Resource Allocation for Physical Layer Security in Heterogeneous Network with Hidden Eavesdropper

The tremendous performance gain of heterogeneous networks(Het Nets) is at the cost of complicated resource allocation. Considering information security, the resource allocation for Het Nets becomes much more challenging and this is the focus of this paper. In this paper, the eavesdropper is hidden from the macro base stations. To relax the unpractical assumption on the channel state information on eavesdropper, a localization based algorithm is first given. Then a joint resource allocation algorithm is proposed in our work, which simultaneously considers physical layer security, cross-tier interference and joint optimization of power and subcarriers under fairness requirements. It is revealed in our work that the considered optimization problem can be efficiently solved relying on convex optimization theory and the Lagrangian dual decomposition method is exploited to solve the considered problem effectively. Moreover, in each iteration the closed-form optimal resource allocation solutions can be obtained based on the Karush-Kuhn-Tucker(KKT) conditions. Finally, the simulation results are given to show the performance advantages of the proposed algorithm.

Collective Background Extraction for Station Market Area by Using Location Based Social Network

Half centuries of follow-up survey has enabled the architects and urban planners to design rationally by the aid of planning Nonetheless, limitation has occurred at planning because city has been changing its utility in accordance with its users＇ demand. In this paper, the authors proposed a method to analyze trait of users in market areas near stations by analyzing location based social network. After the datum collection from geotagged tweets, these GPS （global positioning system） datum were plotted to map attained from yahoo open location platform. Then the morphological analysis and terminology extraction system extracted the keywords and their scores. After calculating the distance from stations and users＇ GPS coordination, the authors extracted the array of keywords and corresponding scores in some station market area. Lastly, ratios of all users＇ scores and city＇s scores were calculated to examine the locality. Full combination of data collection, natural language processing and visualization enabled the authors to envisage distribution of collective background in city.

Recommending Personalized POIs from Location Based Social Network

Location based social networks（ LBSNs） provide location specific data generated from smart phone into online social networks thus people can share their points of interest（ POIs）. POI collections are complex and can be influenced by various factors,such as user preferences,social relationships and geographical influence. Therefore,recommending new locations in LBSNs requires to take all these factors into consideration. However,one problem is how to determine optimal weights of influencing factors in an algorithm in which these factors are combined. The user similarity can be obtained from the user check-in data,or from the user friend information,or based on the different geographical influences on each user＇s check-in activities. In this paper,we propose an algorithm that calculates the user similarity based on check-in records and social relationships,using a proposed weighting function to adjust the weights of these two kinds of similarities based on the geographical distance between users. In addition,a non-parametric density estimation method is applied to predict the unique geographical influence on each user by getting the density probability plot of the distance between every pair of user＇s check-in locations. Experimental results,using foursquare datasets,have shown that comparisons between the proposed algorithm and the other five baseline recommendation algorithms in LBSNs demonstrate that our proposed algorithm is superior in accuracy and recall,furthermore solving the sparsity problem.

LLSDA: Design and Implementation of Lightning Location Data Analysis and Visualization

Visualizing lightning location data is necessary in analyzing and researching lightning activity patterns.This article uses C#and the cross-platform.NET framework to develop a lightning location data analysis class library and the data-driven client to help lightning researchers improve work efficiency by avoiding repeated wheel invention.Lightning Location System Data Analyzer(LLSDA)is a suite of software tools that includes a.NET class library for software developers and a desktop application for end users.It supports a wide range of lightning location data formats,such as the University of Washington Global Lightning Location System(WWLLN)and Beijing Huayun Dongfang ADTD Lightning Location System data format,and maintains scalability.The class library can easily read,parse,and analyze lightning location data,and combined with third-party frameworks can realize grid analysis.The desktop application can be combined with MeteoInfo(a GIS open-source project)for secondary development.

Application of Wireless Network Positioning Technology Based on GPS in Geographic Information Measurement

Based on the analysis of the advantages and disadvantages of GPS positioning system in practical application,this paper proposes the combination of wireless network positioning technology and GPS positioning system to overcome the low accuracy of GPS positioning system in the case of occlusion.This paper introduces in detail the principle of the application of wireless network positioning technology based on GPS positioning system in geographic information measurement,and illustrates its practical application in production by taking coal mine positioning as an example.

