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In this paper, we theoretically and numerically analyze the time delay and corresponding issues for the novel category of Internet of things control system. At present, the Internet of things technology progress and mature, people also gradually combine control system and Internet connection and make them to give full play to their strengths. Internet of things has great innovation in goods intelligent network, and the general Internet of things in the motion control system has a great development space, the future of control system is applied to the large number of the wireless fieldbus and sensor networks. To overcome the severe issues of the IOT system denoted as the time delay, we conduct research from following perspectives. (1) The control system modelling and analysis. Compared in the actual control system in an event-driven clock driver has many advantages such as when the controller equipment or setting of event-driven actuators equipment. (2) The time delay analysis with mathematical modelling. Due to the signal delay, controller cannot receive timely feedback information of the object which will seriously affect the dynamic performance of the remote control system. Complex math model is proposed to deal with the issues. In the final part, we numerically simulation the proposed model and theory compared with other famous methods, the result indicates that the proposed method obtain better performance and feasibility.

It is generally known that network simulator is a program used to verify new or existing network architecture and its activities. Basically network simulator helps to implement the virtual part of network research. This has save a lot of cost on analysis as the results of a network simulator is very close to real network cases. In recent researches, new models and prototypes are introduced to enable latest technologies support on network simulators. Some well-known network simulators are NS2, NS3, OMNET++ and QUALNET. As network research continues to grow rapidly, there is a need to analyze the supports and services offered by each network simulators. The objective of this paper is to investigate and analyze these network simulators in term of network mobility supports. This is because network mobility management has become a crucial topic in networking research. In selecting the right network simulators, issues such as CPU utilization, memory usage, computation time, feasibility, scalability and affordability need to be wisely studied. Using qualitative analysis this paper highlights the strengths and the limitations of these network simulators. The qualitative evaluations of these simulators are hereby presented.

Testing direction and relative distance nearest to test position of environmental field intensity are analyzed using simulating calculation, taking three-dimensional cube good conductor as general test equipment, under vertical incidence of single plane wave, the effect of electrical size of the test equipment on test point selection is analyzed; incident angle of plane wave is transformed to calculate an relative error between selected position field intensity and environmental field intensity in oblique incidence condition so as to meet the demand of the experiment; and then promote it to reverberation chamber which is distributed as superposed field of multiple columns plane wave, make an analytical calculation on relative error , which can be controlled within 3%, of selected test point to satisfy the experimental requirements, and it can be applied to practical test.

For subnanosecond low intensity of wireless network signal with representative Beidou Satellite navigation signal is difficult to obtain accurate time estimation and Angle estimation in the positioning, and easy to be affected by environmental noise, which made its positioning accuracy not higher, this paper proposed a parameter estimation method based on low intensity wireless network receiving signal spectrum. By sampling approach, first sampling launch signal as multidimensional independent sub-signal and modeling independently, through constructing noise space and sub-single space to obtain TOA estimation accurately based on the orthogonalization of corresponding column vector; then using complex domain mapping, on the basis of obtained TOA estimation, to obtain DOA estimation with contrast way accurately. Finally, it conducted accuracy analysis of the proposed parameter estimation method. Test data showed that: compared with PM algorithm, ESPRIT algorithm, the proposed technique was more accurate on TOAand DOA estimation; and in case of low strength of signal and serious background noise, the proposed method can still be effective to maintain the precision of parameters estimation. The technology can effectively reduce the influence of background noise on the signal transmission, has strong practical deployment significance.

This paper proposes a vehicle-positioning improvement algorithm that utilizes positioning data collected from budget GPS devices and vehicle data obtained from ODB devices and relays the information via WAVE communications between cars. Data from both sender and recipient vehicles are matched with Procrustes analysis based on the location in-formation of the other car. The corrected location data is used in order to calculate the distance be-tween the two cars. By using commercial lane-detection technology, the distance between the cars and each lane can also be calculated with the calibrated location data. The difference between the cars’ video-estimated distance and GPS data can be used to improve vehicle-location correction algorithms.

