On Real-Time Status Updates over Symbol Erasure Channels

As sensing, control, and actuation become further integrated into modern communication infrastructures, special consideration must be given to the type of traffic generated by associated devices. Real-time decision making relies on the availability of accurate data and, as such, delivering status updates in a timely fashion is of paramount importance. The topics of real-time status updates and low- delay communications have received much attention in recent years. Within this context, this article presents new results by looking at the interplay between average timeliness and design decisions made at the physical layer for unreliable communication channels. This study focuses on the natural tension between the protection afforded by additional redundancy and the decoding delay associated with longer codewords. The average timeliness is adopted as a performance criterion, and a framework to efficiently compute the performance of various transmission schemes for the binary erasure channel is developed. The problem formulation precludes the use of asymptotically long codewords typical of information theory. Yet, the presence of limited feedback does not seem to boost performance in the present context. Rather, having accurate channel estimates is key in minimizing average timeliness. Numerical examples are included in this article to further illustrate the applicability of the findings.

[1]  Rüdiger L. Urbanke,et al.  Modern Coding Theory , 2008 .

[2]  Brendan J. Frey,et al.  Rateless Coding for Arbitrary Channel Mixtures With Decoder Channel State Information , 2009, IEEE Transactions on Information Theory.

[3]  Santhosh Kumar,et al.  First-Passage Time and Large-Deviation Analysis for Erasure Channels With Memory , 2013, IEEE Transactions on Information Theory.

[4]  Roy D. Yates,et al.  Lazy is timely: Status updates by an energy harvesting source , 2015, 2015 IEEE International Symposium on Information Theory (ISIT).

[5]  Alexander Barg,et al.  Random codes: Minimum distances and error exponents , 2002, IEEE Trans. Inf. Theory.

[6]  Eytan Modiano,et al.  Optimizing age-of-information in a multi-class queueing system , 2015, 2015 IEEE International Symposium on Information Theory (ISIT).

[7]  Anthony Ephremides,et al.  Effect of Message Transmission Path Diversity on Status Age , 2016, IEEE Transactions on Information Theory.

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

[9]  Roy D. Yates,et al.  Real-time status: How often should one update? , 2012, 2012 Proceedings IEEE INFOCOM.

[10]  Qing He,et al.  Optimizing freshness of information: On minimum age link scheduling in wireless systems , 2016, 2016 14th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[11]  Anthony Ephremides,et al.  Age of information with a packet deadline , 2016, 2016 IEEE International Symposium on Information Theory (ISIT).

[12]  Abbas El Gamal,et al.  An efficient feedback coding scheme with low error probability for discrete memoryless channels , 2013, 2014 IEEE International Symposium on Information Theory.

[13]  Richard D. Wesel,et al.  Variable-Length Convolutional Coding for Short Blocklengths With Decision Feedback , 2014, IEEE Transactions on Communications.

[14]  Rajai Nasser,et al.  Age of information: The gamma awakening , 2016, 2016 IEEE International Symposium on Information Theory (ISIT).

[15]  Anthony Ephremides,et al.  Age of information under random updates , 2013, 2013 IEEE International Symposium on Information Theory.

[16]  Kun Chen,et al.  Age-of-information in the presence of error , 2016, 2016 IEEE International Symposium on Information Theory (ISIT).

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