Weighted Algebraic Connectivity Maximization for Optical Satellite Networks

Zheng, Yongxing; Zhao, Shanghong; Liu, Yun; Li, Yongjun; Tan, Qinggui; Ning, Xin

doi:10.1109/access.2017.2697818

Cited by 16 publications

(5 citation statements)

References 18 publications

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“…The usage of FPGA-based systems in the telecommunication industry is widespread, with typical applications in the development of general transmission decoders [16,17], video decoders [18,19], security approaches like parity checks [20,21], satellite issues [22,23], and digital TV systems [24]. The modern usage of those devices includes machine learning proposals [25], cloud computing [26], and 5G communication networks [27].…”

Section: Related Workmentioning

confidence: 99%

Hardware Update through Digital TV Signals

et al. 2021

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This paper presents a new hardware reconfiguration approach named hardware reconfiguration through digital television (HARD), which can update FPGA hardware modules based on digital TV (DTV) signals. Such a scheme allows several synthesized hardware cores (bitstreams) signaled and broadcast through open DTV signals via data streaming to be identified, acquired, decoded, and then used for system updates. Reconfiguration data are partitioned, encapsulated into private sections, and then sent in a carrousel fashion in order to be recovered by modified receivers. Service information content, specially designed for identifying and describing the characteristics of multiplexed hardware bitstreams, was added to the transmitted signal and provided all necessary information in the traditional DTV style. The receiver framework, in turn, checked whether those characteristics corresponded to its embedded reconfigurable devices and, if a match was found, it reassembled the related bitstreams and reconfigured the respective internal circuits. Experiments performed with an implementation of the proposed methodology confirmed its feasibility and showed that remounting and reconfiguration times were satisfactory and presented no blocking aspect. Finally, HARD can be used in several designs regarding intelligent reconfigurable devices, minimize device costs in the long term, and provide better hardware reuse.

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Section: Related Workmentioning

confidence: 99%

Hardware Update through Digital TV Signals

et al. 2021

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“…This predictability can be used to calculate the inter‐satellite visibility and distance, which are important to our model. The corresponding methods are experienced, so we will not discuss how to calculate the dynamic distance L s of constellation s , and simply take the results as algorithmic parameters …”

Section: System Modelmentioning

confidence: 99%

A tradeoff resource allocation based on MF‐TDMA scheme in the multibeam data relay satellite systems

Wang

Zhao

et al. 2018

Satell Commun Network

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A tremendous increase in the number of distributed satellite constellations with the unscheduled burst data traffic will impose addition and diverse requirements on the DRS (data relay satellite) systems, which increases the complexity for beam management and affects a real-time data return and acquisition. In this paper, we suggested that a large capacity can be achieved by a multibeam DRS system based on multifrequency time division multiple access scheme providing multiaccess for the distributed satellite constellations. Because the space-based information network is characterized by the limited on-board resources, a highly dynamic topology and time-varying intersatellite links, we designed a 2-stage dynamic optimization approach to separate the multiobjective optimization for frequency/time blocks and power, aiming at the rapidly converging to the optimal solution and at the same time meeting the fairness resource allocation. In particular, a capacity-fairness tradeoff algorithm is proposed based on hybrid the enhanced genetic algorithm and the particle swarm optimization.Simulation results show that the tradeoff between maximizing total capacity and providing proportional fairness allocation is well balanced. The proposed algorithm can rapidly converge to adapt to the highly dynamic topology in data relay satellite systems. KEYWORDS data relay satellite systems, space-based information networks, multiple beams, resource allocation, satellite communications, proportional fairness 1 | INTRODUCTION Space-based information network (SBIN) with the cooperation scheme of the data relay satellite (DRS) systems have a significant role of achieving a real-time data return and acquisition for mission satellites in the low-earth orbit (LEO) or medium-earth orbit, which can offer an uninterrupted coverage and greatly improve monitoring capabilities. 1,2 The traditional on-board beam management technique 3 has been deployed in a DRS to schedule data packets from the DRS to a single satellite. In recent years, the distributed satellite constellation 4 contributes innovative applications (such as disaster prevention and mitigation, military reconnaissance, and removal of space debris) by replacing a single large satellite with several very capable spacecrafts, which opens the door to new applications. 5It can be predicted that a tremendous increase in the number of distributed satellite constellations will impose addition and very diverse requirements on the SBIN. More specially, far more stringent latency and greater capacity requirements are expected to support the real-time data interaction between the distributed satellite constellations, such as the proximity operations and cooperative communications. The different distributed satellite constellations with the unscheduled burst data traffic increase the complexity for beam management, which presents a new challenge for the DRS systems. To tackle the challenges aforementioned above, the multibeam DRS system 6 is ideally suited to deploy such a network as described. The ...

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“…One major challenge in such a framework is the design of iterative algorithms based on local data that allow to reach a common decision, and the concept of consensus is used as a primary tool from various scientific communities [2]. This topic has been investigated with a large effort from researchers of several diverse fields for its impact on several technological areas, ranging from the electric grid and microgrids control [3], [4] distributed signal processing [5], formation control of vehicles and devices [6], robotic networks [7], and several applications of distributed Artificial Intelligence [1], [8].…”

Section: Introductionmentioning

confidence: 99%

Laplacian Eigenvalue Allocation Through Asymmetric Weights in Acyclic Leader-Follower Networks

Parlangeli

2023

IEEE Access

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This paper tackles the eigenvalue allocation problem through an appropriate choice of the edge weights for the class of combinatorially-symmetric Laplacian matrices of acyclic graphs, namely Laplacian matrices showing symmetric zero/nonzero values in its entries according to a tree graph pattern. The mathematical setting of the problem is remarkably suited for several current multi-agent systems engineering applications, when the communication graph is bidirectional but each agent can set the weight of each incoming neighbor value. The resulting algorithm is inherently iterative and it requires a finite time execution, so that it is well fit for real-world applications as a preliminary routine. For this reason, a special focus is devoted to a distributed implementation of the main algorithm. As a final theoretical result, it is proved that, under the strict interlacing property, the solution is positive, and the algorithm can be iterated. An illustrative example closes the paper, showing how the algorithm works in practice.

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Weighted Algebraic Connectivity Maximization for Optical Satellite Networks

Cited by 16 publications

References 18 publications

Hardware Update through Digital TV Signals

Hardware Update through Digital TV Signals

A tradeoff resource allocation based on MF‐TDMA scheme in the multibeam data relay satellite systems

Laplacian Eigenvalue Allocation Through Asymmetric Weights in Acyclic Leader-Follower Networks

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