44,972 research outputs found
Feedback Enhances Simultaneous Wireless Information and Energy Transmission in Multiple Access Channels
In this report, the fundamental limits of simultaneous information and energy
transmission in the two-user Gaussian multiple access channel (G-MAC) with and
without feedback are fully characterized. More specifically, all the achievable
information and energy transmission rates (in bits per channel use and
energy-units per channel use, respectively) are identified. Furthermore, the
fundamental limits on the individual and sum- rates given a minimum energy rate
ensured at an energy harvester are also characterized. In the case without
feedback, an achievability scheme based on power-splitting and successive
interference cancellation is shown to be optimal. Alternatively, in the case
with feedback (G-MAC-F), a simple yet optimal achievability scheme based on
power-splitting and Ozarow's capacity achieving scheme is presented. Finally,
the energy transmission enhancement induced by the use of feedback is
quantified. Feedback can at most double the energy transmission rate at high
SNRs when the information transmission sum-rate is kept fixed at the
sum-capacity of the G-MAC, but it has no effect at very low SNRs.Comment: INRIA REPORT N{\deg}8804, accepted for publication in IEEE
transactions on Information Theory, March, 201
On the MISO Channel with Feedback: Can Infinitely Massive Antennas Achieve Infinite Capacity?
We consider communication over a multiple-input single-output (MISO) block
fading channel in the presence of an independent noiseless feedback link. We
assume that the transmitter and receiver have no prior knowledge of the channel
state realizations, but the transmitter and receiver can acquire the channel
state information (CSIT/CSIR) via downlink training and feedback. For this
channel, we show that increasing the number of transmit antennas to infinity
will not achieve an infinite capacity, for a finite channel coherence length
and a finite input constraint on the second or fourth moment. This insight
follows from our new capacity bounds that hold for any linear and nonlinear
coding strategies, and any channel training schemes. In addition to the channel
capacity bounds, we also provide a characterization on the beamforming gain
that is also known as array gain or power gain, at the regime with a large
number of antennas.Comment: This work has been submitted to the IEEE Transactions on Information
Theory. It was presented in part at ISIT201
Sharp convergence of nonlinear functionals of a class of Gaussian random fields
We present a self-contained proof of a uniform bound on multi-point
correlations of trigonometric functions of a class of Gaussian random fields.
It corresponds to a special case of the general situation considered in
[Hairer-Xu], but with improved estimates. As a consequence, we establish
convergence of a class of Gaussian fields composite with more general
functions. These bounds and convergences are useful ingredients to establish
weak universalities of several singular stochastic PDEs.Comment: 22 page
Role of scattering in virtual source array imaging
We consider imaging in a scattering medium where the illumination goes
through this medium but there is also an auxiliary, passive receiver array that
is near the object to be imaged. Instead of imaging with the source-receiver
array on the far side of the object we image with the data of the passive array
on the near side of the object. The imaging is done with travel time migration
using the cross correlations of the passive array data. We showed in [J.
Garnier and G. Papanicolaou, Inverse Problems {28} (2012), 075002] that if (i)
the source array is infinite, (ii) the scattering medium is modeled by either
an isotropic random medium in the paraxial regime or a randomly layered medium,
and (iii) the medium between the auxiliary array and the object to be imaged is
homogeneous, then imaging with cross correlations completely eliminates the
effects of the random medium. It is as if we imaged with an active array,
instead of a passive one, near the object. The purpose of this paper is to
analyze the resolution of the image when both the source array and the passive
receiver array are finite. We show with a detailed analysis that for isotropic
random media in the paraxial regime, imaging not only is not affected by the
inhomogeneities but the resolution can in fact be enhanced. This is because the
random medium can increase the diversity of the illumination. We also show
analytically that this will not happen in a randomly layered medium, and there
may be some loss of resolution in this case.Comment: 22 pages, 4 figure
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