Showing papers by "Preben Mogensen published in 2021"
TL;DR: The results indicate that 5G technology can be used for reliable fleet management control of autonomous mobile robots in industrial scenarios, and that5G can support the migration of the on-board path planning intelligence to the edge-cloud.
Abstract: The fourth industrial revolution, or Industry 4.0 (I4.0), makes use of wireless technologies together with other industrial Internet-of-Things (IIoT) technologies, cyber–physical systems (CPS), and edge computing to enable the optimization and the faster re-configuration of industrial production processes. As I4.0 deployments are ramping up, the practical integration of 5G wireless systems with existing industrial applications is being explored in both Industry and Academia, in order to find optimized strategies and to develop guidelines oriented towards ensuring the success of the industrial wireless digitalization process. This paper explores the challenges arisen from such integration between industrial systems and 5G wireless, and presents a framework applicable to achieve a structured and successful integration. The paper aims at describing the different aspects of the framework such as the application operational flow and its associated tools, developed based on analytical and experimental applied research methodologies. The applicability of the framework is illustrated by addressing the integration of 5G technology into a specific industrial use case: the control of autonomous mobile robots. The results indicate that 5G technology can be used for reliable fleet management control of autonomous mobile robots in industrial scenarios, and that 5G can support the migration of the on-board path planning intelligence to the edge-cloud.
25 citations
TL;DR: In this paper, the authors present an overview of current Industry 4.0 applied research topics, addressed from both the industrial production and wireless communication points of view, highlighting relevant industrial use cases, their associated communication requirements, as well as the integrated technological wireless solutions applicable to each of them.
Abstract: This article presents an overview of current Industry 4.0 applied research topics, addressed from both the industrial production and wireless communication points of view. A roadmap toward achieving the more advanced industrial manufacturing visions and concepts, such as “swarm production” (nonlinear and fully decentralized production) is defined, highlighting relevant industrial use cases, their associated communication requirements, as well as the integrated technological wireless solutions applicable to each of them. Further, the article introduces the Aalborg University 5G Smart Production Lab, an industrial lab test environment specifically designed to prototype and demonstrate different Industrial IoT use cases enabled by the integration of robotics, edge-cloud platforms, and autonomous systems operated over wireless technologies such as 4G, 5G, and Wi-Fi. Wireless performance results from various operational trials are also presented for two use cases: wireless control of industrial production and wireless control of autonomous mobile robots.
24 citations
TL;DR: In this article, a measurement campaign for the A2G channels is introduced, where a uniform circular array (UCA) with 16 antenna elements was employed to collect the downlink signals of two different Long Term Evolution (LTE) networks, at the heights of 0-40m in three different, namely rural, urban and industrial scenarios.
Abstract: Cellular-connected unmanned aerial vehicles (UAVs) have recently attracted a surge of interest in both academia and industry. Understanding the air-to-ground (A2G) propagation channels is essential to enable reliable and/or high-throughput communications for UAVs and protect the ground user equipments (UEs). In this contribution, a recently conducted measurement campaign for the A2G channels is introduced. A uniform circular array (UCA) with 16 antenna elements was employed to collect the downlink signals of two different Long Term Evolution (LTE) networks, at the heights of 0-40m in three different, namely rural, urban and industrial scenarios. The channel impulse responses (CIRs) have been extracted from the received data, and the spatial, including angular, parameters of the multipath components in individual channels were estimated according to a high-resolution-parameter-estimation (HRPE) principle. Based on the HRPE results, clusters of multipath components were further identified. Finally, comprehensive spatial channel characteristics were investigated in the composite and cluster levels at different heights in the three scenarios.
22 citations
13 Sep 2021
TL;DR: In this paper, a deep neural network (DNN) is trained to approximate the mapping using data obtained via application of centralized graph coloring (CGC), and the trained network is then deployed at each subnetwork for distributed channel selection.
