The COVID-19 related lockdown measures offer a unique opportunity to understand how changes in economic activity and traffic affect ambient air quality and how much pollution reduction potential can the society offer ...
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With an ever-increasing interests and demands in Near-Space, more and more researchers have put their attentions on this field, leading to an emerging needs for modeling the 20-100km altitude space especially for broa...
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With an ever-increasing interests and demands in Near-Space, more and more researchers have put their attentions on this field, leading to an emerging needs for modeling the 20-100km altitude space especially for broadband communications. Among the lots of works, Media Access Control (MAC) undoubtedly has chief importance and urgency with which communicating objects or nodes can effectively access to Near-Space. However, previous MAC designs mainly focus their attentions on service differentiation by application purposes without considering nodal mobility. In fact, access control for nodes with different mobility levels has significantly influences to MAC performance and is complex and difficult to be implemented together with present MAC protocols. In this paper, we first presented a location method for Near-Space vehicles such as airships and unmanned planes and then modeled the mobile networks infrastructure with mobility considered. For determining the vehicles joining/leaving events locally, we quantify the communication range with Received Signal Strength Indicator (RSSI) aid. Then, for better managing the nodes access to the Near-Space with aforementioned works, we designed a TDMA based reservation MAC protocol to guarantee the servicedelay and networks coverage with best efforts. Simulation results showed that our proposed model better fit for Near-Space mobile communication environments and presented a lower delay and higher coverage regarding to different mobility levels.
作者:
Erlebach, ThomasFiala, JiříETH Zürich
Computer Engineering and Networks Lab. CH-8092 Zürich Switzerland Charles University
Department of Applied Mathematics Institute for Theoretical Computer Science Malostranské nám. 2/25 118 00 Prague Czech Republic
This chapter surveys on-line and approximation algorithms for the maximum independent set and coloring problems on intersection graphs of disks. It includes a more detailed treatment of recent upper and lower bounds o...
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The internal link loss characteristic inference has become an increasingly important issue for operating and evaluating a wireless sensor network. Due to the inherent stringent bandwidth and energy constraints, it is ...
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Tone injection (TI) mitigates the high peak-to-average power ratio problem without incurring data rate loss or extra side information. However, optimal TI requires an exhaustive search over all possible constellations...
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Tone injection (TI) mitigates the high peak-to-average power ratio problem without incurring data rate loss or extra side information. However, optimal TI requires an exhaustive search over all possible constellations, which is a hard optimization problem. In this paper, a novel TI scheme that uses the clipping noise to find the optimal equivalent constellations is proposed. By minimizing the mean error of the clipping noise and possible constellation points, the proposed scheme easily determines the size and position of the optimal equivalent constellations. The proposed scheme achieves significant PAPR reduction while maintaining low complexity.
Tactical communication networking faces complexity, heterogeneity, and reliability requirements. The emerging research area of cognitive networks offers a potential for dealing with these problems. A key feature of co...
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Tactical communication networking faces complexity, heterogeneity, and reliability requirements. The emerging research area of cognitive networks offers a potential for dealing with these problems. A key feature of cognitive networks is the knowledge base, which is produced during the process of learning and responsible for the decision making. We propose a cognitive network model integrated with the knowledge base, which is a primary part of cognitive networks. And then we focus on the construction of the knowledge base and the expression form of the knowledge in the model. In this paper, we use the Bayesian Network (BN) to construct the knowledge base, which is a unique tool for creating a representation of the dependence relationships among network protocol parameters. The data structure of the dependence relationships of the BN is translated into the knowledge which is expressed by the probability. In the simulation experiments, we create the BN through the sampling data to construct the knowledge base using the mathematical tool MATlab.and prove the efficiency of our cognitive network model for optimizing network performance in the OPENT simulation platform.
We study optimal operating conditions for 160-Gb/s signals traversing a slow-light delay line based on parametric amplification. Six phase modulated formats are investigated, including CSRZ, PAP-CSRZ, GAP-CSRZ, RZ duo...
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In this paper, we discuss the performance of the affine projection CM algorithm, which can deal with the cases that the input signals are correlated and decrease the filtering error. We describe the derivation of algo...
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Located in the stratospheric layer of Earth's atmosphere, high altitude platform station (HAPS) is a promising network infrastructure, which can bring significant advantages to sixth-generation (6G) and beyond wir...
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The internal link loss characteristic inference has become an increasingly important issue for operating and evaluating a wireless sensor network. Due to the inherent stringent bandwidth and energy constraints of sens...
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The internal link loss characteristic inference has become an increasingly important issue for operating and evaluating a wireless sensor network. Due to the inherent stringent bandwidth and energy constraints of sensors, it is usually impractical to directly monitor each node or link in wireless sensor network. We consider the problem of inferring the internal link loss characteristics from passive end-to-end measurement in this paper. Specifically, the link loss performance inference during the data aggregation is considered. Under the assumptions that the link losses are mutually independent, we elab.rate a bias corrected link loss Cumulant Generating Function (CGF) algorithm. The simulation results show that the internal link loss CGF can be inferred accurately comparable to the sampled internal link loss CGF. At the end of this paper, we apply the result of internal link loss CGF inference to identify the lossy link in sensor network.
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