thomas M. Cover and Joy A. Thomas , 2008 .

[2]  Yingbin Liang,et al.  Capacity of noncoherent time-selective Rayleigh-fading channels , 2004, IEEE Transactions on Information Theory.

[3]  Thomas L. Marzetta,et al.  Unitary space-time modulation for multiple-antenna communications in Rayleigh flat fading , 2000, IEEE Trans. Inf. Theory.

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

[5]  Philip Schniter,et al.  On the Spectral Efficiency of Noncoherent Doubly Selective Channels , 2006 .

[6]  Thomas Kailath,et al.  On the capacity of frequency- selective channels in training-based transmission schemes , 2004, IEEE Transactions on Signal Processing.

[7]  Amos Lapidoth,et al.  On the asymptotic capacity of stationary Gaussian fading channels , 2005, IEEE Transactions on Information Theory.

[8]  Philip Schniter,et al.  On the Spectral Efficiency of Noncoherent Doubly Selective Block-Fading Channels , 2010, IEEE Transactions on Information Theory.

[9]  Ibrahim C. Abou-Faycal,et al.  The capacity of discrete-time memoryless Rayleigh-fading channels , 2001, IEEE Trans. Inf. Theory.

[10]  Antonio Ruiz,et al.  Frequency domain data transmission using reduced computational complexity algorithms , 1980, ICASSP.

[11]  Helmut Bölcskei,et al.  The SIMO pre-log can be larger than the SISO pre-log , 2009, 2010 IEEE International Symposium on Information Theory.

[12]  W. Boothby An introduction to differentiable manifolds and Riemannian geometry , 1975 .

[13]  Amos Lapidoth,et al.  A Foundation In Digital Communication: Index , 2009 .

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

[15]  Thomas L. Marzetta,et al.  Capacity of a Mobile Multiple-Antenna Communication Link in Rayleigh Flat Fading , 1999, IEEE Trans. Inf. Theory.

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

[17]  Amos Lapidoth,et al.  The fading number of single-input multiple-output fading channels with memory , 2006, IEEE Transactions on Information Theory.

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

[19]  Brian M. Sadler,et al.  Pilot-assisted wireless transmissions: general model, design criteria, and signal processing , 2004, IEEE Signal Processing Magazine.

[20]  Brian M. Sadler,et al.  Pilot Assisted Wireless Transmissions † , 2004 .

[21]  Shlomo Shamai,et al.  Information Theory of Underspread WSSUS Channels , 2011 .

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

[23]  Imre Csiszár,et al.  Information Theory - Coding Theorems for Discrete Memoryless Systems, Second Edition , 2011 .