On Lossy Multi-Connectivity: Finite Blocklength Performance and Second-Order Asymptotics

We consider the lossy transmission of a single source over parallel additive white Gaussian noise channels with independent quasi-static fading, which we term the lossy multi-connectivity problem. We assume that only the decoder has access to the channel state information. Motivated by ultra-reliable and low latency communication requirements, we are interested in the finite blocklength performance of the problem, i.e., the minimal excess-distortion probability of transmitting $k$ source symbols over $n$ channel uses. By generalizing non-asymptotic bounds by Kostina and Verdú for the lossy joint source-channel coding problem, we derive non-asymptotic achievability and converse bounds for the lossy multi-connectivity problem. Using these non-asymptotic bounds and under mild conditions on the fading distribution, we derive approximations for the finite blocklength performance in the spirit of second-order asymptotics for any discrete memoryless source under an arbitrary bounded distortion measure. Furthermore, in the achievability part, we analyze the performance of a universal coding scheme by modifying the universal joint source-channel coding scheme by Csiszár and using a generalized minimum distance decoder. Our results demonstrate that the asymptotic notions of outage probability and outage capacity are in fact reasonable criteria even in the finite blocklength regime. Finally, we illustrate our results via numerical examples.

[1]  Vincent Yan Fu Tan,et al.  Second-Order Coding Rates for Channels With State , 2014, IEEE Transactions on Information Theory.

[2]  A. C. Berry The accuracy of the Gaussian approximation to the sum of independent variates , 1941 .

[3]  Vincent Y. F. Tan,et al.  Unequal Message Protection: Asymptotic and Non-Asymptotic Tradeoffs , 2014, IEEE Transactions on Information Theory.

[4]  Mehul Motani,et al.  Second-Order and Moderate Deviations Asymptotics for Successive Refinement , 2016, IEEE Transactions on Information Theory.

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

[6]  Thomas H. Cormen,et al.  Introduction to algorithms [2nd ed.] , 2001 .

[7]  Katalin Marton,et al.  Error exponent for source coding with a fidelity criterion , 1974, IEEE Trans. Inf. Theory.

[8]  Masahito Hayashi,et al.  Information Spectrum Approach to Second-Order Coding Rate in Channel Coding , 2008, IEEE Transactions on Information Theory.

[9]  Aaron D. Wyner,et al.  Coding Theorems for a Discrete Source With a Fidelity CriterionInstitute of Radio Engineers, International Convention Record, vol. 7, 1959. , 1993 .

[10]  Sergio Verdú,et al.  Scalar coherent fading channel: Dispersion analysis , 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

[11]  Mehul Motani,et al.  On the Finite Blocklength Performance of Lossy Multi-Connectivity , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[12]  Gregory W. Wornell,et al.  Source-channel diversity for parallel channels , 2004, IEEE Transactions on Information Theory.

[13]  Wei Yang,et al.  Fading Channels: Capacity and Channel Coding Rate in the Finite-Blocklength Regime , 2015 .

[14]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[15]  Amos Lapidoth,et al.  Nearest neighbor decoding for additive non-Gaussian noise channels , 1996, IEEE Trans. Inf. Theory.

[16]  Mehul Motani,et al.  The Dispersion of Mismatched Joint Source-Channel Coding for Arbitrary Sources and Additive Channels , 2017, IEEE Transactions on Information Theory.

[17]  Yuval Kochman,et al.  The dispersion of joint source-channel coding , 2011, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[18]  Sergio Verdú,et al.  A new converse in rate-distortion theory , 2012, 2012 46th Annual Conference on Information Sciences and Systems (CISS).

[19]  Shunsuke Ihara Error Exponent for Coding of Memoryless Gaussian Sources with a Fidelity Criterion , 2000 .

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

[21]  Sergio Verdú,et al.  Lossy Joint Source-Channel Coding in the Finite Blocklength Regime , 2012, IEEE Transactions on Information Theory.

[22]  Tsachy Weissman,et al.  Strong Successive Refinability and Rate-Distortion-Complexity Tradeoff , 2015, IEEE Transactions on Information Theory.

[23]  Meir Feder,et al.  On the Diversity-Multiplexing Tradeoff of Unconstrained Multiple-Access Channels , 2015, IEEE Transactions on Information Theory.

[24]  J. Nicholas Laneman,et al.  On the second-order coding rate of non-ergodic fading channels , 2013, 2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[25]  Vincent Y. F. Tan,et al.  The third-order term in the normal approximation for the AWGN channel , 2014, 2014 IEEE International Symposium on Information Theory.

[26]  Stark C. Draper,et al.  The Streaming-DMT of Fading Channels , 2013, IEEE Transactions on Information Theory.

[27]  H. Vincent Poor,et al.  Channel Coding Rate in the Finite Blocklength Regime , 2010, IEEE Transactions on Information Theory.

[28]  Gerhard Fettweis,et al.  How Reliable and Capable is Multi-Connectivity? , 2017, IEEE Transactions on Communications.

[29]  Sergio Verdú,et al.  Fixed-Length Lossy Compression in the Finite Blocklength Regime , 2011, IEEE Transactions on Information Theory.

[30]  Lizhong Zheng,et al.  Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels , 2003, IEEE Trans. Inf. Theory.

[31]  Vincent Yan Fu Tan,et al.  Asymptotic Estimates in Information Theory with Non-Vanishing Error Probabilities , 2014, Found. Trends Commun. Inf. Theory.

[32]  Cheng Chang,et al.  Joint source-channel with side information coding error exponents , 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[33]  Ebrahim MolavianJazi,et al.  A Unified Approach to Gaussian Channels with Finite Blocklength , 2014 .

[34]  Mehul Motani,et al.  The Dispersion of Universal Joint Source-Channel Coding for Arbitrary Sources and Additive Channels , 2017, arXiv.org.

[35]  Giuseppe Durisi,et al.  Quasi-Static Multiple-Antenna Fading Channels at Finite Blocklength , 2013, IEEE Transactions on Information Theory.

[36]  Yuval Kochman,et al.  The Dispersion of Lossy Source Coding , 2011, 2011 Data Compression Conference.