Related papers: Improve Positioning Accuracy in WCDMA/FDD Networks…
Mobile network operators constantly optimize their networks to ensure superior service quality and coverage. This optimization is crucial for maintaining an optimal user experience and requires extensive data collection and analysis. One of…
Six-dimensional movable antenna (6DMA) is an emerging technology that is able to fully exploit the spatial variation of wireless channels by controlling the 3D positions and 3D rotations of distributed antennas/antenna surfaces at the…
In a visible light positioning (VLP) system, a receiver can estimate its location based on signals transmitted by light emitting diodes (LEDs). In this manuscript, we investigate a quasi-synchronous VLP system, in which the LED transmitters…
With the development of high speed trains (HST) in many countries, providing broadband wireless services in HSTs is becoming crucial. Orthogonal frequency-division multiplexing (OFDM) has been widely adopted for broadband wireless…
In this paper, we take a new approach for time of arrival geo-localization. We show that the main sources of error in metropolitan areas are due to environmental imperfections that bias our solutions, and that we can rely on a probabilistic…
Distributed multi-antenna systems are an important enabling technology for future intelligent transportation systems (ITS), showing promising performance in vehicular communications and near-field (NF) localization applications. This work…
Only the chairs can edit This paper investigates the fundamental limits of target position estimation accuracy of joint sensing and communication (JSC) networks comprising several monostatic base stations (BSs) that cooperate to localize…
We design a receiver assembling several photomultipliers (PMTs) as an array to increase the field of view (FOV) of the receiver and adapt to multiuser situation over None-line-of-sight (NLOS) ultraviolet (UV) channels. Channel estimation…
This paper focuses on assessing the limitations in the direction-finding process of radio sources with directional antennas in an urbanized environment, demonstrating how signal source antenna parameters, such as beamwidth and maximum…
Motivated by future automotive applications, we study the joint target detection and parameter estimation problem using orthogonal time frequency space (OTFS), a digital modulation format robust to time-frequency selective channels.…
Deep learning methods require massive of annotated data for optimizing parameters. For example, datasets attached with accurate bounding box annotations are essential for modern object detection tasks. However, labeling with such pixel-wise…
Accurate channel estimation in massive multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems is challenging when the number of pilot symbols is much smaller than the number of transmit antennas.…
Orthogonal Time Frequency Space (OTFS) modulation exploits the sparsity of Delay-Doppler domain channels, making it highly effective in high-mobility scenarios. Its accurate channel estimation supports integrated sensing and communication…
User equipment (UE) positioning accuracy is of paramount importance in current and future communications standard. However, traditional methods tend to perform poorly in non line of sight (NLoS) scenarios. As a result, deep learning is a…
We revisit multi-agent asynchronous online optimization with delays, where only one of the agents becomes active for making the decision at each round, and the corresponding feedback is received by all the agents after unknown delays.…
Time difference of arrival (TDOA) is a widely used technique for localizing a radio transmitter from the difference in signal arrival times at multiple receivers. For TDOA to work, the individual receivers must estimate the respective…
We introduce a novel network-adaptive algorithm that is suitable for alleviating network packet losses for low-latency interactive communications between a source and a destination. Our network-adaptive algorithm estimates in real-time the…
Probabilistic collision detection (PCD) is essential in motion planning for robots operating in unstructured environments, where considering sensing uncertainty helps prevent damage. Existing PCD methods mainly used simplified geometric…
Electromagnetic wave interaction with time-varying systems has gained a lot of research interest in recent years. The temporal modulation gives unprecedented control over the response, allowing us to go beyond the state-of-the-art in…
Evolving 5G New Radio (NR) to support non-terrestrial networks (NTNs), particularly satellite communication networks, is under exploration in 3GPP. The movement of the spaceborne platforms in NTNs may result in large timing varying Doppler…