Spectrum Handoff Scheme Based on Recommended Channel Sensing Sequence

We consider the spectrum handoff delay of a Secondary User(SU)in cognitive radio networks.We propose a spectrum handoff scheme based on Recommended Channel Sensing Sequence(RCSS),which aims to optimise the spectrum handoff delay subject to the sensing reliability and link maintenance constraints.There are two cases that should be considered:1)the SU performs spectrum handoff successfully during the current frame,and 2)the SU successfully performs the spectrum handoff using several frames.We develop a dynamic programming algorithm for RCSS to identify the optimal sensing sequence for the first case,and an updating algorithm for RCSS to improve the handoff performance for the second case.The numerical results confirm that the proposed RCSS handoff scheme can achieve better handoff delay performance than others when the received signal-to-noise ratios of the Pus' signals on different channels are non-identical.

Enhancing Task Assignment in Crowdsensing Systems Based on Sensing Intervals and Location

The popularity of mobile devices with sensors is captivating the attention of researchers to modern techniques,such as the internet of things(IoT)and mobile crowdsensing(MCS).The core concept behind MCS is to use the power of mobile sensors to accomplish a difficult task collaboratively,with each mobile user completing much simpler micro-tasks.This paper discusses the task assignment problem in mobile crowdsensing,which is dependent on sensing time and path planning with the constraints of participant travel distance budgets and sensing time intervals.The goal is to minimize aggregate sensing time for mobile users,which reduces energy consumption to encourage more participants to engage in sensing activities and maximize total task quality.This paper introduces a two-phase task assignment framework called location time-based algorithm(LTBA).LTBA is a framework that enhances task assignment in MCS,whereas assigning tasks requires overlapping time intervals between tasks and mobile users’tasks and the location of tasks and mobile users’paths.The process of assigning the nearest task to the mobile user’s current path depends on the ant colony optimization algorithm(ACO)and Euclidean distance.LTBA combines two algorithms:(1)greedy online allocation algorithm and(2)bio-inspired traveldistance-balance-based algorithm(B-DBA).The greedy algorithm was sensing time interval-based and worked on reducing the overall sensing time of the mobile user.B-DBA was location-based and worked on maximizing total task quality.The results demonstrate that the average task quality is 0.8158,0.7093,and 0.7733 for LTBA,B-DBA,and greedy,respectively.The sensing time was reduced to 644,1782,and 685 time units for LTBA,B-DBA,and greedy,respectively.Combining the algorithms improves task assignment in MCS for both total task quality and sensing time.The results demonstrate that combining the two algorithms in LTBA is the best performance for total task quality and total sensing time,and the greedy algorithm follows it then B-DBA.

Spatio-temporal Variations in Plantation Forests'Disturbance and Recovery of Northern Guangdong Province Using Yearly Landsat Time Series Observations(1986-2015)

Forest disturbance plays a vital role in modulating carbon storage,biodiversity and climate change.Yearly Landsat imagery from 1986 to 2015 of a typical plantation region in the northern Guangdong province of southern China was used as a case study.A Landsat time series stack(LTSS) was fed to the vegetation change tracker model(VCT) to map long-term changes in plantation forests' disturbance and recovery,followed by an intensive validation and a continuous 27-yr change analysis on disturbance locations,magnitudes and rates of plantations' disturbance and recovery.And the validation results of the disturbance year maps derived from five randomly identified sample plots with 25 km^2 located at the four corners and the center of the scene showed the majority of the spatial agreement measures ranged from 60% to 83%.A confusion matrix summary of the accuracy measures for all four validation sites in Fogang County showed that the disturbance year maps had an overall accuracy estimate of 71.70%.Forest disturbance rates' change trend was characterized by a decline first,followed by an increase,then giving way to a decline again.An undulated and gentle decreasing trend of disturbance rates from the highest value of 3.95% to the lowest value of 0.76% occurred between 1988 and 2001,disturbance rate of 4.51% in 1994 was a notable anomaly,while after 2001 there was a sharp ascending change,forest disturbance rate spiked in 2007(5.84%).After that,there was a significant decreasing trend up to the lowest value of 1.96% in 2011 and a slight ascending trend from 2011 to 2015(2.59%).Two obvious spikes in post-disturbance recovery rates occurred in 1995(0.26%) and 2008(0.41%).Overall,forest recovery rates were lower than forest disturbance rates.Moreover,forest disturbance and recovery detection based on VCT and the Landsat-based detections of trends in disturbance and recovery(LandT rendr) algorithms in Fogang County have been conducted,with LandT rendr finding mostly much more disturbance than VCT.Overall,disturbances and recoveries in northern Guangdong were triggered mostly by timber needs,policies and decisions of the local governments.This study highlights that a better understanding about plantations' changes would provide a critical foundation for local forest management decisions in the southern China.