Cooperative multiple input multiple outputs (MIMO) or its variation cooperative multiple input single outputs (MISO) is becoming a potential technique to minimize the energy consumption and prolong lifetime in wireless sensor networks. For cluster based wireless sensor networks, cluster lifetime for cooperative beamforming (CBF) based cooperative MISO scheme is studied in this paper.We first establish the energy model of a cluster with cooperative MISO scheme based on CBF. Based on the energy consumption model, the effects of cluster size and distance between cluster and sink node on the performance of cluster lifetime are discussed, an joint optimization to maximize cluster lifetime by finding the optimal modulation parameter and number of cooperative nodes is proposed. Numerical results show that CBF based cooperative MISO scheme can achieve longer cluster lifetime compare with STBC and the joint optimization can further improve the cluster lifetime.

Big data introduced several novel opportunities for many organizations worldwide. Big data technologies are now available for businesses of all scales and the organizations are adopting them increasingly to capitalize on various business gains. In this era of growing projects globally, big data is not only assisting in information exchange but also bringing convenience for communication management in large scale projects. This study assesses the level of awareness of communication management professionals regarding Big Data technologies and analyzes the contribution of different factors responsible for the rate of adoption of big data technologies for communication management in large projects. The study is based on online surveys and interviews of different organizations and the academia. The findings show that, among others, fear of job loss is a major hindrance while the enhanced information mobility is the major accelerator towards the adoption of big data technologies for communication management. It further establishes that unawareness of the professionals towards big data technologies plays a negative role in their acceptance.

A Radio Environment Map (REM) maps its geolocation information to the propagation characteristics as complementary information for an adaptive communication of cognitive radio (CR). In this paper we propose a novel theoretical three dimension (3D) Multiple Input Multiple Output (MIMO) channel model. The proposed model parameterizes the geolocation information of interacting obstacles referred as scatterers. An efficient response distribution function (ERDF) is developed to interpolate the array response for an arbitrary scatterer location. It is shown that the mutual information of the proposed model is consistent with a conventional geometry-based model with the lower simulation time. It allows us to generate channels with all possible scatterer distribution on the surface of a building effectively.

In opportunistic networks, selfish nodes will refuse to forward messages for others to save their precious resources such as bandwidth, buffer and energy, and the system performance will degrade significantly. Therefore, it is necessary to motivate the selfish nodes to cooperatively forward messages. However, current cooperation mechanisms for opportunistic networks mainly focus on encouraging nodes to participate in message forwarding, but fail to consider the node congestion problem. When many messages are forwarded to the nodes with high connection degree, these nodes will become congested and discard most messages, which will seriously degrade the routing performance. To stimulate the selfish nodes with limited buffer to cooperatively forward messages, this paper proposes a congestion-aware node cooperation mechanism based on double auction, called CANCMDA. In CANCMDA, nodes first determine the self congestion degree according to current free buffer and message receiving speed. Then, combining message delivery probability and congestion degree, nodes trade messages based on double auction model. The double auction trade process is a bayesian game, and nodes get the optimal bid by solving the bayesian equilibrium to trade messages. The experimental results show that CANCMDA can effectively stimulate selfish nodes to cooperatively forward messages when congested, and achieves higher message delivery ratio with lower overhead ratio, compared with other mechanisms.

In this paper, we considered the received signal of the wideband CDMA systems using turbo code in the multipath channel environments, and analyze the performance of the system. This study is to analyze the performance for the variable system bandwidth according to the number of branches of rake receiver by passing the received signal through a rake receiver with a turbo code in Rayleigh fading channel environments. For the design of receiver in wideband CDMA systems, we presented the efficient parameters for the number of iterative decoding and the number of branches of rake receiver.

