Article
Computer Science, Hardware & Architecture
Ryoichi Shinkuma, Naoki Kishi, Kaoru Ota, Mianxiong Dong, Takehiro Sato, Eiji Oki
Summary: The study proposes a scheme utilizing software-defined networking and edge computing technologies to enhance traffic prediction accuracy by incorporating important traffic logs, even when using only logs from active base stations.
Article
Computer Science, Information Systems
Wanying Guo, Jahwan Koo, Isma Farah Siddiqui, Nawab Muhammad Faseeh Qureshi, Dong Ryeol Shin
Summary: This article studies the issue of increased energy consumption due to the increase in base station density in 5G HetNets and proposes an optimized micro base station deployment strategy to improve energy efficiency. Simulation experiments have demonstrated the effectiveness of the proposed strategy in improving energy efficiency.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Jari Huttunen, Matti Parssinen, Tomi Heikkila, Olli Salmela, Jukka Manner, Eva Pongracz
Summary: Growing energy consumption is a global problem. The ICT industry plays a critical role in enabling energy savings, but it also needs to address its own power consumption. This article fills the information gap by providing data on the energy consumption of base transceiver stations for different generations of mobile networks.
Article
Telecommunications
Jiantao Yuan, Zheyi Wu, Rui Yin, Guangzhe Zhao, Xianfu Chen, Celimuge Wu
Summary: Rational sharing of unlicensed spectrum and efficient use of device-to-device (D2D) communication are effective ways to improve energy efficiency (EE) and spectrum efficiency (SE) in 5G new radio system. This paper extends D2D technology to unlicensed spectrum and studies the EE of user terminals in unlicensed D2D (D2D-U) system. A distributed adaptive joint power and spectrum allocation scheme is proposed based on the differentiated projection method to maximize the EE of user terminals, considering the distributed structure and time-varying wireless fading channels in D2D-U networks. Theoretical analysis and numerical results validate the performance of the proposed scheme, which significantly reduces signaling overhead and achieves global optimality.
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
(2023)
Article
Computer Science, Hardware & Architecture
Sangeeta Bhattacharjee, Tamaghna Acharya, Uma Bhattacharya
Summary: This paper surveys the latest techniques for multicast services in cognitive radio networks and analyzes the utility of different spectrum sharing models in fulfilling the communication goals of multicast services. The study emphasizes the characteristics of multicast traffic, key enabling techniques for enhancing the efficiency of such services, and approaches for mitigating interference experienced by licensed users. By analyzing existing works, this paper provides design guidelines for multicast services in future 5G networks and discusses future research directions.
Article
Computer Science, Hardware & Architecture
Shavbo Salehi, Behdis Eslamnour
Summary: The paper proposes a method for using UAV-BS for communication in Industrial IoT and reduces energy consumption through energy-efficient trajectory design. The combination of UMC-IRSA method and Q-Learning algorithm decreases UAV-BS energy consumption effectively.
Article
Computer Science, Information Systems
Parinaz Dastranj, Vahid Solouk, Hashem Kalbkhani
Summary: This study proposes a scheme for selecting ABS in wireless networks with unmanned aerial vehicles, which maximizes energy efficiency and load balancing through target ABS selection, resource block, and power allocation algorithm. The simulation results show that the proposed method improves load balancing, spectral efficiency, and energy efficiency.
COMPUTER COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Yi Yang, Zhixin Liu, Heng Zhu, Xinping Guan, Kit Yan Chan
Summary: This paper proposes a switch algorithm to reduce energy consumption in dense networks. By adjusting the switch status of base stations based on traffic load, the energy consumption becomes more flexible and effective.
Article
Computer Science, Information Systems
Mohammed H. Alsharif, Raju Kannadasan, Abu Jahid, Mahmoud A. Albreem, Jamel Nebhen, Bong Jun Choi
Summary: The study proposes a sustainable solar-powered model for cellular base stations in South Korea, aiming to provide 24-hour uninterrupted power support for LTE base stations and achieve energy savings and emission reductions.
Article
Engineering, Electrical & Electronic
Zhe Wang, Jun Zheng
Summary: This paper investigates the performance of base station cooperation for downlink transmission of an unmanned aerial vehicle in a cellular-connected network. Performance models are derived and validated through Monte Carlo simulations, analyzing factors affecting coverage probability and achievable throughput of the UAV. The study provides theoretical guidance for designing a base station cooperation strategy.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Pan Cao
Summary: With the increasing use of unmanned aerial vehicles, there is a growing threat of using UAVs for infrastructure/cyber-attacks and data-eavesdropping. This research explores the concept of using cellular base stations for imaging to detect UAVs, allowing them to function like inverse synthetic-aperture radars (ISAR) in addition to communication. The feasibility of this joint imaging and communication (JIAC) approach is studied and analyzed, showing promising results for UAV detection with minimal impact on current communication operations.
