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A Survey On Blockchain for Dynamic Spectrum Sharing IEEE Open J. Commun. Soc. Pub Date : 2024-03-14 Lavan Perera, Pasika Ranaweera, Sachitha Kusaladharma, Shen Wang, Madhusanka Liyanage
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Resilient Disaster Relief in Industrial IoT: UAV Trajectory Design and Resource Allocation in 6G Non-Terrestrial Networks IEEE Open J. Commun. Soc. Pub Date : 2024-03-12 Amir Mohammadisarab, Ali Nouruzi, Ata Khalili, Nader Mokari, Bijan Abbasi Arand, Eduard A. Jorswieck
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OIDC2: Open Identity Certification With OpenID Connect IEEE Open J. Commun. Soc. Pub Date : 2024-03-11 Jonas Primbs, Michael Menth
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Multivariate Forecasting of Network Traffic in SDN Based Ubiquitous Healthcare System IEEE Open J. Commun. Soc. Pub Date : 2024-03-08 Deva Priya Isravel, Salaja Silas, Jaspher W.Kathrine, Elijah Blessing Rajsingh, Andrew J
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Time, Simultaneity, and Causality in Wireless Networks With Sensing and Communications IEEE Open J. Commun. Soc. Pub Date : 2024-03-07 Petar Popovski
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Cell-Free Massive MIMO With Multi-Antenna Users and Phase Misalignments: A Novel Partially Coherent Transmission Framework IEEE Open J. Commun. Soc. Pub Date : 2024-03-05 Unnikrishnan Kunnath Ganesan, Tung Thanh Vu, Erik G. Larsson
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TinyML Empowered Transfer Learning on the Edge IEEE Open J. Commun. Soc. Pub Date : 2024-03-05 Ali M. Hayajneh, Maryam Hafeez, Sayed Ali Zaidi, Des McLernon
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Distortion-Aware Power Allocation for Multi-Stream Distributed Massive MIMO System With Nonlinear Power Amplifier IEEE Open J. Commun. Soc. Pub Date : 2024-03-05 Bin Liu, Sofie Pollin
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Laser-Empowered UAVs for Aerial Data Aggregation in Passive IoT Networks IEEE Open J. Commun. Soc. Pub Date : 2024-03-05 Amr M. Abdelhady, Abdulkadir Celik, Carles Diaz-Vilor, Hamid Jafarkhani, Ahmed M. Eltawil
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Joint UAV Trajectory Planning and LEO-Sat Selection in SAGIN IEEE Open J. Commun. Soc. Pub Date : 2024-03-05 Ehab Mahmoud Mohamed, Mohammad Alnakhli, Mostafa M. Fouda
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Beamforming and Device Selection Design in Federated Learning With Over-the-Air Aggregation IEEE Open J. Commun. Soc. Pub Date : 2024-03-05 Faeze Moradi Kalarde, Min Dong, Ben Liang, Yahia A. Eldemerdash Ahmed, Ho Ting Cheng
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Deep Learning-Based FM Demodulation in Complex Electromagnetic Environment IEEE Open J. Commun. Soc. Pub Date : 2024-03-05 Shilian Zheng, Zhangbin Pei, Tao Chen, Jiepeng Chen, Weidang Lu, Xiaoniu Yang
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Energy-Efficient Clustered Cell-Free Networking With Access Point Selection IEEE Open J. Commun. Soc. Pub Date : 2024-03-05 Ouyang Zhou, Junyuan Wang, Fuqiang Liu, Jiangzhou Wang
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Physical Layer Security in Mixed UOWC-RF Networks With Energy Harvesting Relay Against Multiple Eavesdroppers IEEE Open J. Commun. Soc. Pub Date : 2024-03-05 Moloy Kumar Ghosh, Milton Kumar Kundu, Md. Ibrahim, A. S. M. Badrudduza, Md. Shamim Anower, Imran Shafique Ansari, Annie Solomon, Sumit Chakravarty, Imtiaz Ahmed, Heejung Yu
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Cellular Wireless Networks in the Upper Mid-Band IEEE Open J. Commun. Soc. Pub Date : 2024-03-05 Seongjoon Kang, Marco Mezzavilla, Sundeep Rangan, Arjuna Madanayake, Satheesh Bojja Venkatakrishnan, Grégory Hellbourg, Monisha Ghosh, Hamed Rahmani, Aditya Dhananjay
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Grid-Based Channel Modeling Technique for Scenario-Specific Wireless Channel Emulator Based On Path Parameters Interpolation IEEE Open J. Commun. Soc. Pub Date : 2024-03-05 Nopphon Keerativoranan, Kentaro Saito, Jun-Ichi Takada
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Securing Synchrophasors Using Data Provenance in the Quantum Era IEEE Open J. Commun. Soc. Pub Date : 2024-03-01 Kashif Javed, Mansoor Ali Khan, Mukhtar Ullah, Muhammad Naveed Aman, Biplab Sikdar