In this paper, we conduct research on issues related to the primary features of the Internet of things system and the corresponding data communication characteristics based on sparse coding and joint deep neural network. Internet of things is more than the underlying device difference communication method and it is the Internet of things needs to study in the field of hot issue. Using traditional algorithm for Internet communication equipment need particle filter was carried out on the acquisition of communication signal processing. Communication technology enables the Internet of things will perceive the information between different terminals for efficient transmission and exchange, exchange and sharing and the information resources is the key to the functions of things. To enhance the robustness and efficiency of the current IOT systems, we adopt the sparse coded dictionary learning theory to detect the size of the data and optimize the compressive sensing technique to modify the resolution. With the advances of the deep neural network, we analyze the topology of the system network structure and extract the pattern features and characteristics to make the signal transmission process more quickly and feasible. To enhance the objective function, we obtain the restricted optimization algorithm to help terminate the iteration for the higher efficiency. In the final part, we simulation our algorithm for times compared with other well-performed approaches. The result indicates that our method outperforms both in the accuracy layer an in the time-consuming layer which will hold specific meaning.

Oil debris signals are applied to monitor lubricant oil conditions and fault diagnosis of a wind turbine. However, the signals will be influenced by the vibration of transmission mechanism and background noise, hence false alarms and undetected particles will limit sensors ability in examining fine particles in oil debris. This paper presents an approach to enhance the performance of oil debris signals. The de-noising of signals used a wavelet filtering to remove the vibration of a wind turbine, and then set a threshold to remove the background noise which caused by the system of measurement. The effectiveness of this enhanced measurement system is tested by using simulated and experimental signals.

In addition to fixed sensor network such as crop cultivation management system, studies on mobile sensor network have been actively conducting, which is used for collecting information from the moving objects like livestock and cars with use of sensors. The mobility of node enables to prolong the lifespan of network and to manage network efficiently through equal allocation of energy among nodes. To ensure efficient mobility, it is required to make a functional change to MAC layer and routing protocol. In particular, an enhanced transmission mechanism is essential in order to effectively control a link discontinuity or an increase of traffic overhead caused by the mobility of node. This paper aims to propose an energy-efficient transmission mechanism using distance information between sensors in mobile sensor network. Performance of the proposed mechanism has been evaluated by simulation. The simulation results indicate that the proposed mechanism outperforms traditional minimum hop routing method from the perspective of several performance indicators including average packet latency, average energy consumption and network lifespan.

Energy efficiency is one of the primary performance parametersin wireless sensor network (WSN). The data collected by neighboring nodesin the high density WSN tend to have a high correlation which isdirectly transmitted to the sink node (DGN) will seriously reduce the energy efficiency of wireless sensor networks.For improving the energy efficiency of high node density WSN, We introduce distributed source coding (DSC) which can compress the high correlation source data into WSNbased on virtual MIMO. In the simulationresults indicate thatDSC can effectively reduce the energy consumption in data transmission and improve the energy efficiencyof the whole WSN.

Underwater wireless sensor networks are widely used in environmental monitoring and a variety of applications. However, underwater wireless sensor networks should be handled carefully because they have inherent disadvantages, such as long propagation delay in the acoustic signal and low-bandwidth. If using existing protocols for a terrestrial wireless network in an underwater network, performance decreases significantly, so there is a need for a new protocol. This study aims to improve performance that is reduced by a long wait time after a request to send/clear to send (RTS/CTS) transmission in the MAC protocol handshake. By utilizing the wait time after transmitting a packet, sending packets that can be transferred to a neighbor Node Can provide better performance. Experimental results show that end-to-end delay and throughput performance are significantly improved, compared to the existing well-known protocol.

