Delay and Reliability of Load-Based Listen-Before-Talk in LAA

© 2013 IEEE. With the release of the 5 GHz unlicensed spectrum has emerged licensed-Assisted access, in which long-Term evolution (LTE) operators compete with Wi-Fi users for a share of the unlicensed spectrum so as to augment their licensed spectrum. Subsequently, there has been the need to develop a LTE channel access mechanism that enables harmonious coexistence between Wi-Fi and LTE. Load-based listen-before-Talk (LB-LBT) has been adopted as this LTE channel access mechanism by the 3rd Generation Partnership Project (3GPP). Theoretical modelling of LB-LBT schemes has focused on throughput and fair channel-Time sharing between Wi-Fi and LTE technologies. We explore a LB-LBT scheme that belongs to LBT category 4, as recommended by the 3GPP, and develop a model for the distribution of the medium access control (MAC) delays experienced by the Wi-Fi packets and LTE frames. The model, validated by simulations, reveals design insights that can be used to dynamically adjust the LB-LBT parameters not only to achieve channel-Time fairness, but also to guarantee MAC-delay bounds, with specified probability

Harmonising Coexistence of Machine Type Communications with Wi-Fi Data Traffic under Frame-Based LBT

© 1972-2012 IEEE. The existence of relatively long LTE data blocks within the licensed-assisted access (LAA) framework results in bursty machine-type communications (MTC) packet arrivals, which cause system performance degradation and present new challenges in Markov modeling. We develop an embedded Markov chain to characterize the dynamic behavior of the contention arising from bursty MTC and Wi-Fi data traffic in the LAA framework. Our theoretical model reveals a high-contention phenomenon caused by the bursty MTC traffic, and quantifies the resulting performance degradation for both MTC and Wi-Fi data traffic. The Markov model is further developed to evaluate three potential solutions aiming to alleviate the contention. Our analysis shows that simply expanding the contention window, although successful in reducing congestion, may cause unacceptable MTC data loss. A TDMA scheme instead achieves better MTC packet delivery and overall throughput, but requires centralized coordination. We propose a distributed scheme that randomly spreads the MTC access processes through the available time period. Our model results, validated by simulations, demonstrate that the random spreading solution achieves a near TDMA performance, while preserving the distributed nature of the Wi-Fi protocol. It alleviates the MTC traffic contention and improves the overall throughput by up to 10%

Recent Breakthroughs on Angle-of-Arrival Estimation for Millimeter-Wave High-Speed Railway Communication

© 2019 IEEE. With significantly improved efficiency, largescale hybrid antenna arrays with tens to hundreds of antennas have great potential to support millimeter-wave (mmWave) communication for high-speed railway (HSR) applications. The significant beamforming gains rely on fast and accurate estimation of the angle-of-arrival (AoA), but this can be impeded by the high train speed, the cost/energy oriented design of arrays, and the severe attenuation of mmWave signals. This article reviews these challenges, and discusses the limitations of existing AoA estimation techniques under hybrid antenna array settings. The article further reveals a few recent theoretical breakthroughs that can potentially enable fast and reliable estimation, even based on severely attenuated signals. Under a speed setting of 500 km/h, a performance study is carried out to confirm the significant improvements of estimation accuracy and subsequent beamforming gains as the results of the breakthroughs

Group-based susceptible-infectious-susceptible model in large-scale directed networks

© 2019 Xu Wang et al. Epidemic models trade the modeling accuracy for complexity reduction. This paper proposes to group vertices in directed graphs based on connectivity and carries out epidemic spread analysis on the group basis, thereby substantially reducing the modeling complexity while preserving the modeling accuracy. A group-based continuous-time Markov SIS model is developed. The adjacency matrix of the network is also collapsed according to the grouping, to evaluate the Jacobian matrix of the group-based continuous-time Markov model. By adopting the mean-field approximation on the groups of nodes and links, the model complexity is significantly reduced as compared with previous topological epidemic models. An epidemic threshold is deduced based on the spectral radius of the collapsed adjacency matrix. The epidemic threshold is proved to be dependent on network structure and interdependent of the network scale. Simulation results validate the analytical epidemic threshold and confirm the asymptotical accuracy of the proposed epidemic model

A higher-level MRP supertree of placental mammals

BACKGROUND: The higher-level phylogeny of placental mammals has long been a phylogenetic Gordian knot, with disagreement about both the precise contents of, and relationships between, the extant orders. A recent MRP supertree that favoured 'outdated' hypotheses (notably, monophyly of both Artiodactyla and Lipotyphla) has been heavily criticised for including low-quality and redundant data. We apply a stringent data selection protocol designed to minimise these problems to a much-expanded data set of morphological, molecular and combined source trees, to produce a supertree that includes every family of extant placental mammals. RESULTS: The supertree is well-resolved and supports both polyphyly of Lipotyphla and paraphyly of Artiodactyla with respect to Cetacea. The existence of four 'superorders' – Afrotheria, Xenarthra, Laurasiatheria and Euarchontoglires – is also supported. The topology is highly congruent with recent (molecular) phylogenetic analyses of placental mammals, but is considerably more comprehensive, being the first phylogeny to include all 113 extant families without making a priori assumptions of suprafamilial monophyly. Subsidiary analyses reveal that the data selection protocol played a key role in the major changes relative to a previously published higher-level supertree of placentals. CONCLUSION: The supertree should provide a useful framework for hypothesis testing in phylogenetic comparative biology, and supports the idea that biogeography has played a crucial role in the evolution of placental mammals. Our results demonstrate the importance of minimising poor and redundant data when constructing supertrees

Attack and Defence of Ethereum Remote APIs

© 2018 IEEE. Ethereum, as the first Turing-complete blockchain platform, provides various application program interfaces for developers. Although blockchain has highly improved security, faulty configuration and usage can result in serious vulnerabilities. In this paper, we focus on the security vulnerabilities of the official Go-version Ethereum client (geth). The vulnerabilities are because of the insecure API design and the specific Ethereum wallet mechanism. We demonstrate attacks exploiting these vulnerabilities in an Ethereum testbed. The vulnerabilities are confirmed by the scanning results on the public Internet. Finally, corresponding countermeasures against attacks are provided to enhance the security of the Ethereum platform

Novel Plasmonic Nanocavities for Optical Trapping-Assisted Biosensing Applications

Plasmonic nanocavities have proved to confine electromagnetic fields into deep subwavelength volumes, implying their potentials for enhanced optical trapping and sensing of nanoparticles. In this review, the fundamentals and performances of various plasmonic nanocavity geometries are explored with specific emphasis on trapping and detection of small molecules and single nanoparticles. These applications capitalize on the local field intensity, which in turn depends on the size of plasmonic nanocavities. Indeed, properly designed structures provide significant local field intensity and deep trapping potential, leading to manipulation of nano-objects with low laser power. The relationship between optical trapping-induced resonance shift and potential energy of plasmonic nanocavity can be analytically expressed in terms of the intercavity field intensity. Within this framework, recent experimental works on trapping and sensing of single nanoparticles and small molecules with plasmonic nanotweezers are discussed. Furthermore, significant consideration is given to conjugation of optical tweezers with Raman spectroscopy, with the aim of developing innovative biosensors. These devices, which take the advantages of plasmonic nanocavities, will be capable of trapping and detecting nanoparticles at the single molecule level