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A Novel Approach for Scalable and Sustainable 6G Networks IEEE Open J. Commun. Soc. Pub Date : 2024-03-01 Luis Blanco, Engin Zeydan, Sergio Barrachina-Muñoz, Farhad Rezazadeh, Luca Vettori, Josep Mangues-Bafalluy
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Towards Natively Intelligent Semantic Communications and Networking IEEE Open J. Commun. Soc. Pub Date : 2024-02-29 Stylianos E. Trevlakis, Nikolaos Pappas, Alexandros-Apostolos A. Boulogeorgos
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Performance Analysis of RIS-Assisted Communication With Direct Link: A New Copula Application IEEE Open J. Commun. Soc. Pub Date : 2024-02-28 Damoon Shahbaztabar, Imène Trigui, Wei-Ping Zhu, Wessam Ajib
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Correction to “Dynamic Spectrum Sharing for 5G NR and 4G LTE Coexistence—A Comprehensive Review” IEEE Open J. Commun. Soc. Pub Date : 2024-02-28 Rony K. Saha, John M. Cioffi
The Authors’ biographies were omitted from the above original article [1] .
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Channel Reciprocity Attacks Using Intelligent Surfaces With Non-Diagonal Phase Shifts IEEE Open J. Commun. Soc. Pub Date : 2024-02-27 Haoyu Wang, Zhu Han, A. Lee Swindlehurst
While reconfigurable intelligent surface (RIS) technology has been shown to provide numerous benefits to wireless systems, in the hands of an adversary such technology can also be used to disrupt communication links. This paper describes and analyzes an RIS-based attack on multi-antenna wireless systems that operate in time-division duplex mode under the assumption of channel reciprocity. In particular
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Bandit-Based Learning-Aided Full-Duplex/Half-Duplex Mode Selection in 6G Cooperative Relay Networks IEEE Open J. Commun. Soc. Pub Date : 2024-02-26 Nikolaos Nomikos, Themistoklis Charalambous, Panagiotis Trakadas, Risto Wichman
The high level of autonomy and intelligence that is envisioned in sixth generation (6G) networks necessitates the development of learning-aided solutions, especially in cases in which conventional Channel State Information (CSI)-based network processes introduce high signaling overheads. Moreover, in wireless topologies characterized by fast varying channels, timely and accurate CSI acquisition might
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An Extended Look at Midpoint Optimization for Segment Routing IEEE Open J. Commun. Soc. Pub Date : 2024-02-26 Alexander Brundiers, Timmy Schüller, Nils Aschenbruck
In this paper, we discuss and examine the concept of Midpoint Optimization (MO) for Segment Routing (SR). It is based on the idea of integrating SR policies into the Interior Gateway Protocol (IGP) to allow various demands to be steered into them. We discuss the benefits of this approach when compared to end-to-end SR and potential challenges that might arise in deployment. We further develop a Linear
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Precise Frequency Response of COTS LED for VLC Using Internal Quantum Efficiency Metric IEEE Open J. Commun. Soc. Pub Date : 2024-02-21 Jian Xiong, Menghan Li, Runxin Zhang, Lu Lu, Qifu Tyler Sun, Keping Long
Visible light communications (VLC) utilizing LEDs for transmissions have been widely considered a revolutionary solution for next-generation networks such as 6G. Frequency response (FR) is of great importance for LEDs, but the inherent internal quantum efficiency (IQE) of LEDs is often disregarded, resulting in imprecise FR models. Although it is widely known that IQE varies with the injected direct
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An Efficient and Dependable UAV-Assisted Code Dissemination in 5G-Enabled Industrial IoT IEEE Open J. Commun. Soc. Pub Date : 2024-02-21 Ravi Sharma, Balázs Villányi
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Beamforming Design for Dynamic Metasurface Antennas-Based Massive Multiuser MISO Downlink Systems IEEE Open J. Commun. Soc. Pub Date : 2024-02-20 Jung-Chieh Chen, Chiu-Hsiang Hsu
