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Found 14 papers, 1 papers with code
An Overview of Electromagnetic Illusions: Empowering Smart Environments with Reconfigurable Metasurfaces
This study delves into the innovative landscape of metasurfaces, with a particular focus on their role in achieving EM illusion (EMI) a facet of paramount significance.
Use of Parallel Explanatory Models to Enhance Transparency of Neural Network Configurations for Cell Degradation Detection
In a previous paper, we have shown that a recurrent neural network (RNN) can be used to detect cellular network radio signal degradations accurately.
On Chernoff Lower-Bound of Outage Threshold for Non-Central $χ^2$-Distributed Beamforming Gain in URLLC Systems
The cumulative distribution function (CDF) of a non-central $\chi^2$-distributed random variable (RV) is often used when measuring the outage probability of communication systems.
Near and Far Field Model Mismatch: Implications on 6G Communications, Localization, and Sensing
The upcoming 6G technology is expected to operate in near-field (NF) radiating conditions thanks to high-frequency and electrically large antenna arrays.
On Chernoff Lower-Bound of Outage Threshold for Non-Central $χ^2$-Distributed MIMO Beamforming Gain
The cumulative distribution function (CDF) of a non-central $\chi^2$-distributed random variable (RV) is often used when measuring the outage probability of communication systems.
Collaborative Learning with a Drone Orchestrator
For this system, the convergence rate of collaborative learning is derived while considering data heterogeneity, sensor noise levels, and communication errors, then, the drone trajectory that maximizes the final accuracy of the trained NN is obtained.
Sherman-Morrison Regularization for ELAA Iterative Linear Precoding
The design of iterative linear precoding is recently challenged by extremely large aperture array (ELAA) systems, where conventional preconditioning techniques could hardly improve the channel condition.
Age of Information in Federated Learning over Wireless Networks
In this paper, federated learning (FL) over wireless networks is investigated.
Constellation-Oriented Perturbation for Scalable-Complexity MIMO Nonlinear Precoding
The basic concept of COP is to apply vector perturbation (VP) in the constellation domain instead of symbol domain; as often used in conventional techniques.
Power Allocation for FDMA-URLLC Downlink with Random Channel Assignment
With imperfect CSIT, the proposed approach can still provide remarkable user capacity at limited cost of transmit-power efficiency.
Network-ELAA Beamforming and Coverage Analysis for eMBB/URLLC in Spatially Non-Stationary Rician Channels
Finally, it is shown that the network-ELAA can offer significant coverage extension (50% or more in most of cases) when comparing with the single-AP scenario.
Massive-MIMO MF Beamforming with or without Grouped STBC for Ultra-Reliable Single-Shot Transmission Using Aged CSIT
In addition, a combinatorial approach of the MF beamforming and grouped space-time block code (G-STBC) is proposed to further mitigate the detrimental impact of the CSIT uncertainty.
Towards Radio Designs with Non-Linear Processing for Next Generation Mobile Systems
We report gains that we have managed to verify, and we also discuss remaining challenges, missing algorithmic components and future research directions that would be required towards highly efficient, future mobile systems that can efficiently exploit the gains of non-linear, base-station processing.
Information Theory Signal Processing Information Theory
On Deep Learning Solutions for Joint Transmitter and Noncoherent Receiver Design in MU-MIMO Systems
Otherwise, it is called non-systematic waveform, where no artificial design is involved.
