With the rapid development of marine activities, there has been an increasing number of Internet-of-Things (IoT) devices on the ocean. This leads to a growing demand for high-speed and ultrareliable ...maritime communications. It has been reported that a large performance loss is often inevitable if the existing fourth-generation (4G), fifth-generation (5G), or satellite communication technologies are used directly on the ocean. Hence, conventional theories and methods need to be tailored to this maritime scenario to match its unique characteristics, such as dynamic electromagnetic propagation environments, geometrically limited available base station (BS) sites and rigorous service demands from mission-critical applications. Toward this end, we provide a survey on the demand for maritime communications enabled by state-of-the-art hybrid satellite-terrestrial maritime communication networks (MCNs). We categorize the enabling technologies into three types based on their aims: 1) enhancing transmission efficiency; 2) extending network coverage; and 3) provisioning maritime-specific services. Future developments and open issues are also discussed. Based on this discussion, we envision the use of external auxiliary information, such as sea state and atmosphere conditions, to build up an environment-aware, service-driven, and integrated satellite-air-ground MCN.
Two Algorithms for the k-Widest Path Problem Gomes, Teresa; Martins, Lúcia; Craveirinha, José M. F. ...
Journal of network and systems management,
07/2023, Letnik:
31, Številka:
3
Journal Article
Recenzirano
In communication networks where services require a certain amount of bandwidth for setting up a connection, an important problem (to be referred to as the
k
-widest path problem) is to enumerate ...paths in non-increasing order of the bandwidth availability of the paths. For this problem, a path follows a non-additive, concave cost property. Notably, this problem parallels the
k
-shortest path problem for which the path cost is additive. We present two exact algorithms for solving this problem, denoted by kWP-1 and kWP-2, inspired by the loopless version of MPS (Martins–Pascoal–Santos) algorithm and Yen’s algorithm for the
k
-shortest path algorithm, respectively. Our numerical study shows that kWP-2 is more effective than kWP-1 for the
k
-widest path problem, in contrast with the relatively better performance of MPS over Yen’s algorithm regarding the enumeration of
k
-shortest paths.
Autonomous driving like subsequent generation cyber-physical system (CPS) with present improvement of wireless communication network, here is a substantial necessity of big data analyzes along ...greater accurateness and lower delay. Nevertheless, obtainable researches fail to discourse few challenges like adversarial attacks, centralized control, safety and secrecy. For overcome these issues, Blockchain espoused Adaptive multi-scale dual attention network with Quaternion fractional order Meixner moments for Cyber security in Wireless Communication Network (BC-CS-AMSDAN-QFOMM-WCN
)
is proposed in this manuscript. First, Adaptive multi-scale dual attention network (AMSDAN) approach is presented at the edge layer and mitigate the challenges in the cloud layer. The AMSDAN is built on a block chain environment to alleviate the triple main defies that is encryption, decryption, Mining and Generation of Block. In Encryption phase, every node in a wireless communication network is allotted a public and private key with the help of Quaternion fractional order Meixner moments (QFOMM). In Decryption phase, the digital signature is decrypted into messages through sender’s public key. Mining and Generation of Block, a green proof of work mechanism is used to upgrading safety of transacted data. The proposed approach are implemented in Ethereum and Solidity programming language also this efficacy is evaluated through particular performances matrices, such as response time, CPU time, block creation time, delay, sensitivity, throughput, energy efficiency, computational cost, and accuracy. Then the performance of the proposed BC-CS-AMSDAN-QFOMM-WCN method provides 23.31%, 11.03%, 27.89% higher throughput and 36.51%, 13.09%, 22.24% minimum delay compared with existing method like Blockchain Based Privacy Preserving Framework for Emerging 6G Wireless Communications (BC-CS-B-RAN-WCN), Blockchain and Machine Learning for Wireless Communications and Networking Systems (BC-CS-DAG-ML-WCN) and Blockchain-Based Spectrum Sharing Transactions for Multi-Operators Wireless Communication Networks (BC-CS-SS-TSS-WCN) respectively.