This study addresses a massive multiuser multiple-input single-output downlink system with a base station equipped with dynamic metasurface antennas (DMAs) serving single-antenna users. Our goal is to jointly optimize the transmit precoder and configurable DMA coefficients to maximize system performance. This task is challenging due to the complex interdependencies between these parameters. The established
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Aqua-Sense: Relay-Based Underwater Optical Wireless Communication for IoUT Monitoring IEEE Open J. Commun. Soc. Pub Date : 2024-02-19 Maaz Salman, Javad Bolboli, Ramavath Prasad Naik, Wan-Young Chung
Underwater wireless optical communication (UWOC) performance is negatively impacted by challenges such as water turbulence, restricted range, and misalignment. These challenges can impact the feasibility of large-scale deployment. In comparison to conventional acoustic and radio frequency (RF) communication, UWOC can play a pivotal role in connecting various Internet of Underwater Things (IoUT) devices
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Attribute-Based Management of Secure Kubernetes Cloud Bursting IEEE Open J. Commun. Soc. Pub Date : 2024-02-19 Mauro Femminella, Martina Palmucci, Gianluca Reali, Mattia Rengo
In modern cloud computing, the need for flexible and scalable orchestration of services, combined with robust security measures, is paramount. In this paper, we propose an innovative approach for managing secure cloud bursting in Kubernetes, combining Attribute-Based Encryption (ABE) with Kubernetes labeling. Our model addresses the challenges of complexity, cost, and data protection compliance by
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Enhancing Adaptive Beamforming in 3-D Space Through Self-Improving Neural Network Techniques IEEE Open J. Commun. Soc. Pub Date : 2024-02-16 Ioannis Mallioras, Traianos V. Yioultsis, Nikolaos V. Kantartzis, Pavlos I. Lazaridis, Zaharias D. Zaharis
In the rapidly evolving domain of wireless networks, adaptive beamforming stands as a cornerstone for achieving higher data rates, enhanced network capacity, and reduced latency. This study introduces a novel integration of deep neural networks (NNs) into adaptive beamforming, specifically for uniform planar arrays (UPAs). We embark on an exploration of different NN architectures (a deep feedforward
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Explainable Deep-Learning Approaches for Packet-Level Traffic Prediction of Collaboration and Communication Mobile Apps IEEE Open J. Commun. Soc. Pub Date : 2024-02-16 Idio Guarino, Giuseppe Aceto, Domenico Ciuonzo, Antonio Montieri, Valerio Persico, Antonio Pescapè
Significant in lifestyle have reshaped the Internet landscape, resulting in notable shifts in both the magnitude of Internet traffic and the diversity of apps utilized. The increased adoption of communication-and-collaboration apps, also fueled by lockdowns in the COVID pandemic years, has heavily impacted the management of network infrastructures and their traffic. A notable characteristic of these
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Guest Editorial: Special Issue on Resource-Efficient Collaborative Deep Learning Over B5G/6G Networks IEEE Open J. Commun. Soc. Pub Date : 2024-02-12 Bouziane Brik, Mehdi Bennis, Xianbin Wang, Mohsen Guizani
Collaborative machine learning is considered as the bedrock of the intelligent B5G networks, where distributed agents collaborate with each other to train learning models in a distributed fashion, without sharing data at a central entity. Despite its broad applicability, the main issue of collaborative learning is the need of local computing to build local learning models as well as iterative information
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Opportunistic Throughput Optimization in Energy Harvesting Dynamic Spectrum Sharing Wireless Networks IEEE Open J. Commun. Soc. Pub Date : 2024-02-14 Amirhossein Taherpour, Abbas Taherpour, Tamer Khattab, Mohamed Abdallah
We investigate opportunistic transmissions in a time-slotted wireless network, emphasizing constraints arising from finite durations allocated to various network operations and the availability of energy for these operations. Each time frame (time slot) comprises three sub-frames: sensing, reporting, and either transmission or energy harvesting based on the presence or absence of the primary user.
