13 citations · 21 across the 24 of their papers we have counts for
27 papers
POPT: Physics-Informed Deep Learning for Phase-Only Positioning in Distributed MIMO
Fatih Ayten, Ossi Kaltiokallio, Jukka Talvitie +6
This article develops a physics-informed deep learning framework for single-snapshot 3D phase-only positioning in narrowband phase-coherent distributed multiple-input multiple-outp…
Gaussian Process-Based Extended Object Estimation for 6G ISAC at Millimeter-Wave Frequencies
M. Ertug Pihtili, Ossi Kaltiokallio, Julia Equi +4
This paper introduces a Gaussian process (GP)-based method for extended object estimation (EOE) in integrated sensing and communication (ISAC) scenarios, representing a promising a…
Phase-Only Positioning in Distributed MIMO Under Phase Impairments: AP Selection Using Deep Learning
Fatih Ayten, Musa Furkan Keskin, Akshay Jain +5
Carrier phase positioning (CPP) can enable cm-level accuracy in next-generation wireless systems, while recent literature shows that accuracy remains high using phase-only measurem…
Multi-band Carrier Phase Positioning toward 6G: Performance Bounds and Efficient Estimators
Ehsan Shourezari, Ossi Kaltiokallio, Mehmet C. Ilter +4
In addition to satellite systems, carrier phase positioning (CPP) is gaining attraction also in terrestrial mobile networks, particularly in 5G New Radio evolution toward 6G. One k…
Clutter Suppression in Bistatic ISAC with Joint Angle and Doppler Estimation
M. Ertug Pihtili, Julia Equi, Ossi Kaltiokallio +4
The coexistence of radar and communications in wireless systems marks a paradigm shift for the sixth-generation (6G) networks. As 6G systems are expected to operate at higher frequ…
Sensing with Mobile Devices through Radio SLAM: Models, Methods, Opportunities, and Challenges
Yu Ge, Ossi Kaltiokallio, Elizaveta Rastorgueva-Foi +7
The integration of sensing and communication (ISAC) is a cornerstone of 6G, enabling simultaneous environmental awareness and communication. This paper explores radio SLAM (simulta…
Failure Tolerant Phase-Only Indoor Positioning via Deep Learning
Fatih Ayten, Mehmet C. Ilter, Akshay Jain +5
High-precision localization turns into a crucial added value and asset for next-generation wireless systems. Carrier phase positioning (CPP) enables sub-meter to centimeter-level a…
Phase-Only Positioning: Overcoming Integer Ambiguity Challenge through Deep Learning
Fatih Ayten, Mehmet C. Ilter, Ossi Kaltiokallio +5
This paper investigates uplink carrier phase positioning (CPP) in cell-free (CF) or distributed antenna system context, assuming a challenging case where only phase measurements ar…
Target Handover in Distributed Integrated Sensing and Communication
Yu Ge, Ossi Kaltiokallio, Hui Chen +7
The concept of 6G distributed integrated sensing and communications (DISAC) builds upon the functionality of integrated sensing and communications (ISAC) by integrating distributed…
Batch SLAM with PMBM Data Association Sampling and Graph-Based Optimization
Yu Ge, Ossi Kaltiokallio, Yuxuan Xia +6
Simultaneous localization and mapping (SLAM) methods need to both solve the data association (DA) problem and the joint estimation of the sensor trajectory and the map, conditioned…
Robust NLoS Localization in 5G mmWave Networks: Data-based Methods and Performance
Roman Klus, Jukka Talvitie, Julia Vinogradova +3
Ensuring smooth mobility management while employing directional beamformed transmissions in 5G millimeter-wave networks calls for robust and accurate user equipment (UE) localizati…
Multi-Objective Deep Reinforcement Learning for 5G Base Station Placement to Support Localisation for Future Sustainable Traffic
Ahmed Al-Tahmeesschi, Jukka Talvitie, Miguel López-Benítez +2
Millimeter-wave (mmWave) is a key enabler for next-generation transportation systems. However, in an urban city scenario, mmWave is highly susceptible to blockages and shadowing. T…
Robust Snapshot Radio SLAM
Ossi Kaltiokallio, Elizaveta Rastorgueva-Foi, Jukka Talvitie +3
The intrinsic geometric connections between millimeter-wave (mmWave) signals and the propagation environment can be leveraged for simultaneous localization and mapping (SLAM) in 5G…
Millimeter-wave Radio SLAM: End-to-End Processing Methods and Experimental Validation
Elizaveta Rastorgueva-Foi, Ossi Kaltiokallio, Yu Ge +6
In this article, we address the timely topic of cellular bistatic simultaneous localization and mapping (SLAM) with specific focus on end-to-end processing solutions, from raw I/Q…
Joint RIS Calibration and Multi-User Positioning
Yi Lu, Hui Chen, Jukka Talvitie +2
Reconfigurable intelligent surfaces (RISs) are expected to be a key component enabling the mobile network evolution towards a flexible and intelligent 6G wireless platform. In most…
MmWave Mapping and SLAM for 5G and Beyond
Yu Ge, Ossi Kaltiokallio, Hyowon Kim +5
Device localization and radar-like mapping are at the heart of integrated sensing and communication, enabling not only new services and applications, but can also improve communica…
Doppler Exploitation in Bistatic mmWave Radio SLAM
Yu Ge, Ossi Kaltiokallio, Hui Chen +5
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 equip…
A CNN Approach for 5G mmWave Positioning Using Beamformed CSI Measurements
Ghazaleh Kia, Laura Ruotsalainen, Jukka Talvitie
The advent of Artificial Intelligence (AI) has impacted all aspects of human life. One of the concrete examples of AI impact is visible in radio positioning. In this article, for t…
Iterated Posterior Linearization PMB Filter for 5G SLAM
Yu Ge, Yibo Wu, Fan Jiang +5
5G millimeter wave (mmWave) signals have inherent geometric connections to the propagation channel and the propagation environment. Thus, they can be used to jointly localize the r…
A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM
Yu Ge, Ossi Kaltiokallio, Hyowon Kim +6
Millimeter wave (mmWave) signals are useful for simultaneous localization and mapping (SLAM), due to their inherent geometric connection to the propagation environment and the prop…
mmWave Simultaneous Localization and Mapping Using a Computationally Efficient EK-PHD Filter
Ossi Kaltiokallio, Yu Ge, Jukka Talvitie +2
Future cellular networks that utilize millimeter wave signals provide new opportunities in positioning and situational awareness. Large bandwidths combined with large antenna array…
HybridDeepRx: Deep Learning Receiver for High-EVM Signals
Jaakko Pihlajasalo, Dani Korpi, Mikko Honkala +6
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. Spe…
Millimeter-wave Mobile Sensing and Environment Mapping: Models, Algorithms and Validation
Carlos Baquero Barneto, Elizaveta Rastorgueva-Foi, Musa Furkan Keskin +5
Integrating efficient connectivity, positioning and sensing functionalities into 5G New Radio (NR) and beyond mobile cellular systems is one timely research paradigm, especially at…
Joint Positioning and Tracking via NR Sidelink in 5G-Empowered Industrial IoT: Releasing the Potential of V2X Technology
Yi Lu, Mike Koivisto, Jukka Talvitie +4
The fifth generation (5G) mobile networks with enhanced connectivity and positioning capabilities play an increasingly important role in the development of automated vehicle-to-eve…