Abstract: This paper investigates efficient deep learning based methods for interference mitigation in independent wireless subnetworks via dynamic allocation of radio resources. Resource allocation is cast as a mapping from interference power measurements at each subnetwork to a class of shared frequency channels. A deep neural network (DNN) is then trained to approximate this mapping using data obtained via application of centralized graph coloring (CGC). The trained network is then deployed at each subnetwork for distributed channel selection. Simulation results in an environment with mobile subnetworks have shown that relatively small-sized DNNs can be trained offline to perform distributed channel allocation. The results also show that regardless of the choice of initialization, a DNN for distributed channel selection can achieve similar performance as CGC up to a probability of loop failure (PLF) of 6 × 10–5 in diverse environments with only aggregate interference power measurements as input.
8 citations
29 Mar 2021
TL;DR: In this paper, the authors introduce two new decentralized resource allocation schemes that meet the stringent requirements of reliable, high throughput and low latency communication of broadcasted video data among robots within proximity.
Abstract: Robotic swarms are becoming relevant across different industries. In an indoor factory, collective perception of the environment can be used for increased factory automatization. It requires reliable, high throughput and low latency communication of broadcasted video data among robots within proximity. We introduce two new decentralized resource allocation schemes that meet these stringent requirements. The two proposed decentralized schemes are denoted as: (i) device sequential, where robots take turns to allocate resources, and (ii) group scheduling, where robots select local group leaders who perform the resource allocation. A comparative evaluation is performed by simulation against a centralized resource allocation scheme and the current 3GPP release 16 NR sidelink mode 2 scheme. Our results show that the two proposed decentralized resource allocation schemes outperform sidelink mode 2 due to the mitigation of the half-duplex problem. The proposed schemes reach the throughput target of 10 Mbps with a reliability of 99.99% for a swarm size of 50 robots.
3 citations
25 Apr 2021
TL;DR: A Markov-based channel state model that takes into consideration the time correlations of the LOS variations along the satellite’s orbit and can accurately reflect the behaviour of the channel state variations of those scenarios, essentially leading to a realistic number of state changes per satellite pass.
Abstract: Low Earth orbit (LEO) satellite networks will play a major role in future broadband communications. To study LEO satellite mobility performance, and guarantee reliable service, accurate channel characterization is necessary. Current models, such as the ones reported by 3GPP and ITU, define channel parameters as a function of elevation angle, frequency and deployment scenario. However, key parameters including the line-of-sight (LOS) probability and the shadow fading do not describe any time component or correlation and, therefore, the movement of the satellite is not captured. This fact might result in unrealistic changes of the LOS/NLOS states hampering the radio mobility studies for 5G-based LEO satellite networks. In this paper, we present a Markov-based channel state model that takes into consideration the time correlations of the LOS variations along the satellite’s orbit. The proposed model is based on ray-tracing measurements of suburban and dense urban scenarios and it can accurately reflect the behaviour of the channel state variations of those scenarios, essentially leading to a realistic number of state changes per satellite pass.
2 citations
TL;DR: The investigation in [1] shows that in the high signal-to-interference-plus-noise (SINR) regime, geometrical programming (GP) can be used to efficiently and reliably solve the problem and a new condensation method is proposed that makes the power control practically solvable for both small- and large-scale networks.
Abstract: Power control is becoming increasingly essential for the fifth-generation (5G) and beyond systems. An example use-case, among others, is the unmanned-aerial-vehicle (UAV) communications where the nearly line-of-sight (LoS) radio channels may result in very low signal-to-interference-plus-noise ratios (SINRs). The authors in (Chiang et al. , 2007) proposed to efficiently and reliably solve this kind of non-convex problem via a series of geometrical programmings (GPs) using condensation approximation. However, it is only applicable for a small-scale network with several communication pairs and practically infeasible with more (e.g., tens of) nodes to be jointly optimized. We therefore in this paper aim to provide new insights into this problem. By properly introducing auxiliary variables, the problem is transformed to an equivalent form which is simpler and more intuitive for condensation. A novel condensation method with linear complexity is also proposed based on the form. The enhancements make the GP-based power control feasible for both small- and especially large-scale networks that are common in 5G and beyond. The algorithm is verified via simulations. A preliminary case study of uplink UAV communications also shows the potential of the algorithm.
1 citations
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TL;DR: In this article, the uplink communications of cellular-connected UAVs are investigated and several different scheduling and power control algorithms are proposed to optimize the spectrum efficiency based on the geometrical programming (GP) principle together with the successive convex approximation (SCA) technique.