Article
Automation & Control Systems
Jinsong Gui, Lihuan Hui, Neal N. Xiong, Jie Wu
Summary: In this study, a novel incentive architecture based on dynamic radio frequency charging technology is proposed to improve spectrum efficiency, using Stackelberg game theory as a formulation. The model involves a competition between small base stations, small energy providers, and small virtual access points to improve spectrum efficiency for edge devices, demonstrating convergence and improvement through theoretical analysis and simulation results.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Construction & Building Technology
Carmela Vetromile, Antonio Spagnuolo, Antonio Petraglia, Antonio Masiello, Maria Rosa di Cicco, Carmine Lubritto
Summary: In the telecommunications sector, energy saving has been a major focus in recent years. While attention is often on the energy efficiency of consumer products and data centers, the telecommunications network that manages the entire system is sometimes overlooked. Smart energy management of Base Transceiver Stations can lead to significant savings in power consumption and environmental impact.
ENERGY AND BUILDINGS
(2021)
Article
Computer Science, Hardware & Architecture
Greta Vallero, Margot Deruyck, Michela Meo, Wout Joseph
Summary: This paper investigates the impact of MEC technology on RAN performance in terms of caching, proposes new user association policies to reduce network energy consumption, and the simulation results show that this technology and methodology can significantly reduce user experienced delay and energy consumption.
Article
Computer Science, Information Systems
Greta Vallero, Daniela Renga, Michela Meo, Marco Ajmone Marsan
Summary: This paper focuses on using ML tools for resource management in a portion of a Radio Access Network (RAN), specifically in Base Station (BS) activation and deactivation. The aim is to reduce energy consumption while meeting the variable traffic demand of users. Traffic predictions, made using Artificial Neural Networks (ANN), are used to make informed decisions on BS activation and deactivation. The results indicate that even with prediction errors, good performance trade-offs can be achieved, and dynamic resource allocation has an impact on BS failure rates.
COMPUTER COMMUNICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Dan Yao, Stephen McLaughlin, Yoann Altmann
Summary: This paper presents a new Expectation Propagation (EP) framework for image restoration using patch-based prior distributions. The EP method is used to approximate posterior distributions, addressing scalability issues in high-dimensional inference problems. Experimental results demonstrate the potential benefits of this flexible approximate Bayesian method for uncertainty quantification in imaging problems, at a reduced computational cost compared to sampling techniques.
SIAM JOURNAL ON IMAGING SCIENCES
(2022)
Article
Engineering, Electrical & Electronic
Mohamed Amir Alaa Belmekki, Rachael Tobin, Gerald S. Buller, Stephen McLaughlin, Abderrahim Halimi
Summary: This paper proposes a task-optimized adaptive sampling framework for 3D single-photon LiDAR imaging. It enables fast acquisition and processing of high-dimensional data by targeting informative regions for object classification and target detection. The framework is demonstrated to be effective in both sequential and parallel scanning modes for different detector array sizes.
IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING
(2022)
Article
Engineering, Electrical & Electronic
Sandor Plosz, Aurora Maccarone, Stephen McLaughlin, Gerald S. Buller, Abderrahim Halimi
Summary: This paper introduces a two-step statistical-based approach for real-time image reconstruction in extreme light scattering conditions. It includes an optional target detection method for data compression and a reconstruction algorithm for delivering clean depth and reflectivity images. Both methods are implemented in parallel on GPUs, enabling real-time data processing at high speed. Comparisons with state-of-the-art algorithms on simulated and real underwater data show the benefits of the proposed framework for target detection and fast depth estimation.
IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING
(2023)
Article
Optics
Mohamed Amir Alaa Belmekki, Jonathan Leach, Rachael Tobin, Gerald S. Buller, Stephen McLaughlin, Abderrahim Halimi
Summary: 3D single-photon LiDAR imaging is crucial for many applications, but requires analysis of low signal-to-noise ratio returns and high data volume. This paper proposes a multiscale approach for 3D surface detection, reducing data volume while obtaining background-free surfaces for depth and reflectivity inference. A hierarchical Bayesian model is also introduced for 3D reconstruction and spectral classification. Results demonstrate the superiority of these approaches compared to state-of-the-art algorithms.
Article
Optics
Aurora Maccarone, Kristofer Rummond, Aongus Mccarthy, Ulrich K. S. Teinlehner, Julian Achella, Diego A. Guirre G. Arcia, Agata Pawlikowska, Robert A. Lamb, Robert K. Henderson, Stephen Mclaughlin, Yoann Altmann, Gerald S. Buller
Summary: We developed a fully submerged underwater LiDAR transceiver system using single-photon detection technologies. The system utilized a silicon single-photon avalanche diode (SPAD) detector array and picosecond resolution time-correlated single-photon counting for photon time-of-flight measurement. Real-time three-dimensional imaging was achieved through a joint surface detection and distance estimation algorithm. The system demonstrated high-resolution imaging of stationary and moving targets at depths of 1.8 meters and stand-off distances of up to 5.5 attenuation lengths.
