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This paper presents LuMaMi28, a real-time 28GHz multi-user (MU) multiple-input multiple-output (MIMO) testbed. In this testbed, the base station has 16 transceiver chains with a fully-digital beamforming architecture (with different pre-coding algorithms) and simultaneously supports multiple user equipments (UEs) with spatial multiplexing. The UEs are equipped with a beam-switchable antenna array
High-precision localization and machine learning (ML) are envisioned to be key technologies in future wireless systems. This paper presents an ML pipeline to solve localization tasks. It consists of multiple parallel processing chains, each trained using a different fingerprint to estimate the position of the user equipment. In this way, ensemble learning can be utilized to fuse all chains to impr
High-precision cellular-based localization is one of the key technologies for next-generation communication systems. In this paper, we investigate the potential of applying machine learning (ML) to a massive multiple-input multiple-output (MIMO) system to enhance localization accuracy. We analyze a new ML-based localization pipeline that has two parallel fully connected neural networks (FCNN). The
Connected Autonomous Vehicles (AVs) have the potential to revolutionize Intelligent Transportation Systems (ITS) by addressing urban transport challenges, such asAutonomous Intersection Management (AIM). However, the assumption of highly accurate positioning in most ITS applications does not align with real-life situations. While extensive research has been conducted to improve positioning accurac
In recent years, since the cloud can provide tremendous advantages regarding storage and computing resources, the industry has been motivated to move industrial control systems to the cloud. However, the cloud also introduces significant security challenges since moving control systems to the cloud can enable attackers to infiltrate the system and establish an attack that can lead to damages and d
The study aimed at examining recruiter’s experience of moral stress at recruiting and staffing companies in Sweden. Further purpose was to investigate dilemmas of four other psychological factors related to work, relevant for moral stress: cognition, emotion, control, and stress reactions. For moral stress and all other factors, differences based on sexes and work experience were investigated. An
When processing radar signals, the target steering vector is generally only partially known, being subject to various forms of errors and mismatches. In this article, we investigate the design of an unimodular transmit sequence that is robust against steering vector mismatches, with the aim of enhancing the performance of a frequency diverse array multiple-input-multiple-output (FDA-MIMO) radar sy
A fundamental aspect of the human mind is its ability to perceive, understand, and remember life experiences, which we process as distinct and meaningful sequences of events, each with a clear beginning and end. This includes experiences from audiovisual media. However, while movies do not explicitly signal when one event ends and another begins, viewers still consistently and automatically percei
When interacting with other humans, we attempt to develop a shared understanding using various means. One such method is through our eyes: when someone is looking at something, we understand that their attention is focused on that object. In this work, we present the results of an eye-tracking study built upon the Progger tool, in which we used additional code highlighting in an attempt to influen
Cellular user positioning is a promising service provided by Fifth Generation New Radio (5G NR) networks. Besides, Machine Learning (ML) techniques are foreseen to become an integrated part of 5G NR systems improving radio performance and reducing complexity. In this paper, we investigate ML techniques for positioning using 5G NR fingerprints consisting of uplink channel estimates from the physica
With the growing demand for efficient, safe and sustainable transportation systems, the imperative to design intelligent routing and traffic management solutions within urban settings, requiring minimal data exchange and ensuring scalability, becomes evident. This paper introduces an innovative paradigm for traffic management. By seamlessly integrating machine learning and Autonomous Intersection
Traditional control systems face challenges in managing high data loads and computing power, prompting the evolution of Cloud Control Systems (CCS)-a fusion of Networked Control Systems (NCS) and cloud computing. Despite offering manifold advantages, CCS encounters hurdles in navigating the dynamic cloud environment characterized by fluctuating workloads, rendering static frequency settings ineffi
With the dynamic nature of modern software development and operations environments and the increasing complexity of cloud-based software systems, traditional monitoring practices are often insufficient to timely identify and handle unexpected operational failures. To address these challenges, this paper presents the findings from a quantitative industry survey focused on the application of Machine
Massive multiple-input multiple-output (MIMO) technology will continue playing an important role in beyond 5G wireless systems. Fully digital beamforming at the millimeter wave (mmWave) spectrum enables applications that require high data rates and low latency. This paper investigates the development and deployment of mmWave massive MIMO systems in an in-flight cabin environment, from both system
The ability to encode, imagine, and remember coherent representations of the world is crucial for everyday life and depends on a brain network involving the hippocampal region. Scene construction tasks, which measure spatial coherence, have been shown to be sensitive to hippocampal integrity in amnesic patients. Hippocampal dysfunction has been implicated in posttraumatic stress disorder (PTSD), a
With several upcoming sample return missions, such as the Mars Sample Return Campaign, non-destructive methods will be key to maximizing their scientific output. In this study, we demonstrate that the combination of neutron and X-ray tomography provides an important tool for the characterization of such valuable samples. These methods allow quantitative analyses of internal sample features and als
[Context] The continuous inflow of bug reports is a considerable challenge in large development projects. Inspired by contemporary work on mining software repositories, we designed a prototype bug assignment solution based on machine learning in 2011-2016. The prototype evolved into an internal Ericsson product, TRR, in 2017-2018. TRR’s first bug assignment without human intervention happened in A
In this paper we present methods for triangulation of infinite cylinders from image line silhouettes. We show numerically that linear estimation of a general quadric surface is inherently a badly posed problem. Instead we propose to constrain the conic section to a circle, and give algebraic constraints on the dual conic, that models this manifold. Using these constraints we derive a fast minimal
QUIC is a UDP-based transport layer protocol developed by Google that boasts lower latency performance than TCP. However, different conclusions have been reported regarding its performance due to variations in targeted applications and experimental setups. This leads to our conclusion that protocol performance evaluation should be heavily dependent on the QoS requirements of the target application
We explore vibe coding as a rapid prototyping approach powered by generative AI. We discuss how it lowers the barrier to creating high-fidelity prototypes, enabling nontechnical users to build apps, and examine its implications for communication, validation, and iterative software design.
