Interference-constrained adaptive simultaneous spectrum sensing and data transmission scheme for unslotted cognitive radio network

Cognitive radio (CR) is widely recognized as a novel approach to improve the spectrum efficiency. However, there exists one problem needed to be resolved urgently, that is the two conflicting goals in CR network: one is to minimize the interference to primary (licensed) system; the other is to maximize the throughput of secondary (unlicensed) system. Meanwhile, the secondary user (SU) has to monitor the spectrum continuously to avoid the interference to primary user (PU), thus the throughput of the secondary system is affected by how often and how long the spectrum sensing is performed. Aiming to balance the two conflicting goals, this article proposes a novel Interference-Constrained Adaptive Simultaneous spectrum Sensing and data Transmission (ICASST) scheme for unslotted CR network, where SUs are not synchronized with PUs. In the ICASST scheme, taking advantage of the statistic information of PU's activities, the data transmission time is adaptively adjusted to avoid the interference peculiar to unslotted CR network; the operation of spectrum sensing is moved to SU receiver from SU transmitter to increase the data transmission time and hence improve the throughput of SU. Simulation results validate the efficiency of ICASST scheme, which significantly increases the throughput of secondary system and decreases the interference to PU simultaneously. © 2012 Yang et al

Distributed Robust Learning-Based Backstepping Control Aided with Neurodynamics for Consensus Formation Tracking of Underwater Vessels

This paper addresses distributed robust learning-based control for consensus formation tracking of multiple underwater vessels, in which the system parameters of the marine vessels are assumed to be entirely unknown and subject to the modeling mismatch, oceanic disturbances, and noises. Towards this end, graph theory is used to allow us to synthesize the distributed controller with a stability guarantee. Due to the fact that the parameter uncertainties only arise in the vessels' dynamic model, the backstepping control technique is then employed. Subsequently, to overcome the difficulties in handling time-varying and unknown systems, an online learning procedure is developed in the proposed distributed formation control protocol. Moreover, modeling errors, environmental disturbances, and measurement noises are considered and tackled by introducing a neurodynamics model in the controller design to obtain a robust solution. Then, the stability analysis of the overall closed-loop system under the proposed scheme is provided to ensure the robust adaptive performance at the theoretical level. Finally, extensive simulation experiments are conducted to further verify the efficacy of the presented distributed control protocol

Anti-noise-folding regularized subspace pursuit recovery algorithm for noisy sparse signals

© 2014 IEEE. Denoising recovery algorithms are very important for the development of compressed sensing (CS) theory and its applications. Considering the noise present in both the original sparse signal x and the compressive measurements y, we propose a novel denoising recovery algorithm, named Regularized Subspace Pursuit (RSP). Firstly, by introducing a data pre-processing operation, the proposed algorithm alleviates the noise-folding effect caused by the noise added to x. Then, the indices of the nonzero elements in x are identified by regularizing the chosen columns of the measurement matrix. Afterwards, the chosen indices are updated by retaining only the largest entries in the Minimum Mean Square Error (MMSE) estimated signal. Simulation results show that, compared with the traditional orthogonal matching pursuit (OMP) algorithm, the proposed RSP algorithm increases the successful recovery rate (and reduces the reconstruction error) by up to 50% and 86% (35% and 65%) in high noise level scenarios and inadequate measurements scenarios, respectively

The superflares of soft Gamma-ray repeatres: giant quakes in solid quark stars?

Three times of supergiant flares from soft $\gamma$-ray repeatres are observed, with typical released energy of $\sim 10^{44-47}$ erg. A conventional model (i.e., the magnetar model) for such events is catastrophic magnetism-powered instability through magnetohydrodynamic process, in which a significant part of short-hard $\gamma$-ray bursts could also be the results of magnetars. Based on various observational features (e.g., precession, glitch, thermal photon emission) and the underlying theory of strong interaction (quantum chromodynamics, QCD), it could not be ruled out yet that pulsar-like stars might be actually solid quark stars. Strain energy develops during a solid star's life, and starquakes could occur when stellar stresses reach a critical value, with huge energy released. An alternative model for supergiant flares of soft $\gamma$-ray repeatres is presented, in which energy release during a star quake of solid quark stars is calculated. Numerical results for spherically asymmetric solid stars show that the released gravitational energy during a giant quake could be as high as $10^{48}$ erg if the tangential pressure is slightly higher than the radial one. Difficulties in magnetar models may be overcome if AXPs/SGRs are accreting solid quark stars with mass $\sim (1-2)M_\odot$.Comment: Extensive discussions are presented, with a new figure added to show the change of mass and radius of accreting quark star