In this paper, the challenging problem of train localization is investigated. Precise localization of rail vehicles is a key element for development of more efficient and safe operation of high-speed railway. The localization task is formulated in a 3GPP LTE-based framework that enables us to derive the Doppler frequency offset of moving train, by exploitation of positioning reference signal (PRS) placed in the subframe, in Ricean channel. Then, a PRS-oriented train position approach is proposed. The PRS time difference of arrival from positioning references eNB1 and eNB2, is calculated by sequences cross correlation, and the train running curve is determined by inquiring about the line database of track section. Finally, the train position is evaluated by combining the information of PRS time difference of arrival and the train’s moving trajectory. In the simulation, the localization performance is well demonstrated, when two types of railway alignments, i.e., straight line and circle curve, are considered.

Signal sparse matrix structure, the degree of relationship between signal sparse representation, which affect application of compression perception to the effect of recovery reconstruction for signal. In order to solve this problem, a variety of dictionary learning algorithm such as KSVD, OLM (Online dictionary learning method) should be put forward. These algorithms used overlapping image blocks to build a dictionary, produced a large number of sparse coefficients, resulting in a fitting and calculation too slowly, and cannot ensure convergence. Based on this, it designed a fast dictionary learning algorithm based on proximal gradient. Algorithm based on the analysis of proximal gradient multiple, on the basis of convex optimization problem, applied to the dictionary learning involved in solving optimization, reduce the complexity of each iteration, reduces the iterative overhead, at the same time to ensure the convergence. Experiments on synthetic data show that the proposed algorithm dictionary learning speed, the time is short, and obtain a better dictionary.

In this paper design of Microstrip band-reject filters have been presented for different dielectric materials on L-band applications. The various designs have also been compared with different dielectric constants and other performance parameters to check for viability and stability of designs on the considered frequency band. IE3D 14.1 simulation tool has been used for obtaining the Insertion loss and return loss performance of microstrip filter.

Many wireless channels encountered in practice tend to exhibit the structure of sparse multipath due to large bandwidth or large number of antennas. High-rate data wireless communications over multipath wireless channels usually require that the channel response be known at the receiver. In this paper, a novel scheme for the estimation of sparse wireless channels is developed. The initial estimation of the channel taps is obtained by the unstructured least-squares (LS) method. Then, the presence of a channel tap is detected via an improved threshold obtained by applying the nature of sparse channels and the statistics of the noise vector. At last, the channel estimate is refined by deploying the knowledge previously acquired on the position of the nonzero taps and the structured LS method. The proposed method is compared and contrasted with the existing sparse estimation methods. And the results show the validity of the proposed method.

Based on low energy consumption and high privacy protection required by range query in two-level wireless sensor network, this paper proposes a kind of secure probabilistic range query (SPRQ). SPRQ is made up of data encryption, prefix member verification and probabilistic neighbor verification and spate query and transmission process. It can ensure completing range query without disclosing privacy. The analysis and simulation result indicate that compared with other safety agreement, SPRQ has lower energy consumption when it ensures the safety of range query.

Broadcasting is the simplest way to send a message from one node to all the other nodes in a network. Simple flooding is the simplest form of broadcasting that provides important control, route discovery, and network information update functionality for unicast and multicast protocols. However, simple flooding generates too many broadcast message duplications in networks. The Minimizing Re-Transmissions (MRT) approach has been developed to reduce broadcast duplication in ad hoc wireless networks by minimizing the number of retransmitting nodes based on the network topology information. While MRT is one of the most efficient broadcasting techniques for ad hoc wireless networks, when MRT is applied for wired networks, it still generates broadcast duplication in the networks. In this paper, we develop a variant of MRT for wired networks called MRT for wired networks (wMRT) to completely remove broadcast duplication in wired networks. In addition to minimizing the number of retransmitting nodes, wMRT also minimizes the number of retransmitting ports of each node in wired networks. This results in no broadcast duplication in wired networks. The traffic performance of wMRT is analyzed, evaluated, and compared to that of the simple flooding and MRT techniques. Simulations are conducted using the OMNeT++ simulation tool in order to validate the traffic performance analysis. The analyzed and simulated results show that the wMRT completely removes broadcast duplication in wired networks, thus saving a significant amount of network bandwidth, as well as improving network traffic performance.