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An Affine Precoded Superimposed Pilot Based mmWave MIMO-OFDM ISAC System IEEE Open J. Commun. Soc. Pub Date : 2024-02-14 Awadhesh Gupta, Meesam Jafri, Suraj Srivastava, Aditya K. Jagannatham, Lajos Hanzo
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Securing 5G/6G IoT Using Transformer and Personalized Federated Learning: An Access-Side Distributed Malicious Traffic Detection Framework IEEE Open J. Commun. Soc. Pub Date : 2024-02-14 Yantian Luo, Xu Chen, Hancun Sun, Xiangling Li, Ning Ge, Wei Feng, Jianhua Lu
Malicious traffic has posed a significant threat to current 5G networks. In the upcoming 6G era, with the rapid development of the Internet of Things (IoT), defending against malicious traffic has become even more challenging due to the diverse nature and widespread distribution of IoT devices. This paper presents a new distributed framework for detecting malicious traffic on the access side of the
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Deep Learning Models for Time-Series Forecasting of RF-EMF in Wireless Networks IEEE Open J. Commun. Soc. Pub Date : 2024-02-13 Chi Nguyen, Adnan Ahmad Cheema, Cetin Kurnaz, Ardavan Rahimian, Conor Brennan, Trung Q. Duong
Radio-frequency electromagnetic field (RF-EMF) forecasting plays an important role in the evaluation of regulatory compliance, network planning and system optimization. The knowledge of RF-EMF levels is essential to ensure compliance with standards and avoid public health concerns, especially with the arrival of new frequencies and scenarios in fifth-generation (5G) and sixth generation (6G) wireless
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Security Threats to xApps Access Control and E2 Interface in O-RAN IEEE Open J. Commun. Soc. Pub Date : 2024-02-12 Cheng-Feng Hung, You-Run Chen, Chi-Heng Tseng, Shin-Ming Cheng
Open Radio Access Networks (O-RANs) represent a novel wireless access network architecture that decomposes traditional RAN functions and makes them openly accessible. O-RANs enable real-time coordination, RAN performance optimization, and management through RAN Intelligent Controllers (RICs) and their related xApps. Due to the openness of O-RAN, developers have the flexibility to download various pre-developed
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Semantics-Aware Active Fault Detection in Status Updating Systems IEEE Open J. Commun. Soc. Pub Date : 2024-02-08 George Stamatakis, Nikolaos Pappas, Alexandros Fragkiadakis, Nikolaos Petroulakis, Apostolos Traganitis
With its growing number of deployed devices and applications, the Internet of Things (IoT) raises significant challenges for network maintenance procedures. In this work, we address a problem of active fault detection in an IoT scenario, whereby a monitor can probe a remote device to acquire fresh information and facilitate fault detection. However, probing could significantly impact the system’s energy
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Indoor Measurements for RIS-Aided Communication: Practical Phase Shift Optimization, Coverage Enhancement, and Physical Layer Security IEEE Open J. Commun. Soc. Pub Date : 2024-02-07 Sefa Kayraklik, Ibrahim Yildirim, Ibrahim Hokelek, Yarkin Gevez, Ertugrul Basar, Ali Gorcin
Practical experiments are a crucial step to demonstrate the viability of reconfigurable intelligent surface (RIS)-empowered communication, which is one of the emerging technologies for next-generation networks. In this paper, we present practical measurements to demonstrate the RIS capabilities for enhancing signal coverage and providing physical layer security (PLS) in an indoor environment. First
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AoI-Aware Energy-Efficient SFC in UAV-Aided Smart Agriculture Using Asynchronous Federated Learning IEEE Open J. Commun. Soc. Pub Date : 2024-02-07 Mohammad Akbari, Aisha Syed, W. Sean Kennedy, Melike Erol-Kantarci
In the midst of rising global population and environmental challenges, smart agriculture emerges as a vital solution by integrating advanced technologies to optimize agricultural practices. Through data-driven insights and automation, it tackles the necessity for sustainable resource management, enhancing productivity and resilience in the face of complex food security and ecological concerns. The