Susceptibility indicator for chiral topological orders emergent from correlated fermions

Chiral topological orders formed in correlated fermion systems have been widely explored. However, the mechanism on how they emerge from interacting fermions is still unclear. Here, we propose a susceptibility condition. Under this condition, we show that chiral topological orders can spontaneously take place in correlated fermion systems. The condition leads to a low-energy effective theory of bosons with strong frustration, mimicking the flat band systems. The frustration then melts the long-range orders and results in topological orders with time-reversal symmetry breaking. We apply the theory to strongly-correlated semiconductors doped to the metallic phase. A novel excitonic topological order with semionic excitations and chiral excitonic edge state is revealed, which goes beyond the common knowledge that excitonic phases are generally formed in semimetals or semiconductors. These results demonstrate an unprecedented indicator for chiral topological orders, which bridges the existing gap between interacting fermions and correlated topological matter.Comment: 20 pages, 4 figure

Discriminant Projective Non-Negative Matrix Factorization

Projective non-negative matrix factorization (PNMF) projects high-dimensional non-negative examples X onto a lower-dimensional subspace spanned by a non-negative basis W and considers W-T X as their coefficients, i.e., X approximate to WWT X. Since PNM

Room temperature gas sensing properties of SnO₂/multiwall-carbon-nanotube composite nanofibers

Author name used in this publication: Shuncheng Lee2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Distributed Neurodynamics-Based Backstepping Optimal Control for Robust Constrained Consensus of Underactuated Underwater Vehicles Fleet

Robust constrained formation tracking control of underactuated underwater vehicles (UUVs) fleet in three-dimensional space is a challenging but practical problem. To address this problem, this paper develops a novel consensus based optimal coordination protocol and a robust controller, which adopts a hierarchical architecture. On the top layer, the spherical coordinate transform is introduced to tackle the nonholonomic constraint, and then a distributed optimal motion coordination strategy is developed. As a result, the optimal formation tracking of UUVs fleet can be achieved, and the constraints are fulfilled. To realize the generated optimal commands better and, meanwhile, deal with the underactuation, at the lower-level control loop a neurodynamics based robust backstepping controller is designed, and in particular, the issue of "explosion of terms" appearing in conventional backstepping based controllers is avoided and control activities are improved. The stability of the overall UUVs formation system is established to ensure that all the states of the UUVs are uniformly ultimately bounded in the presence of unknown disturbances. Finally, extensive simulation comparisons are made to illustrate the superiority and effectiveness of the derived optimal formation tracking protocol.Comment: This paper is accepted by IEEE Transactions on Cybernetic

Impacts of Potential China's Environmental Protection Tax Reforms on Provincial Air Pollution Emissions and Economy

China's environmental protection tax (EPT) has been implemented since the beginning of 2018 to control environmental issues (e.g., air pollution). The current EPT law indicates that tax revenues are given to provincial governments without return. However, tax revenue redistribution is the key to achieving a so‐called “double dividend”; that is, an environmental tax could benefit both the environment and economic efficiency. Based on our previous analysis of the effectiveness of the current EPT, we further explore whether the double dividend could be achieved under different tax reforms based on the multiregion and multisectoral computable general equilibrium model. We find that recycling the EPT revenue to reduce household income tax (EPT_Int) is an efficient way to achieve the double dividend, and there is no double dividend if the EPT revenue is compensated by reducing enterprise income tax (EPT_Ent) or by investing in solar power (EPT_Sol). Combining EPT_Int and EPT_Sol could be a better approach if more air pollution emissions reductions are required to achieve the national reduction targets. At the provincial level, recycling the EPT revenues to reduce household income tax could offset the negative effect of environmental tax on the economy and achieve the double dividend in all provinces, especially the provinces with higher emission intensity, such as Shanxi, Hebei, Inner Mongolia, and Guizhou Provinces. This result shows that provinces with high emission intensity may further reduce air pollutant emissions during the post‐EPT era