Considering the condition of target selected under different circumstances, this paper proposed a new multi-objective model of transmission congestion management with interruptible load based on brand circuit overload match with interrupt capacity. The objective function of the mathematical model presented in this paper are respectively that, if interruptible load matching with overload capacity ,the least number of interruptible load node at least, the lowest total interrupt amount of interruptible load. The multi-object model put forward three goals, brand circuit overload match with interruptible load, the minimum number of interruptible load nodes and the minimum total interruption of interruptible load. Against other optimization methods cannot prioritize to multiple targets and it can easily lead to convergence in the process of solving problems, the paper presented construct evaluation function based on the linear weighted sum to optimize multi-objective linear problem. This method can be sorted prior to multi-objective optimization model. And it has better convergence than other optimization methods in the solution process. Finally, it tested and verified the correctness of method through the IEEE 30 bus power system. And it successfully applied to grid congestion management in oilfield.

This paper presents a kind of DV-Hop localization algorithm based on distance correction of nodes. This algorithm introduces the concept of distance correction factor and combines with the node communication radius to correct the average distance of each hop between unknown node and anchor node，and makes it be closer to the real value. The simulation results show that the proposed algorithm can reduce the average localization error of node, and when the value of distance correction factor is 0.8，the average localization error of node under DA-DV-Hop localization algorithm is reduced 15.53% than the traditional DV-Hop localization algorithm.

Recently, mobile internet traffic has rapidly increased as the huge increase of the mobile devices and smart phone. If mobile internet traffic increases steadily, the resource for cellular network is not enough for the demand of huge internet traffic. Hence, D2D (Device-to-Device) technology is highlighted in order to resolve the lack of cellular resources and the demand of internet traffic. D2D communications use the same resource, which means that it shares the resource of cellular networks. But, D2D technology has some problems such as the mutual interference with celluar users by sharing same resource with cellular network and increased complexity to search the optimum resource for D2D links with minimizing the mutual interference with cellular users using same resources. In this paper, we proposed a efficient resource allocation for D2D links by using the location information for Cellular and D2D users, respectively. Proposed scheme utilizes location information and SINR (Signal-to-Interference-plus-Noise Ratio) information in order to increase the efficiency of resource and also reduce computational complexity. Of the proposed scheme first selects the prospective cellular resources based on the location information and then finally D2D resource by SINR comparison from the group of selected resources in previous procedure. Simulation results show that the proposed scheme attains the higher throughput over the scheme with only location information and we also compare the D2D and cellular throughput of the proposed scheme according to the rate of the group selection for the next SINR comparison in order to determine the optimum resource for D2D communication.

With the aggravation of terrorist activities and frequent occuring of all kinds of car bomb attacks, social and public safety issues have become the focus of attention of the whole world. The vehicle chassis foreign body detection system developed in this paper is mainly used in all kinds of important occasions, to achieve real-time and safe detection of vehicles which is helpful to protect the lives and property of citizens, and to block the invasion and transimission of drugs and other harmful substances. Traditional vehicle chassis detection is carried out by security personnel with dedicated portable underbody detection tool, which is time-consuming, laborious and ineffective. In this paper, we construct a intelligent vehicle chassis image detection system. However, there is always distortion in the real time vehicle chassis image captured by multi-line CCD array which therefore needs to be corrected. This paper presents an image correction method for multi linear CCD. Firstly, Sobel differential operator is used to detect the binarized image of the edge of the vehicle chassis on horizontal and vertical directions. Secondly, we use Radon transform to detect angle of inclination of traveling distorted image captured by line scan cameras based on the results of edge detection, using shear transformation to correct binarized chassis image. Finally, a standard chassis image can be obtained based on image interpolation, the characteristic of Sobel operator and recapture the image. Experimental results show that this proposed method is simple and insensitive of stains and light. In addition, a standard chassis image can be obtained after completing the distortion correction.