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Zeroing Unknown Terms: A Novel Clustering Architecture for Low Network Overhead in Distributed Massive MIMO IEEE Open J. Commun. Soc. Pub Date : 2024-02-06 Supuni Gunasekara, Rajitha Senanayake, Peter Smith, Margreta Kuijper
We propose a novel user-centric clustering architecture for distributed massive multiple-input-multiple-output networks. We examine the uplink of a general multi-cell scenario in which a cluster of base stations (BSs) with large antenna arrays detect the signals of multiple users simultaneously. As opposed to traditional clustering schemes, where the channel coefficients of all the users within the
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Real-Time Network Packet Classification Exploiting Computer Vision Architectures IEEE Open J. Commun. Soc. Pub Date : 2024-02-06 Emilio Paolini, Luca Valcarenghi, Luca Maggiani, Nicola Andriolli
Forthcoming 6G/NextG networks highlight the need for advanced Artificial Intelligence (AI)-based security mechanisms to identify malicious activities and adapt to emerging threats. In this context, the integration of computer vision techniques into the cybersecurity field is promising due to their potential for sophisticated pattern recognition. In this paper we introduce a computationally efficient
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At the Dawn of Generative AI Era: A Tutorial-cum-Survey On New Frontiers in 6G Wireless Intelligence IEEE Open J. Commun. Soc. Pub Date : 2024-02-05 Abdulkadir Celik, Ahmed M. Eltawil
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QoE Prediction for Gaming Video Streaming in O-RAN Using Convolutional Neural Networks IEEE Open J. Commun. Soc. Pub Date : 2024-02-05 Georgios Kougioumtzidis, Atanas Vlahov, Vladimir K. Poulkov, Pavlos I. Lazaridis, Zaharias D. Zaharis
The growing popularity of online and cloud gaming applications is reshaping the landscape of the entertainment industry and acting as a key driver of market growth. However, the dependency of these applications on network resources poses significant challenges to the communication infrastructure. This is particularly critical as network performance plays a key role in influencing user satisfaction
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Semantic Communications for Image-Based Sign Language Transmission IEEE Open J. Commun. Soc. Pub Date : 2024-02-02 Vasileios Kouvakis, Stylianos E. Trevlakis, Alexandros-Apostolos A. Boulogeorgos
Semantic information representation in image-based communication often employs feature vectors, lacking interpretability and posing challenges for human comprehension. This paper addresses this challenge by exploring the reconstruction of original images in the context of American sign language (ASL) transmission. The conventional method involves decoding feature vectors through neural networks, introducing
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Latency-Aware Computation Offloading in Multi-RIS-Assisted Edge Networks IEEE Open J. Commun. Soc. Pub Date : 2024-02-01 An Huang, Long Qu, Maurice J. Khabbaz
Mobile Edge Computing (MEC) has a widely established merit of bringing powerful computing servers to geographically closer locations to computationally limited devices; hence, reducing the task offloading latency from these devices to the servers. However, the frequent communication between devices and edge servers increases the network-wide traffic, therefore, stands in the way of enjoying notable
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Effect of Random Misalignment in the Capacity of Millimeter-Wave OAM IEEE Open J. Commun. Soc. Pub Date : 2024-02-01 Xiangyu Cui, Ki-Hong Park, Mohamed-Slim Alouini
Since the discovery of vortex beams by Allen et al., there has been a growing interest in exploring the applications of orbital angular momentum (OAM) in communication. Among all these researches, especially radio frequency (RF) wireless communication based on OAM should be one of the most promising research topics since the frequency resource is increasingly scarce and OAM can provide us with a new
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Max-Min Throughput Optimization in WPCNs: A Hybrid Active/Passive IRS-Assisted Scheme IEEE Open J. Commun. Soc. Pub Date : 2024-01-30 Iqra Hameed, Insoo Koo