Abstract: Cellular connected unmanned aerial vehicle (UAV) has been identified as a promising paradigm and attracted a surge of research interest recently. Although the nearly line-of-sight (LoS) channels are favorable to receive higher powers, UAV can in turn cause severe interference to each other and to any other users in the same frequency band. In this contribution, we focus on the uplink communications of cellular-connected UAV. To cope with the severe interference among UAV-UEs, several different scheduling and power control algorithms are proposed to optimize the spectrum efficiency (SE) based on the geometrical programming (GP) principle together with the successive convex approximation (SCA) technique. The proposed schemes include maximizing the sum SE of UAVs, maximizing the minimum SE of UAVs, etc., applied in the frequency domain and/or the time domain. Moreover, the quality of service (QoS) constraint and the uplink single-carrier (SC) constraint are also considered. The performances of these power and resource allocation algorithms are evaluated via extensive simulations in both full buffer transmission mode and bursty traffic mode. Numerical results show that the proposed algorithms can effectively enhance the uplink SEs of cellular-connected UAVs.
Posted Content•
TL;DR: In this article, the authors proposed two cooperative resource allocation schemes, device sequential and group scheduling, and introduced a control signaling design to avoid half-duplex problems at the receiver and mitigate interference.
Abstract: Decentralized cooperative resource allocation schemes for robotic swarms are essential to enable high reliability in high throughput data exchanges. These cooperative schemes require control signaling with the aim to avoid half-duplex problems at the receiver and mitigate interference. We propose two cooperative resource allocation schemes, device sequential and group scheduling, and introduce a control signaling design. We observe that failure in the reception of these control signals leads to non-cooperative behavior and to significant performance degradation. The cause of these failures are identified and specific countermeasures are proposed and evaluated. We compare the proposed resource allocation schemes against the NR sidelink mode 2 resource allocation and show that even though signaling has an important impact on the resource allocation performance, our proposed device sequential and group scheduling resource allocation schemes improve reliability by an order of magnitude compared to sidelink mode 2.
Proceedings Article•
18 Jul 2021
TL;DR: In this article, the authors proposed tractable analytical frameworks of coverage and rate based on the novel unbounded path-loss model with a constant distance factor r_0 for analyzing the UAV-to-UAV communications.
Abstract: In this paper, we focus on ultra-dense network modelingwhere both the Base Stations (BSs) and Mobile Terminals(MTs) are UAVs. In this case, two communication nodes canbe very close to each other. However, existing cellular networkanalyses typically use the standard unbounded path loss modelwhere received power decays like r^beta over a distance r. Thisstandard model is a good approximation for the path-loss inwireless communications over large values of r but is not validfor small values of r due to the singularity at 0. This model is oftenused along with a random uniform node distribution, even thoughin a group of uniformly distributed nodes some may be arbitrarilyclose to one another, thus, it will lose accuracy and may benot applicable for UAV-to-UAV communications. To tackle thisproblem, by using mathematical tool behind stochastic geometry,we propose tractable analytical frameworks of coverage and ratebased on the novel unbounded path-loss model with a constantdistance factor r_0 for analyzing the UAV-to-UAV communications.
Proceedings Article•
18 Jul 202122 Mar 2021
TL;DR: In this paper, a measurement-based comparison of large vehicle shadowing at 3.5 and 5.9 GHz was performed for both V2V and V2I scenarios in a controlled environment.
Abstract: This paper presents a measurement-based comparison of large vehicle shadowing at 3.5 and 5.9 GHz. Obstructed line-of-sight measurements were performed for both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) scenarios in a controlled environment. The results show how the V2I scenarios with elevated transmit antenna positions can benefit from a 2-6 dB smaller shadow loss as compared to the V2V scenarios. Due to the smaller diffraction loss experienced at 3.5 GHz, the maximum shadow levels can be up to 2-3 dB smaller than at 5.9 GHz. The absolute numbers and empirical distributions provided can be used in system level evaluations of vehicle-to-everything (V2X) and vehicle-to-network (V2N) vehicular communication scenarios.