Airborne Communication Networks: A Survey Cao, Xianbin; Yang, Peng; Alzenad, Mohamed ...
IEEE journal on selected areas in communications,
09/2018, Letnik:
36, Številka:
9
Journal Article
Recenzirano
Odprti dostop
Owing to the explosive growth of requirements of rapid emergency communication response and accurate observation services, airborne communication networks (ACNs) have received much attention from ...both industry and academia. ACNs are subject to heterogeneous networks that are engineered to utilize satellites, high-altitude platforms (HAPs), and low-altitude platforms (LAPs) to build communication access platforms. Compared to terrestrial wireless networks, ACNs are characterized by frequently changed network topologies and more vulnerable communication connections. Furthermore, ACNs have the demand for the seamless integration of heterogeneous networks such that the network quality-of-service (QoS) can be improved. Thus, designing mechanisms and protocols for ACNs poses many challenges. To solve these challenges, extensive research has been conducted. The objective of this special issue is to disseminate the contributions in the field of ACNs. To present this special issue with the necessary background and offer an overall view of this field, three key areas of ACNs are covered. Specifically, this paper covers LAP-based communication networks, HAP-based communication networks, and integrated ACNs. For each area, this paper addresses the particular issues and reviews major mechanisms. This paper also points out future research directions and challenges.
Blockchain is a shared distributed digital ledger technology that can better facilitate data management, provenance and security, and has the potential to transform healthcare. Importantly, ...blockchain represents a data architecture, whose application goes far beyond Bitcoin - the cryptocurrency that relies on blockchain and has popularized the technology. In the health sector, blockchain is being aggressively explored by various stakeholders to optimize business processes, lower costs, improve patient outcomes, enhance compliance, and enable better use of healthcare-related data. However, critical in assessing whether blockchain can fulfill the hype of a technology characterized as 'revolutionary' and 'disruptive', is the need to ensure that blockchain design elements consider actual healthcare needs from the diverse perspectives of consumers, patients, providers, and regulators. In addition, answering the real needs of healthcare stakeholders, blockchain approaches must also be responsive to the unique challenges faced in healthcare compared to other sectors of the economy. In this sense, ensuring that a health blockchain is 'fit-for-purpose' is pivotal. This concept forms the basis for this article, where we share views from a multidisciplinary group of practitioners at the forefront of blockchain conceptualization, development, and deployment.
Network Routing: Algorithms, Protocols, and Architectures, Second Edition explores network routing and how it can be broadly categorized into Internet routing, PSTN routing, and telecommunication ...transport network routing. The book systematically considers these routing paradigms, as well as their interoperability, discussing how algorithms, protocols, analysis, and operational deployment impact these approaches and addressing both macro-state and micro-state in routing. Readers will learn about the evolution of network routing, the role of IP and E.164 addressing and traffic engineering in routing, the impact on router and switching architectures and their design, deployment of network routing protocols, and lessons learned from implementation and operational experience. Numerous real-world examples bring the material alive.
Bridges the gap between theory and practice in network routing, including the fine points of implementation and operational experienceRouting in a multitude of technologies discussed in practical detail, including, IP/MPLS, PSTN, and optical networkingPresents routing protocols such as OSPF, IS-IS, BGP in detailDetails various router and switch architecturesDiscusses algorithms on IP-lookup and packet classificationAccessible to a wide audience with a vendor-neutral approach
In this paper, the problem of energy efficient transmission and computation resource allocation for federated learning (FL) over wireless communication networks is investigated. In the considered ...model, each user exploits limited local computational resources to train a local FL model with its collected data and, then, sends the trained FL model to a base station (BS) which aggregates the local FL model and broadcasts it back to all of the users. Since FL involves an exchange of a learning model between users and the BS, both computation and communication latencies are determined by the learning accuracy level. Meanwhile, due to the limited energy budget of the wireless users, both local computation energy and transmission energy must be considered during the FL process. This joint learning and communication problem is formulated as an optimization problem whose goal is to minimize the total energy consumption of the system under a latency constraint. To solve this problem, an iterative algorithm is proposed where, at every step, closed-form solutions for time allocation, bandwidth allocation, power control, computation frequency, and learning accuracy are derived. Since the iterative algorithm requires an initial feasible solution, we construct the completion time minimization problem and a bisection-based algorithm is proposed to obtain the optimal solution, which is a feasible solution to the original energy minimization problem. Numerical results show that the proposed algorithms can reduce up to 59.5% energy consumption compared to the conventional FL method.
Understanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. We construct a database of ...interactions among ligands, receptors and their cofactors that accurately represent known heteromeric molecular complexes. We then develop CellChat, a tool that is able to quantitatively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Through manifold learning and quantitative contrasts, CellChat classifies signaling pathways and delineates conserved and context-specific pathways across different datasets. Applying CellChat to mouse and human skin datasets shows its ability to extract complex signaling patterns. Our versatile and easy-to-use toolkit CellChat and a web-based Explorer ( http://www.cellchat.org/ ) will help discover novel intercellular communications and build cell-cell communication atlases in diverse tissues.
