11 research outputs found
Sensing-Assisted Receivers for Resilient-By-Design 6G MU-MIMO Uplink
We address the resilience of future 6G MIMO communications by considering an
uplink scenario where multiple legitimate transmitters try to communicate with
a base station in the presence of an adversarial jammer. The jammer possesses
full knowledge about the system and the physical parameters of the legitimate
link, while the base station only knows the UL-channels and the
angle-of-arrival (AoA) of the jamming signals. Furthermore, the legitimate
transmitters are oblivious to the fact that jamming takes place, thus the
burden of guaranteeing resilience falls on the receiver. For this case we
derive one optimal jamming strategy that aims to minimize the rate of the
strongest user and multiple receive strategies, one based on a lower bound on
the achievable signal-to-interference-to-noise-ratio (SINR), one based on a
zero-forcing (ZF) design, and one based on a minimum SINR constraint. Numerical
studies show that the proposed anti-jamming approaches ensure that the sum rate
of the system is much higher than without protection, even when the jammer has
considerably more transmit power and even if the jamming signals come from the
same direction as those of the legitimate users.Comment: Accepted to 3rd IEEE International Symposium on Joint Communications
& Sensin
On the Need of Analog Signals and Systems for Digital-Twin Representations
We consider the task of converting different digital descriptions of analog
bandlimited signals and systems into each other, with a rigorous application of
mathematical computability theory. Albeit very fundamental, the problem appears
in the scope of digital twinning, an emerging concept in the field of digital
processing of analog information that is regularly mentioned as one of the key
enablers for next-generation cyber-physical systems and their areas of
application. In this context, we prove that essential quantities such as the
peak-to-average power ratio and the bounded-input/bounded-output norm, which
determine the behavior of the real-world analog system, cannot generally be
determined from the system's digital twin, depending on which of the
above-mentioned descriptions is chosen. As a main result, we characterize the
algorithmic strength of Shannon's sampling type representation as digital twin
implementation and also introduce a new digital twin implementation of analog
signals and systems. We show there exist two digital descriptions, both of
which uniquely characterize a certain analog system, such that one description
can be algorithmically converted into the other, but not vice versa
A Digital Twinning Platform for Integrated Sensing, Communications and Robotics
In this paper, a digital twinning framework for indoor integrated sensing,
communications, and robotics is proposed, designed, and implemented. Besides
leveraging powerful robotics and ray-tracing technologies, the framework also
enables integration with real-world sensors and reactive updates triggered by
changes in the environment. The framework is designed with commercial,
off-the-shelf components in mind, thus facilitating experimentation in the
different areas of communication, sensing, and robotics. Experimental results
showcase the feasibility and accuracy of indoor localization using digital
twins and validate our implementation both qualitatively and quantitatively.Comment: accepted to the 4th IEEE Joint Communications & Sensing Hybrid
Symposium, 19-21 March 2024, Leuven, Belgiu
Trustworthy Digital Representations of Analog Information—An Application-Guided Analysis of a Fundamental Theoretical Problem in Digital Twinning
This article compares two methods of algorithmically processing bandlimited time-continuous signals in light of the general problem of finding “suitable” representations of analog information on digital hardware. Albeit abstract, we argue that this problem is fundamental in digital twinning, a signal-processing paradigm the upcoming 6G communication-technology standard relies on heavily. Using computable analysis, we formalize a general framework of machine-readable descriptions for representing analytic objects on Turing machines. Subsequently, we apply this framework to sampling and interpolation theory, providing a thoroughly formalized method for digitally processing the information carried by bandlimited analog signals. We investigate discrete-time descriptions, which form the implicit quasi-standard in digital signal processing, and establish continuous-time descriptions that take the signal’s continuous-time behavior into account. Motivated by an exemplary application of digital twinning, we analyze a textbook model of digital communication systems accordingly. We show that technologically fundamental properties, such as a signal’s (Banach-space) norm, can be computed from continuous-time, but not from discrete-time descriptions of the signal. Given the high trustworthiness requirements within 6G, e.g., employed software must satisfy assessment criteria in a provable manner, we conclude that the problem of “trustworthy” digital representations of analog information is indeed essential to near-future information technology