Development with IT technology has wide effect for military sector. For this reasons, the important sources is ‘First see, and first determine, and first attack’ in modern and future warfare. And there are also importance with patriot robot such as drone for understand the movement pattern with enemy. Therefore, in develop country; they process with sensor system, delicate attack system, informationization and identification proactively. For now, the connection between equipment is essential in the war environment, so the secure with these things is important. But this is planned with using network structure based on TCP/IP, So there is a raised problem that plan which I mentioned has difficult to deal with attack from using structural weakness. In this paper, the attack type which is possible in the Airborne Network is made an inquiry and it analyze.

Low cost and low power is one of the important reasons in the wide application of backscatter sensor networks. Based on LabVIEW and USRP platforms, this paper presents and implements a simple and configurable SDR prototype for backscatter sensor networks. The SDR prototype can apply to the multi-sensor environment with low power. The prototype consists of configurable backscatter transceiver with homodyne receiver and sensor nodes. It can reduce the power consumption of system efficiently through harvesting wireless RF energy and waking sensor nodes. The frequency division multiple access method with configurable sub-carrier is proposed, and the constraint conditions of sensing data pulse period for avoiding collision among sensors are presented and proved in this paper. The performance of the prototype is analyzed, and the closed-form solution of the probability of outage under the log-normal channel is also given and proved. Finally, the experiment and simulation show the SDR prototype is effective and feasible. The EVM value is less than 2.8%, and the probability of outage error between numerical analysis and Monte Carlo simulation is less than 1.86%.

As a kind of wireless communication system, OFDM systems are widely used in the current and next generation wireless communications. According to the characteristics of OFDM systems, this paper proposed a new heterogeneous multi-core DSP architecture for OFDM system - HeteroM-DSP. Hetero M-DSP based on VLIW DSP core, which has good Data-Level Parallelism and Instruction-Level Parallelism. Each independent DSP core through sharing memory, task scheduling bus and bus controller based open-ring interconnection, improve the communications parallelism between DSP cores. Meanwhile, in order to implement different OFDM systems flexibly, each DSP core has different computational capabilities. It is also improved processor performance/ power rate. Experimental results for the IEEE 802.11a receiver show that Hetero M-DSP can efficiently use for OFDM systems.

Previous studies of aerosol optical thickness (AOT) estimations were generally based on observations from a single satellite sensor. Due to the limited observations from one instrument, the observations yielded AOT estimations with a system bias. In this paper, we combined two heterogeneous data sources, Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), together and proposed collaborative regression models to achieve more accurate AOT estimations than a single sensor does. These two independent remote sensors in the A-train satellite constellation both provide global AOT retrievals and they scan the same location on the Earth surface within a two-minute interval. However, the two remote sensors have different design principles respectively and their heterogeneous observation data streams pose challenges for information fusion. In our study, we proposed two types of heterogeneous collaborative regression approaches. One type of collaborative regression approach fuses information in a feature level. The other type of collaborative approach combines information in a model level. In our study, in each level, we apply a linear regression collaboration model and a neural network collaboration model. The proposed approaches are evaluated based on global observation data from MODIS and CALIOP during April 2, 2009 and April 1, 2011. The encouraging experimental results show that the regression approach collaborating in a model level achieves significantly more accurate AOT estimations than the results from the collaborative regression approach in a feature level. It also obtains significantly superior results to the deterministic AOT retrievals from any single satellite sensor.

Subsea communication system is a key component of marine electromagnetic exploration system. In subsea communication system, only the power line channel model is fully studied, it could help to achieve high-speed and reliable power line carrier communication. In this paper, a channel model is established by using the theory of multi conductor transmission. The single Pi structure, double Pi structure and T structure cable model have been simulated through the Spice. The accuracy of single Pi structure model was verified by measurement and simulation. It provides a guiding role for the whole communication system.