Article
Optics
Dan Yao, Peter W. R. Connolly, Arran J. Sykes, Yash D. Shah, Claudio Accarino, James Grant, David R. S. Cumming, Gerald S. Buller, Stephen Mclaughlin, Yoann Altmann
Summary: This paper presents an experimental demonstration of a Bayesian image reconstruction approach for rapid single-photon color imaging of moving objects. The authors address the challenges of efficient spectral separation and high-speed image reconstruction in low-photon flux environments using hardware and computational solutions.
Article
Multidisciplinary Sciences
Abdullah Abdulaziz, Simon Peter Mekhail, Yoann Altmann, Miles J. Padgett, Stephen McLaughlin
Summary: This paper proposes a real-time imaging system using flexible multimode fibers (MMFs) that remains robust to bending. The approach does not require accessing or providing feedback signal from the distal end of the fiber during imaging. By leveraging a variational autoencoder, the system is able to reconstruct and classify images from speckle patterns, and can still recover these images when the fiber's bending configuration is changed to an untrained state. The system utilizes a 300 mm long MMF with a 62.5 μm core to image 10 x 10 cm objects placed approximately 20 cm from the fiber, and it can handle a change in fiber bend of 50° and a range of movement of 8 cm.
SCIENTIFIC REPORTS
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Qianru Zhou, Rongzhen Li, Lei Xu, Anmin Fu, Jian Yang, Alasdair J. G. Gray, Stephen McLaughlin
Summary: The Internet is a complex machine and defending it from intrusions is challenging. With the increasing intrusions, intrusion detection relies more on Artificial Intelligence. However, current interpretation AI technologies are not accurate or sufficient. This paper proposes a rigorous interpretable AI-driven intrusion detection approach using formal logic calculations and presents detailed explanations for decision tree models. Experiments are conducted in real-life traffic.
SOFT COMPUTING AND ITS ENGINEERING APPLICATIONS, ICSOFTCOMP 2022
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
A. Abdulaziz, Y. Altmann, S. McLaughlin, M. E. Davies
Summary: This paper presents an artificial neural network approach for estimating hazardous material release parameters using time-series of multispectral satellite images. The proposed method aims to overcome the limitations of existing techniques and improve the accuracy and speed of source term estimation in real-world applications.
2023 SENSOR SIGNAL PROCESSING FOR DEFENCE CONFERENCE, SSPD
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Dan Yao, Yoann Altmann, Stephen McLaughlin
Summary: In this paper, a new EP algorithm using l(1)-TV prior is proposed for color image restoration in the low photon-count regime. The algorithm can estimate the RGB values of each pixel from a single channel grayscale image and provide uncertainty quantification of the estimates.
2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP
(2022)
Article
Engineering, Electrical & Electronic
Kai Xu, Jiayu Hou, Li Wang, Simona Sibio, John S. Thompson, Stephen McLaughlin, Yuan Ding, Gunnar Peters
Summary: This paper introduces a practical dynamic subarray m-MIMO structure based on reconfigurable power dividers, and the extensive system simulation results show that this structure outperforms the fixed subarray counterpart.
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY
(2022)
Proceedings Paper
Acoustics
Abderrahim Halimi, Jakeoung Koo, Robert A. Lamb, Gerald S. Buller, Stephen McLaughlin
Summary: This paper presents a new Bayesian algorithm for the robust reconstruction of multispectral single-photon Lidar data acquired in extreme conditions. The proposed method utilizes multiscale information to estimate distribution of the target's depth and reflectivity, improving decision making.
2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
(2022)
Proceedings Paper
Acoustics
Abdullah Abdulaziz, Jianxin Zhou, Angela Di Fulvio, Yoann Altmann, Stephen McLaughlin
Summary: In this paper, a method of pulse shape discrimination using Gaussian mixture variational autoencoder (GMVAE) is proposed. By learning the features of pulses from unlabeled data, the classification accuracy can be improved. Experimental results show that GMVAE outperforms other classifiers on different datasets.
2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
(2022)
Article
Computer Science, Artificial Intelligence
Dan Yao, Stephen McLaughlin, Yoann Altmann
Summary: This paper presents a scalable approximate Bayesian method for image restoration using Total Variation (TV) priors, with the ability to offer uncertainty quantification. The method utilizes the Expectation Propagation (EP) framework for estimation and automatically adjusts the regularization parameter through Expectation Maximization (EM).
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2022)
Article
Computer Science, Information Systems
M. E. N. G. W. E. SUN, G. E. O. R. G. E. GOUSSETIS, K. A. XU, Y. U. A. N. DING, S. T. E. P. H. E. N. MCLAUGHLIN, A. N. D. R. E. A. SEGNERI, M. A. R. I. A. J. E. S. U. S. C. A. N. E. V. A. T. E. SANCHEZ
Summary: This paper discusses the need for high data transmission throughput in future broadband satellite communication systems and the limitations of current ACM technology. It proposes a method for selecting optimal system configurations based on the non-linear characteristics of the SatCom link and the pre-distortion algorithm. The effectiveness of the method is validated through simulations and experimental tests.