A review of technological solutions and advances in the framework of a Vertical Heterogeneous Network (VHetNet) integrating satellite, airborne and terrestrial networks is presented. The disruptive ...features and challenges offered by a fruitful cooperation among these segments within a ubiquitous and seamless wireless connectivity are described. The available technologies and the key research directions for achieving global wireless coverage by considering all these layers are thoroughly discussed. Emphasis is placed on the available antenna systems in satellite, airborne and ground layers by highlighting strengths and weakness and by providing some interesting trends in research. A summary of the most suitable applicative scenarios for future 6G wireless communications are finally illustrated.
Path planning has been a hot and challenging field in unmanned aerial vehicles (UAV). With the increasing demand of society and the continuous progress of technologies, UAV communication networks ...(UAVCN) are also flourishing. The mobility of UAV nodes allows for flexible network deployment, but some challenges are brought, such as power constraints, throughput, cost, and time efficiency. Therefore, path planning is significant for UAVCN. This article presents a review of UAVCN path planning. We first introduce the network structure and performance evaluation of UAVCN. We then investigate the generic UAV path planning algorithms and the path planning algorithms in UAVCN. In this article, the advantages and disadvantages of each path planning algorithm and the functional problems. The challenges faced in path planning for UAVCN, the solutions, state-of-the-art, and representative results are also presented. In addition, we illustrate future research directions for UAVCN path planning as well, which can provide some help to researchers.
Load frequency control (LFC) of modern power systems tends to employ open communication networks to transmit measurement/control signals. Under a limited network bandwidth, the continuous and ...high-sampling-rate signal transmission will be prone to degradation of the LFC performance through network congestion. This brief proposes a decentralized control performance standards (CPSs)-oriented event-triggered (ET) LFC scheme for power systems under constrained communication bandwidth. The proposed scheme comprises the ET LFC scheme and the CPSs-oriented regulation scheme. In the CPSs-oriented regulation scheme, regulation rules are designed to adjust the threshold parameter of the ET LFC scheme based on the North American Electrical Reliability Council (NERC)'s CPS1 and CPS2. The rules generate a larger threshold parameter to lower the triggering frequency in order to reduce unnecessary transmission of measurement/control signals, while ensuring the frequency and tie-lie power of the power systems to meet the required CPS1 and CPS2 instead of the asymptotic stability requirement in the existing research. The reduced transmission of these signals lessens the communication burden. In addition, the decentralized control strategy is used to solve the problems of poor large scalability and computational dimension caused by the centralized control strategy. The effectiveness of the proposed scheme is evaluated on an IEEE 39-bus test system with renewable energy sources.
This paper studies optimal resource allocation in the wireless-powered communication network (WPCN), where one hybrid access point (H-AP) operating in full duplex (FD) broadcasts wireless energy to a ...set of distributed users in the downlink (DL) and, at the same time, receives independent information from the users via time-division multiple access in the uplink (UL). We design an efficient protocol to support simultaneous wireless energy transfer (WET) in the DL and wireless information transmission (WIT) in the UL for the proposed FD-WPCN. We jointly optimize the time allocations to the H-AP for DL WET and different users for UL WIT and the transmit power allocations over time at the H-AP to maximize the users' weighted sum rate of UL information transmission with harvested energy. We consider both the cases with perfect and imperfect self-interference cancellation (SIC) at the H-AP, for which we obtain optimal and suboptimal time and power allocation solutions, respectively. Furthermore, we consider the half-duplex (HD) WPCN as a baseline scheme and derive its optimal resource allocation solution. Simulation results show that the FD-WPCN outperforms the HD-WPCN when effective SIC can be implemented and more stringent peak power constraint is applied at the H-AP.
