2018
DOI: 10.1109/tit.2018.2817519
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Empirical and Strong Coordination via Soft Covering With Polar Codes

Abstract: We design polar codes for empirical coordination and strong coordination in two-node networks. Our constructions hinge on the fact that polar codes enable explicit low-complexity schemes for soft covering. We leverage this property to propose explicit and low-complexity coding schemes that achieve the capacity regions of both empirical coordination and strong coordination for sequences of actions taking value in an alphabet of prime cardinality. Our results improve previously known polar coding schemes, which … Show more

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Cited by 21 publications
(31 citation statements)
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References 46 publications
(106 reference statements)
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“…Perhaps surprisingly, we show that this is not the case and that codes may be designed for fixed channels; this is particularly convenient as it allows us to exploit families of channel capacity-and channel resolvability-achieving codes, such as polar codes [15], [17].…”
Section: A Setup For Mlc With Ppmmentioning
confidence: 96%
“…Perhaps surprisingly, we show that this is not the case and that codes may be designed for fixed channels; this is particularly convenient as it allows us to exploit families of channel capacity-and channel resolvability-achieving codes, such as polar codes [15], [17].…”
Section: A Setup For Mlc With Ppmmentioning
confidence: 96%
“…We note that polar codes have already been proposed for coordination in other settings: [19] proposes polar coding schemes for point-to-point empirical coordination with error free links and uniform actions, while [21] generalizes the polar coding scheme to the case of non uniform actions. Polar coding for strong point-to-point coordination has been presented in [20,37]. In [22] the authors construct a joint coordination-channel polar coding scheme for strong coordination of actions.…”
Section: Polar Coding Schemes For Strong Coordination With No Stamentioning
confidence: 99%
“…The metric introduced by Wyner in [6] was later called weak secrecy and is given as the normalized mutual information rate under the assumption of uniform distribution p M [60] [59]. The weak security metric criterion was strengthened to strong secrecy by subsequent improvement of Wyner's model in [48] and coincides with the mutual information also with uniform distribution p M [58, Appendix D-C] [61] and is given as…”
Section: B Proposed Wiretap Channel Model For the Finite-length Regimementioning
confidence: 99%