Study on the Precise Location of the Xinjiang Yutian M_S7.3 Earthquake

The seismic waveform of the Yutian Ms7. 3 earthquake, Xinjiang on February 12, 2014 was recorded clearly and completely by the Digital Seismic Networks of Xinjiang, Qinghai, Tibet, and Xinjiang Hotan array, so the method of joint location by regional seismic network and seismic array can be used to accurately determine the earthquake source location. The following technologies were used in the process of location： （ 1 ） We selected seismic stations equally located around the epicenter of the Ms 7. 3 earthquake with an average interval of about 15 degrees in the initial location. （2） The recording waveforms of Yutian seismic station were rotated to the radial and tangential directions to precisely obtain the arrival time of S-waves to determine the epicentral distance. （ 3） The velocity model was used in the determination of location of the epicenter, based on the historical records of earthquakes in the area within a radius of 1.0 ° from the source as the center, and the velocity model is obtained after re-fitting and calibration. （4） Based on the waveform records of the Hotan seismic array, the method of waveform beaming was used to determine the azimuths and perform the correction of the epicenter location with these azimuths. （5） The deterministic method was used to measure the source depth. Finally, it is concluded that the Yutian Ms 7. 3 main shock hypocenter location is 36. 197°N, 82. 467°E, focal depth 12km and original time 17：19：48. 2 μm. February 12, 2014.

Experimental study on location accuracy of a 3D VHF lightning-radiation-source locating network

This paper reports the investigation of the location accuracy of a three-dimensional （3D） lightning-radiation-source locating system using sounding balloon measurements. By comparing the information from the balloon-borne VHF transmitter flight path and locations using simple geometric models, the location uncertainties of sources both over and outside the network were estimated. For radiation sources inside the network and below an altitude of 7 km, the horizontal uncertainty was 12-48 m and the total mean value was 21 m （rms）, and the vertical uncertainty was 20-78 m and the total mean value was 49 m （rms）. Outside the network, the location uncertainties increased with distance. The geometric model showed that range and altitude errors increased as a function of the range squared whereas the range errors increased parabolically with distance, and that was confirmed by the covariance calculation results. The standard deviation was used inside the network and covariance was used outside the network. The results indicated that location errors from a simple geometric model exhibited good agreement with standard experimental data. The geometry of the network, set of measurements, and calculation method were verified as suitable. The chi-square values of the least squares goodness of fit algorithm were verified and the timing error （A/rms） Of the fitting formula was estimated. The distribution of the chi-square values was less than 5, corresponding to a timing error of 50-66 ns （rms）.

A Novel Routing Strategy to Provide Source Location Privacy in Wireless Sensor Networks

In order to secure the source location privacy when information is sent back to the base station in wireless sensor network, we propose a novel routing strategy which routes the packets to the base station through three stages： directional random routing, h-hop routing in the annular region and the shortest path routing. These stages provide two fold protections to prevent the source location from being tracked down by the adversary. The analysis and simulation results show that proposed scheme, besides providing longer safety period, can significantly reduce energy consumption compared with two baseline schemes.

Probability-based Clustering and Its Application to WLAN Location Estimation

Wireless local area networks (WLAN) localization based on received signal strength is becoming an important enabler of location based services. Limited efficiency and accuracy are disadvantages to the deterministic location estimation techniques. The probabilistic techniques show their good accuracy but cost more computation overhead. A Gaussian mixture model based on clustering technique was presented to improve location determination efficiency. The proposed clustering algorithm reduces the number of candidate locations from the whole area to a cluster. Within a cluster, an improved nearest neighbor algorithm was used to estimate user location using signal strength from more access points. Experiments show that the location estimation time is greatly decreased while high accuracy can still be achieved.

Detecting and Locating Failures in Communication Networks

The connectivity of a strongly connected network may be destroyed after link damage.Since many net- works are connected by directed links,the reachability may be restored by altering the direction of one or more of the links and thus reconfigoring the network.The location of the failed link must first be determined.In this paper,we examine new methods to determine the location of failed links and nodes in networks.A routing test approach is proposed and the conditions under which communication networks may be tested are discussed. Finally,an adaptive algorithm and a heuristic algorithm that can locate a single failed llnk or a single failed node are presented.