115 research outputs found
The First and Second Order Asymptotics of Covert Communication over AWGN Channels
This paper investigates the asymptotics of the maximal throughput of
communication over AWGN channels by channel uses under a covert constraint
in terms of an upper bound of Kullback-Leibler divergence (KL
divergence). It is shown that the first and second order asymptotics of the
maximal throughput are and
, respectively.
The technique we use in the achievability is quasi--neighborhood
notion from information geometry. We prove that if the generating distribution
of the codebook is close to Dirac measure in the weak sense, then the
corresponding output distribution at the adversary satisfies covert constraint
in terms of most common divergences. This helps link the local differential
geometry of the distribution of noise with covert constraint. For the converse,
the optimality of Gaussian distribution for minimizing KL divergence under
second order moment constraint is extended from dimension to dimension .
It helps to establish the upper bound on the average power of the code to
satisfy the covert constraint, which further leads to the direct converse bound
in terms of covert metric
Perfectly Covert Communication with a Reflective Panel
This work considers the problem of \emph{perfect} covert communication in
wireless networks. Specifically, harnessing an Intelligent Reflecting Surface
(IRS), we turn our attention to schemes that allow the transmitter to
completely hide the communication, with \emph{zero energy} at the unwanted
listener (Willie) and hence zero probability of detection. Applications of such
schemes go beyond simple covertness, as we prevent detectability or decoding
even when the codebook, timings, and channel characteristics are known to
Willie. We define perfect covertness, give a necessary and sufficient condition
for it in IRS-assisted communication, and define the optimization problem. For
two IRS elements, we analyze the probability of finding a solution and derive
its closed form. We then investigate the problem of more than two IRS elements
by analyzing the probability of such a zero-detection solution. We prove that
this probability converges to as the number of elements tends to infinity.
We provide an iterative algorithm to find a perfectly covert solution and prove
its convergence. The results are also supported by simulations, showing that a
small amount of IRS elements allows for a positive rate at the legitimate user
yet with zero probability of detection at an unwanted listener.Comment: 30 pages, 5 figure
Finite Blocklength Analysis of Gaussian Random coding in AWGN Channels under Covert constraints II: A Viewpoint of Total Variation Distance
Covert communication over an additive white Gaussian noise (AWGN) channel
with finite block length is investigated in this paper. The attention is on the
covert criterion, which has not been considered in finite block length
circumstance. As an accurate quantity metric of discrimination, the variation
distance with given finite block length n and signal-noise ratio (snr) is
obtained. We give both its analytic solution and expansions which can be easily
evaluated. It is shown that K-L distance, which is frequently adopted as the
metric of discrimination at the adversary in asymptotic regime, is not
convincing in finite block length regime compared with the total variation
distance. Moreover, the convergence rate of the total variation with different
snr is analyzed when the block length tends to infinity. The results will be
very helpful for understanding the behavior of the total variation distance and
practical covert communication
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