12 research outputs found

    Interference Mapping in 3D for High-Density Indoor IoT Deployments

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    Deployment of practical Internet of Things (IoT) in the context of 5G can be hindered by substantial interference and spectrum limitations, especially in the unlicensed frequency bands. Due to the high density of such devices in indoor scenarios, the need for interference characterization which facilitates more effective spectrum utilization is further emphasized. This chapter studies the influence of diverse scenarios for the dense placement of interferers on the spectrum occupancy through the use of 3D interference maps for two popular IoT technologies—LoRa and Wi-Fi. The experiments are performed with software-defined radio (SDR) platforms in real time and an automated positioning tool which provides the measurements to characterize the interference in 3D space. The findings demonstrate a nonuniform character of the interference and the significant impact of fading within the width, height, and length of the examined area. They suggest the role of dynamic relocation for realistic IoT scenarios

    Challenges in Implementing Low-Latency Holographic-Type Communication Systems

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    Holographic-type communication (HTC) permits new levels of engagement between remote users. It is anticipated that it will give a very immersive experience while enhancing the sense of spatial co-presence. In addition to the newly revealed advantages, however, stringent system requirements are imposed, such as multi-sensory and multi-dimensional data capture and reproduction, ultra-lightweight processing, ultra-low-latency transmission, realistic avatar embodiment conveying gestures and facial expressions, support for an arbitrary number of participants, etc. In this paper, we review the current limitations to the HTC system implementation and systemize the main challenges into a few major groups. Furthermore, we propose a conceptual framework for the realization of an HTC system that will guarantee the desired low-latency transmission, lightweight processing, and ease of scalability, all accompanied with a higher level of realism in human body appearance and dynamics

    Real-time adaptive spectrum sensing for cyclostationary and energy detectors

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    Application of a 3D Talking Head as Part of Telecommunication AR, VR, MR System: Systematic Review

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    In today’s digital era, the realms of virtual reality (VR), augmented reality (AR), and mixed reality (MR) collectively referred to as extended reality (XR) are reshaping human–computer interactions. XR technologies are poised to overcome geographical barriers, offering innovative solutions for enhancing emotional and social engagement in telecommunications and remote collaboration. This paper delves into the integration of (AI)-powered 3D talking heads within XR-based telecommunication systems. These avatars replicate human expressions, gestures, and speech, effectively minimizing physical constraints in remote communication. The contributions of this research encompass an extensive examination of audio-driven 3D head generation methods and the establishment of comprehensive evaluation criteria for 3D talking head algorithms within Shared Virtual Environments (SVEs). As XR technology evolves, AI-driven 3D talking heads promise to revolutionize remote collaboration and communication

    Enabling RF data analytics services and applications via cloudification

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    Autonomous learning model for achieving multi cell load balancing capabilities in HetNet

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    UAV-Based Volumetric Measurements toward Radio Environment Map Construction and Analysis

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    Unmanned aerial vehicle (UAV)-empowered communications have gained significant attention in recent years due to the promise of agile coverage provision for a large number of various mobile nodes on the ground and in three-dimensional (3D) space. Consequently, there is a need for efficient spectrum utilization in these dense aerial networks, which is characterized through radio environment maps (REMs), the construction of which is an important research area. Nevertheless, due to the difficult collection of radio frequency (RF) data, there are limited works that are based on real-world measurement campaigns. This paper presents a novel experimental setup that includes a constellation of three UAVs, the communication signals of which are measured by a software-defined radio (SDR) mounted on a separate UAV. It follows a trajectory that defines the REM’s two-dimensional (2D) area on a plane, executed at four altitudes, to extend the REM to 3D. The measurements are then processed and their features (received mean power level, average difference of the mean power, percentage of meaningful correlations) are analyzed in the temporal, spatial, and frequency domains to determine the utilization of a 20 MHz band in the 2.4 GHz spectrum, as well as their variation with altitude. This analysis provides a base for research in reducing the amount of measurements (by identifying the regions of low and of high interest) and spectrum occupancy prediction for UAV-based communication coexistence

    Limited Sampling Spatial Interpolation Evaluation for 3D Radio Environment Mapping

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    The increasing densification and diversification of modern and upcoming wireless networks have become an important motivation for the development of agile spectrum sharing. Radio environment maps (REMs) are a basic tool for spectrum utilisation characterisation and adaptive resource allocation, but they need to be estimated through accurate interpolation methods. This work evaluated the performance of two established algorithms for spatial three-dimensional (3D) data collected in two real-world scenarios: indoors, through a mechanical measuring system, and outdoors, through an unmanned aerial vehicle (UAV) for measurement collection. The investigation was undertaken for the complete dataset on two-dimensional (2D) planes of different altitudes and for a subset of limited samples (representing the regions of interest or RoIs), which were combined together to describe the spatial 3D environment. A minimum error of −9.5 dB was achieved for a sampling ratio of 21%. The methods’ performance and the input data were analysed through the resulting Kriging error standard deviation (STD) and the STD of the distances between the measurement and the estimated points. Based on the results, several challenges for the interpolation performance and the analysis of the spatial RoIs are described. They facilitate the future development of 3D spectrum occupancy characterisation in indoor and UAV-based scenarios
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