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Low-Delay Joint Source-Channel Mappings for the Gaussian MAC
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
Queen's University, Kingston, ON, Canada.
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-7926-5081
2014 (English)In: IEEE Communications Letters, ISSN 1089-7798, Vol. 18, no 2, 249-252 p.Article in journal (Refereed) Published
Abstract [en]

The bivariate Gaussian multiterminal source coding problem with transmission over the Gaussian multiple-access channel is studied. We propose the use of low-delay joint source-channel mappings and show how performance saturation, which is unavoidable with linear transmission, can be overcome by optimizing the mappings. The optimized mappings are in general nonlinear and perform a combination of hard and soft decision signaling for the error-resilient transmission of analog data.

Place, publisher, year, edition, pages
2014. Vol. 18, no 2, 249-252 p.
Keyword [en]
Joint source-channel coding, low-delay transmission, multi-terminal source coding, Gaussian multiple-access channel, correlated sources, mean square error
National Category
URN: urn:nbn:se:kth:diva-33400DOI: 10.1109/LCOMM.2013.120413.132088ISI: 000332199300015ScopusID: 2-s2.0-84900667700OAI: diva2:415058
VinnovaSwedish Research Council

QC 20140404. Updated from submitted to published.

Available from: 2011-05-05 Created: 2011-05-05 Last updated: 2014-04-04Bibliographically approved
In thesis
1. Low-delay sensing and transmission
Open this publication in new window or tab >>Low-delay sensing and transmission
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis studies cooperative sensing and transmission in the context ofwireless sensor networks (WSNs). We especially focus on two means of cooperative sensing and transmission, namely, distributed source coding and relaying. We consider systems where the usefulness of the measured data is dependent on how old the data is and we therefore need low-delay transmission schemes. At first sight, the low-delay criterion may seem to be of little relevance, but it is this aspect in particular that distinguishes this thesis from many of the existing communication theoretic results, which often are asymptotic in the block lengths. The thesis is composed of an introductory part, discussing the fundamentals of communication theory and how these are related to the requirements of WSNs, followed by a part where the results of the thesis are reported in Papers A-H.

Papers A-D study different scenarios for distributed source-channel coding. In Paper A, we consider transmission of correlated continuous sources and propose an iterative algorithm for designing simple and energy-efficient sensor nodes. In particular the cases of the binary symmetric channel as well as the additive white Gaussian noise channel are studied. In Paper B, the work is extended to channels with interference and it is shown that also in this case there can be significant power savings by performing a joint optimization of the system.Papers C and D use a more structured approach and propose side-information-aware source-channel coding strategies using lattices and sinusoids.

In Paper E, we apply the methods we have used in joint source-channel coding to the famous Witsenhausen counterexample. By using a relatively simple iterative algorithm, we are able to demonstrate the best numerical performance known to date.

For the case of systems with relays, we study the transmission of a continuous Gaussian source and the transmission of an uniformly distributed discrete source. In both situations, we propose algorithms to design low-delay source-channel and relay mappings. By studying the structure of the optimized source-channel and relay mappings, we provide useful insights into how the optimized systems work. These results are reported in Papers F and G.

In Paper H, we finally consider sum-MSE minimization for the Gaussian multiple-input, multiple-output broadcast channel. By using recently discovered properties of this problem, we derive a closed-form expression for the optimal power allocation in the two-user scenario and propose a conceptually simple and efficient algorithm that handles an arbitrary number of users.

Throughout the thesis we show that there are significant gains if the parts of the system are jointly optimized for the source and channel statistics. All methods that are considered in this thesis yield very low coding and decoding delays. In general, nonlinear mappings outperform linear mappings for problems where there is side-information available. Another contribution of this thesis is visualization of numerically optimized systems that can be used as inspiration when structured low-delay systems are designed.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2011. xii, 30 p.
Trita-EE, ISSN 1653-5146 ; 2011:039
Cooperative communication, wireless sensor networks, low-delay transmission, joint source-channel coding, distributed source coding, estimation, quantization
National Category
urn:nbn:se:kth:diva-33404 (URN)978-91-7415-983-7 (ISBN)
Public defence
2011-05-26, Hörsal F3, Lindstedtsvägen 26, KTH, Stockholm, 13:15 (English)
ICT - The Next Generation
The author changed name from Johannes Karlsson to Johannes Kron in January 2011. QC 20110512Available from: 2011-05-12 Created: 2011-05-05 Last updated: 2011-10-30Bibliographically approved

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