The emerging non-orthogonal multiple access (NOMA) technology can effectively improve the throughput performance of Internet of Things (IoT) devices. Besides throughput maximization, ensuring ...throughput fairness is a practical design issue when implementing NOMA in wireless powered communication networks (WPCN). To this end, we investigate the joint transmission time and power allocation problem for NOMA communication, aiming to improve the sum-throughput while guaranteeing different wireless devices' (WDs') throughput in multi-cell WPCN. In particular, we first analyze the feasibility of the problem by deriving the necessary and sufficient conditions for the existence of feasible solutions and propose an efficient algorithm to obtain the set of feasible values of transmission time allocation. We then propose an efficient algorithm for the transmission time allocation to improve the sum-throughput. During each search iteration, we adopt the successive convex approximation (SCA) approach to transform the non-convex power allocation problem into a sequence of convex problems and obtain the locally optimal transmit power under a fixed transmission time. Numerical simulations show that the proposed algorithm can improve the sum-throughput while guaranteeing each WD's throughput.
This paper proposes a distributed hierarchical cooperative control strategy for a cluster of islanded microgrids (MGs) with intermittent communication, which can regulate the frequency/voltage of all ...distributed generators (DGs) within each MG as well as ensure the active/reactive power sharing among MGs. A droop-based distributed secondary control scheme and a distributed tertiary control scheme are presented based on the iterative learning mechanics, by which the control inputs are merely updated at the end of each round of iteration, and thus, each DG only needs to share information with its neighbors intermittently in a low-bandwidth communication manner. A two-layer sparse communication network is modeled by pinning one or some DGs (pinned DGs) from the lower network of each MG to constitute an upper network. Under this control framework, the tertiary level generates the frequency/voltage references based on the active/reactive power mismatch among MGs while the pinned DGs propagate these references to their neighbors in the secondary level, and the frequency/voltage nominal set points for each DG in the primary level can be finally adjusted based on the frequency/voltage errors. Stability analysis of the two-layer control system is given, and sufficient conditions on the upper bound of the sampling period ratio of the tertiary layer to the secondary layer are also derived. The proposed controllers are distributed, and thus, allow different numbers of heterogeneous DGs in each MG. The effectiveness of the proposed control methodology is verified by the simulation of an ac MG cluster in Simulink/SimPower Systems.
At present, psychological barriers are widespread in physical education, and all physical education teachers need to solve this issue. The emergence of wireless communication networks and new ...interactive devices have a significant influence on multimodal human–computer interaction, which has become a prominent area of research. In this paper, we analyze the psychological obstacles in sports by leveraging mobile intelligent information systems (MIIS) within the wireless communication networks. The paper begins by introducing the reasons and background of sports psychological barriers, then examines and summarizes existing academic research on sports psychological barriers and mobile intelligent information systems. Subsequently, the paper presents a comprehensive summary in conjunction with computer vision’ multimodal learning for human–computer interaction. Furthermore, an algorithm is proposed, and various algorithms are analyzed for sports’ psychological barriers within the framework of mobile intelligent information systems. The paper also includes a factor analysis of sports psychological obstacles within the mobile intelligent information system. Finally, various experiments are conducted and the results are summarized and discussed. The experimental findings indicate a 4% improvement in the effectiveness of using mobile intelligent information systems for addressing sports psychological disorders compared to traditional methods. The utilization of multimodal human interaction extends to diverse domains of learning and daily life. Leveraging multimodal interaction technology and virtual reality technology in developing new interactive applications holds the potential to enhance the convenience and naturalness of human–computer interaction.
Wireless communication in the TeraHertz band (0.1-10 THz) is envisioned as one of the key enabling technologies for the future sixth generation (6G) wireless communication systems scaled up beyond ...massive multiple input multiple output (Massive-MIMO) technology. However, very high propagation attenuations and molecular absorptions of THz frequencies often limit the signal transmission distance and coverage range. Benefited from the recent breakthrough on the reconfigurable intelligent surfaces (RIS) for realizing smart radio propagation environment, we propose a novel hybrid beamforming scheme for the multi-hop RIS-assisted communication networks to improve the coverage range at THz-band frequencies. Particularly, multiple passive and controllable RISs are deployed to assist the transmissions between the base station (BS) and multiple single-antenna users. We investigate the joint design of digital beamforming matrix at the BS and analog beamforming matrices at the RISs, by leveraging the recent advances in deep reinforcement learning (DRL) to combat the propagation loss. To improve the convergence of the proposed DRL-based algorithm, two algorithms are then designed to initialize the digital beamforming and the analog beamforming matrices utilizing the alternating optimization technique. Simulation results show that our proposed scheme is able to improve 50% more coverage range of THz communications compared with the benchmarks. Furthermore, it is also shown that our proposed DRL-based method is a state-of-the-art method to solve the NP-hard beamforming problem, especially when the signals at RIS-assisted THz communication networks experience multiple hops.
PDF