The integration of wireless powered communication network (WPCNs) with intelligent reflecting surface (IRS) technology has emerged as a promising solution for enhancing the energy and spectral efficiency of the network. Recent studies have explored the benefits of active and passive reflecting element surfaces in various networks. However, most existing works on IRS-assisted WPCNs mainly focus on comparing
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Deterministic K-Identification for MC Poisson Channel With Inter-Symbol Interference IEEE Open J. Commun. Soc. Pub Date : 2024-01-29 Mohammad Javad Salariseddigh, Vahid Jamali, Uzi Pereg, Holger Boche, Christian Deppe, Robert Schober
Various applications of molecular communications (MCs) feature an alarm-prompt behavior for which the prevalent Shannon capacity may not be the appropriate performance metric. The identification capacity as an alternative measure for such systems has been motivated and established in the literature. In this paper, we study deterministic K-identification (DKI) for the discrete-time Poisson channel (DTPC)
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Warm and Cold Start Quantum Annealing for Metaverse Resource Optimization IEEE Open J. Commun. Soc. Pub Date : 2024-01-29 Mahzabeen Emu, Salimur Choudhury, Kai Salomaa
Metaverse refers to the intersection of parallel virtual worlds with their physical counterparts by allowing users to interact with virtual people, objects, and environments. Resource allocation in various aspects of Metaverse domains, called as MetaSlices hereinafter, is a crucial optimization research problem. To serve this purpose, we consider a MetaSlice framework with the notion of sharing resources
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AI and 6G Into the Metaverse: Fundamentals, Challenges and Future Research Trends IEEE Open J. Commun. Soc. Pub Date : 2024-01-29 Muhammad Zawish, Fayaz Ali Dharejo, Sunder Ali Khowaja, Saleem Raza, Steven Davy, Kapal Dev, Paolo Bellavista
Since Facebook was renamed Meta, a lot of attention, debate, and exploration have intensified about what the Metaverse is, how it works, and the possible ways to exploit it. It is anticipated that Metaverse will be a continuum of rapidly emerging technologies, usecases, capabilities, and experiences that will make it up for the next evolution of the Internet. Several researchers have already surveyed
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Performance Analysis of Two-Way Relaying in mmWave-Based Aerial Links IEEE Open J. Commun. Soc. Pub Date : 2024-01-26 Heyam F. Hassan, Saud Althunibat, Mohammad Taghi Dabiri, Mazen Hasna, Khalid A. Qaraqe
Two-Way Relaying (TWR) is an efficient relaying technique that doubles the spectral efficiency as compared to the traditional one-way relaying. As such, it has been nominated as a solution to extend the coverage of links operating on the Millimeter Wave (mmWave) band. In this paper, the performance of TWR is investigated for mmWave-based aerial links in which the involved entities are all aerial. Taking
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Generative Deep Learning Techniques for Traffic Matrix Estimation From Link Load Measurements IEEE Open J. Commun. Soc. Pub Date : 2024-01-26 Grigorios Kakkavas, Nikolaos Fryganiotis, Vasileios Karyotis, Symeon Papavassiliou
Traffic matrices (TMs) contain crucial information for managing networks, optimizing traffic flow, and detecting anomalies. However, directly measuring traffic to construct a TM is resource-intensive and computationally expensive. A more practical approach involves estimating the TM from readily available link load measurements, which falls under the category of inferential network monitoring based
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A Flexible Polar Decoding Architecture With Adjustable Latency and Reliability IEEE Open J. Commun. Soc. Pub Date : 2024-01-24 Shintaro Fujiwara, Hideki Ochiai
Future mobile and wireless communications should support various applications with their own reliability and latency requirements. Polar codes, adopted in the 5G standard, are capacity achieving as the codeword length increases even with low complexity successive cancellation (SC) decoding. On the other hand, to improve the performance under relatively short codeword lengths, successive cancellation
