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Found 13 papers, 1 papers with code
Multi-Objective Deep Reinforcement Learning for 5G Base Station Placement to Support Localisation for Future Sustainable Traffic
This work assumes a pre-deployed BS and another BS is required to be added to support both localisation accuracy and coverage rate in an urban city scenario.
Robust Snapshot Radio SLAM
The intrinsic geometric connections between millimeter-wave (mmWave) signals and the propagation environment can be leveraged for simultaneous localization and mapping (SLAM) in 5G and beyond networks.
Millimeter-wave Radio SLAM: End-to-End Processing Methods and Experimental Validation
In this article, we address the timely topic of cellular bistatic simultaneous localization and mapping (SLAM) with specific focus on complete processing solutions from raw I/Q samples to user equipment (UE) and landmark location information in millimeter-wave (mmWave) networks.
Joint RIS Calibration and Multi-User Positioning
Reconfigurable intelligent surfaces (RISs) are expected to be a key component enabling the mobile network evolution towards a flexible and intelligent 6G wireless platform.
MmWave Mapping and SLAM for 5G and Beyond
We distinguish the different types of sensing problems and then focus on mapping and SLAM as running examples.
Doppler Exploitation in Bistatic mmWave Radio SLAM
Networks in 5G and beyond utilize millimeter wave (mmWave) radio signals, large bandwidths, and large antenna arrays, which bring opportunities in jointly localizing the user equipment and mapping the propagation environment, termed as simultaneous localization and mapping (SLAM).
A CNN Approach for 5G mmWave Positioning Using Beamformed CSI Measurements
The CSI data of the signals from one Base Station (BS) is collected at the reference points with known positions to train a CNN.
Iterated Posterior Linearization PMB Filter for 5G SLAM
In this paper, we study the linearization of the measurement function with respect to the posterior PDF, and implement the iterated posterior linearization filter into the Poisson multi-Bernoulli SLAM filter.
A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM
Millimeter wave (mmWave) signals are useful for simultaneous localization and mapping (SLAM), due to their inherent geometric connection to the propagation environment and the propagation channel.
mmWave Simultaneous Localization and Mapping Using a Computationally Efficient EK-PHD Filter
Future cellular networks that utilize millimeter wave signals provide new opportunities in positioning and situational awareness.
HybridDeepRx: Deep Learning Receiver for High-EVM Signals
In this paper, we propose a machine learning (ML) based physical layer receiver solution for demodulating OFDM signals that are subject to a high level of nonlinear distortion.
Millimeter-wave Mobile Sensing and Environment Mapping: Models, Algorithms and Validation
Integrating efficient connectivity, positioning and sensing functionalities into 5G New Radio (NR) and beyond mobile cellular systems is one timely research paradigm, especially at mm-wave and sub-THz bands.
Joint Positioning and Tracking via NR Sidelink in 5G-Empowered Industrial IoT: Releasing the Potential of V2X Technology
The fifth generation (5G) mobile networks with enhanced connectivity and positioning capabilities play an increasingly important role in the development of automated vehicle-to-everything (V2X) and other advanced industrial Internet of Things (IoT) systems.