Intelligent reflecting surface (IRS) is expected to be an important enabling technology for future wireless communication networks due to its capacity for reconfiguring wireless propagation ...environments. In this article, we consider a multiuser communication system for wireless powered communication network (WPCN) with IRS assistance. To overcome the low-quality communication problem of remote Internet of Things (IoT) devices in WPCN, we propose a multiobjective optimization scheme for IRS-assisted WPCN to optimize jointly throughput and remaining energy of remote IoT devices. We present a multiobjective optimization problem by jointly designing the hybrid access point (HAP) transmit beamforming, HAP receive beamforming, IRS phase shift beamforming, the IoT device transmit power, and energy-harvesting (EH)/information transmission (IT) time allocation to maximize system throughput and remaining energy. To address the aforementioned multiobjective optimization problem, the original optimization problem is first transformed into a Markov game model, and then, a multiobjective optimization scheme based on a multiagent deep deterministic policy gradient (MADDPG) is proposed. We centrally train the MADDPG model offline, and the two optimization objectives throughput and remaining energy are abstracted as two agents to execute decisions online. According to the results of the simulation, the multiobjective optimization scheme based on multiagent reinforcement learning can guarantee the performance of WPCN and enhance the throughput and remaining energy overall.
With the gradual growth of natural gas units, the coupling between power networks and natural gas networks has deepened, and the synergistic operation between them has become more and more important. ...At the same time, the integration of uncertain renewable energy brings challenges to the economic and safe operation of power and natural gas interconnected systems. In order to cope with the operational risks brought by uncertain wind sources to the interconnected system, this paper adopts the method of distributionally robust chance constraints, where an ambiguity set related to the moment information of a small amount of historical wind power forecast error data is attained in a data-driven way. Then the chance constrained problem is transformed into a formation that is easily solved. For different situations with or without a central coordinator of the two entities of electricity and gas, this work respectively gives the solution steps based on the relaxed alternating direction method of multipliers. In the case of no coordinator, this paper particularly presents the convergence performance when the exchange of information has a packet loss rate during iterative calculation processes. The simulation results show that compared with the method of traditional Gaussian chance constrained optimization and symmetrical distributionally robust chance constrained optimization, the moment-based distributionally robust chance constrained optimization can achieve a lowest probability of chance constraint violation at the expense of energy dispatch costs. In addition, compared with the traditional alternating direction method of multipliers, the relaxed alternating direction method of multipliers can achieve the nearly same energy dispatch costs with a smaller number of iterations. It is also found that the packet loss of the early iteration process may be the main factor that has a degradation impact on the convergence process rather than the nominal loss probability.
•The distributional robustness of wind power forecast errors is analyzed.•Distributed and decentralized optimization architecture is presented.•Different relaxed alternating direction methods of multipliers are developed.•Lossy communication is considered in the iteration of decentralized optimization.
This paper studies an unmanned aerial vehicle (UAV)-enabled wireless powered communication network (WPCN), in which a UAV is dispatched as a mobile access point (AP) to serve a set of ground users ...periodically. The UAV employs the radio frequency (RF) wireless power transfer (WPT) to charge the users in the downlink, and the users use the harvested RF energy to send independent information to the UAV in the uplink. Unlike the conventional WPCN with fixed APs, the UAV-enabled WPCN can exploit the mobility of the UAV via trajectory design, jointly with the wireless resource allocation optimization, to maximize the system throughput. In particular, we aim to maximize the uplink common (minimum) throughput among all ground users over a finite UAV's flight period, subject to its maximum speed constraint and the users' energy neutrality constraints. The resulted problem is nonconvex and thus difficult to be solved optimally. To tackle this challenge, we first consider an ideal case without the UAV's maximum speed constraint, and obtain the optimal solution to the relaxed problem. The optimal solution shows that the UAV should successively hover above a finite number of ground locations for downlink WPT, as well as above each of the ground users for uplink communication. Next, we consider the general problem with the UAV's maximum speed constraint. Based on the above multilocation-hovering solution, we first propose an efficient successive hover-and-fly trajectory design, jointly with the downlink and uplink wireless resource allocation, and then propose a locally optimal solution by applying the techniques of alternating optimization and successive convex programming (SCP). Numerical results show that the proposed UAV-enabled WPCN achieves significant throughput gains over the conventional WPCN with fixed-location AP.
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