Reconstruction and transmission of astronomical image based on compressed sensing

In the process of image transmission, the famous JPEG and JPEG-2000 compression methods need more transmission time as it is difficult for them to compress the image with a low compression rate. Recently the compressed sensing（CS） theory was proposed, which has earned great concern as it can compress an image with a low compression rate, meanwhile the original image can be perfectly reconstructed from only a few compressed data. The CS theory is used to transmit the high resolution astronomical image and build the simulation environment where there is communication between the satellite and the Earth. Number experimental results show that the CS theory can effectively reduce the image transmission and reconstruction time. Even with a very low compression rate, it still can recover a higher quality astronomical image than JPEG and JPEG-2000 compression methods.

Adaptive double-threshold energy detection algorithm for cognitive radio

Due to the fact that the conventional spectrum sensing algorithm is susceptible to noise, an adaptive double-threshold energy detection algorithm for a cognitive radio is proposed. Based on double-threshold energy detection, the algorithm can adaptively switch between one-round sensing and two-round sensing by comparing the observations with the pre-fixed thresholds. Mathematical expressions for the probability of detection, the probability of false alarm, and the sensing time are derived. The relationships including signal to noise ratio （SNR） vs. the probability of detection and SNR vs. the sensing time are plotted using Monte Carlo simulation and the algorithm is verified in a real cognitive system based on GNU Radio and universal software radio peripheral （USRP）. Simulation and experimental results show that, compared with the existing spectrum sensing method, the proposed algorithm can achieve a higher probability of detection within a reasonable sensing time.

A performance enhanced Rayleigh Brillouin optical time domain analysis sensing system

Aiming at the problem of large fading noise in Rayleigh Brillouin optical time domain analysis system, a wavelength scanning technique is proposed to enhance the performance of the temperature sensing system. The principle of the proposed technique to reduce the fading noise is introduced based on the analysis of Rayleigh Brillouin optical time domain analysis system. The experimental results show that the signal-to-noise ratio(SNR) at the end of optical fiber with length of 50 m after 17 times wavelength scanning is 5.21 d B higher than that with single wavelength, the Brillouin frequency shift(BFS) on the heated fiber with length of 70 m inserted at the center of sensing fiber can be accurately measured as 0.19 MHz, which is equivalent to a measurement accuracy of 0.19 °C. It indicates that the proposed technique can realize high-accuracy temperature measurement and has huge potential in the field of long-distance and high-accuracy sensing.

A time sequential microfluid sensor with Tesla valve channels

The concentration of biomarkers in sweat can be used to evaluate human health,making efficient sweat sensing a focus of research.While flow channel design is often used to detect sweat velocity,it is rarely incorporated into the sensing of biomarkers,limiting the richness of sensing results.In this study,we report a time sequential sensing scheme for uric acid in sweat through a sequential design of Tesla valve channels.Graphene electrodes for detecting uric acid and directional Tesla valve flow channels were fabricated using laser engraving technology to realize time sequential sensing.The performance of the channels was verified through simulation.The time sequential detection of uric acid concentration in sweat can help researchers improve the establishment of human health management systems through flexible wearable devices.

Energy efficiency optimization of cognitive relay network based on cooperative spectrum sensing

This paper focuses on the energy efficiency of cognitive relay （CR） networks with cooperative sensing, joint optimization of the sensing time and the signal-to-noise ratio （SNR） is studied to maximize the energy efficiency of CR network. Theoretical analysis shows that there exists an optimal sensing time and optimal SNR to make the energy efficiency maximized under a constraint of detection probability. Simulation results illustrate that the optimal fusion rule performs better than the OR rule and the AND rule in terms of the energy efficiency. By properly designing the fusion rule threshold as well as the number of cooperative sensing users, the energy efficiency of CR networks can be further improved.

Spatial and temporal variation of vegetation phenology and its response to climate changes in Qaidam Basin from 2000 to 2015

Based on TIMESAT 3.2 platform, MODIS NDVI data(2000–2015) of Qaidam Basin are fitted, and three main phenological parameters are extracted with the method of dynamic threshold, including the start of growth season(SGS), the end of growth season(EGS) and the length of growth season(LGS). The spatial and temporal variation of vegetation phenology and its response to climate changes are analyzed respectively. The conclusions are as follows:(1) SGS is mainly delayed as a whole. Areas delayed are more than the advanced in EGS, and EGS is a little delayed as a whole. LGS is generally shortened.(2) With the altitude rising, SGS is delayed, EGS is advanced, and LGS is shortened and phenophase appears a big variation below 3000 m and above 5000 m.(3) From 2000 to 2015, the temperature appears a slight increase along with a big fluctuation, and the precipitation increases evidently.(4) Response of phenophase to precipitation is not obvious in the low elevation humid regions, where SGS arrives early and EGS delays; while, in the upper part of the mountain regions, SGS delays and EGS advances with temperature rising, SGS arrives early and EGS delays with precipitation increasing.