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Computation Rate Maximization for Wireless-Powered Edge Computing With Multi-User Cooperation IEEE Open J. Commun. Soc. Pub Date : 2024-01-24 Yang Li, Xing Zhang, Bo Lei, Qianying Zhao, Min Wei, Zheyan Qu, Wenbo Wang
The combination of mobile edge computing (MEC) and radio frequency-based wireless power transfer (WPT) presents a promising technique for providing sustainable energy supply and computing services at the network edge. This study considers a wireless-powered mobile edge computing system that includes a hybrid access point (HAP) equipped with a computing unit and multiple Internet of Things (IoT) devices
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Terahertz Multiple Access: A Deep Reinforcement Learning Controlled Multihop IRS Topology IEEE Open J. Commun. Soc. Pub Date : 2024-01-23 Muhammad Shehab, Mohamed Elsayed, Abdullateef Almohamad, Ahmed Badawy, Tamer Khattab, Nizar Zorba, Mazen Hasna, Daniele Trinchero
We explore THz communication uplink multi-access with multi-hop Intelligent reflecting surfaces (IRSs) under correlated channels. Our aims are twofold: 1) enhancing the data rate of a desired user while dealing with interference from another user and 2) maximizing the combined data rate. Both tasks involve non-convex optimization challenges. For the first aim, we devise a sub-optimal analytical approach
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Communications Security in Industry X: A Survey IEEE Open J. Commun. Soc. Pub Date : 2024-01-19 Ijaz Ahmad, Felipe Rodriguez, Tanesh Kumar, Jani Suomalainen, Senthil Kumar Jagatheesaperumal, Stefan Walter, Muhammad Zeeshan Asghar, Gaolei Li, Nikolaos Papakonstantinou, Mika Ylianttila, Jyrki Huusko, Thilo Sauter, Erkki Harjula
Industry 4.0 is moving towards deployment using 5G as one of the main underlying communication infrastructures. Thus, the vision of the Industry of the future is getting more attention in research. Industry X (InX) is a significant thrust beyond the state-of-the-art of current Industry 4.0, towards a mix of cyber and physical systems through novel technological developments. In this survey, we define
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Resource-Constrained EXtended Reality Operated With Digital Twin in Industrial Internet of Things IEEE Open J. Commun. Soc. Pub Date : 2024-01-19 Hugues M. Kamdjou, David Baudry, Vincent Havard, Samir Ouchani
EXtended Reality (XR) alongside the Digital Twin (DT) in Industrial Internet of Things (IIoT) emerges as a promising next-generation technology. Its diverse applications hod the potential to revolutionize multiple facets of Industry 4.0 and serve as a cornerstone for the rise of Industry 5.0. However, current systems are still not effective in providing a high-quality experience for users due to various
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RIS-Assisted Integrated Sensing and Communication Systems: Joint Reflection and Beamforming Design IEEE Open J. Commun. Soc. Pub Date : 2024-01-15 Mohamed I. Ismail, Abdullah M. Shaheen, Mostafa M. Fouda, Ahmed S. Alwakeel
The Integrated Sensing and Communication (ISAC) system merged with Reconfigurable Intelligent Surface (RIS) has recently received much attention. This paper proposes an intelligent metaheuristic version of Enhanced Artificial Ecosystem Optimizer (EAEO) for a suggested beamforming optimization framework in ISAC systems with RIS. Two RIS are utilized in the presented model to enhance the received signal-to-noise
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Leveraging Edge Computing for Minimizing Base Station Energy Consumption in Multi-Cell (N)OMA Downlink Systems IEEE Open J. Commun. Soc. Pub Date : 2024-01-15 Mateen Ashraf, Taneli Riihonen, Kyung Geun Lee
In this paper, we suggest that the combination of edge computing in the form of data compression with communication at the base stations (BSs) for transmissions to their associated multiple downlink users (DUs) is advantageous for minimizing the total energy consumption. We assume that the individual DUs have minimum rate requirements along with outage probability constraints. Then, we set the resource