A Frequency Divided Multiple Input Multiple Output (FD-MIMO) radar is proposed, which can synthesize the High Range Resolution Profile (HRRP) by transmitting and receiving narrowband waveforms in different frequency bands without over-demanding system bandwidth. And thanks to short pulse duration, the HRRP of FD-MIMO radar has good Doppler tolerance. But the synthesized HRRP suffers from high-level sidelobes near and far from the mainlobe caused by the discontinuity of the synthesized spectrum and the interferences between the subband waveforms respectively. To suppress them, the reciprocal spectrum filter is applied and the out-of-band attenuation of each subband waveform is utilized. Finally, numerical experiments show the effectiveness of the presented methods.

A novel method based on phase modulated signal is proposed in this paper in order to solve the transmit-receiver waveform design issue. Using the characteristics of phased modulated signal, higher output Signal to Interference plus Noise Ratio (SINR) is obtained for a fixed transmitter by transmitting more energy. The experimental results prove the efficiency of the proposed method, compared with other algorithms, the output SINR is about 1.8 dB higher, extremely well when the spectral density of clutter is relatively small to the noise.

In this paper, the Positive Alpha Stable (PαS) distribution is introduced to identify four traditional kinds of radar clutter, such as Rayleigh, Weibull, Log-normal and K. The tail distributions of various clutters are represented with PαS parameterization. Furthermore, a new method for recognizing such radar clutter distributions is proposed, which relies on the estimated model parameters for Alpha stable distribution. Simulation results show that the proposed new method has higher precision and less calculation burden in comparison with traditional KS testing.

Based on the squinted mode Synthetic Aperture Radar (SAR), this paper describes the relationship between system parameters (wavelength, squint angle, resolution, swath) and phase errors, which caused by the approximation of slant range and 2-D frequency domain decoupling. The secondary approximation is proven to be accurate enough in normal Hi-band high squint SAR image formation. But, range-focus problem with time domain range walk correction limits the azimuth aperture of the Refined Range Doppler (RRD) algorithm; and the variant space Secondary Range Compression (SRC) causes degradation in the performance of normal Chirp Scaling (CS) algorithms. So with the consideration of variant space SRC, the Nonlinear CS algorithm is suitable for large region high squint imaging. Simulations of a MMW-band SAR system demonstrate the convolution.

This paper presents a method for synthetic aperture radar images target recognition based on multi images of the same target and Hidden Markov Models (HMM). Feature vectors of target images are extracted with principal component analysis in wavelet domain. Feature sequences of an image are obtained from the feature vectors of multi images of the same target in different azimuths. Target recognition is carried out for feature sequences with the HMM. The experiments results show that the correctness of recognition is enhanced obviously with the proposed method, and it is an effective method for SAR images target recognition.

The micro-Doppler effect may be generated by additional frequency modulations on the returned radar signal, if the target contains rotating structures, such as a rotor on a helicopter. The body image will be contaminated duo to the existence of the micro-Doppler. In the paper, a simple method based on integral of slow-time is introduced, which has separated the signal from the body of target and that from the rotating parts successfully. It makes the ISAR image clearer, and also provides some information of the rotating parts, such as the radius and the rotation frequency. Finally, a computer simulation is given to prove the effectiveness of the method, and the performances of extraction of micro-Doppler spectrogram in the condition of different SNR are also discussed.

Target-aspect sensitivity makes High Resolution Range Profiles (HRRP) become a long sequence with statistical characteristic changing continuously. A novel frame segmentation method based on correlation coefficient is presented according to the statistical characteristic changes of HRRP sequence. Experimental results for measured data show that the presented method can exactly divide the statistical characteristic changes of HRRPs and the resulting frames are coincident with flying trajectory. Template Matching Method (TMM) classifier in time domain, shortest distance classifier and Support Vector Machine (SVM) classifier in frequency domain are used to evaluate recognition performances. Comparing with the current uniform frame segmentation method based on scattering center model, the presented method efficiently improves the recognition rates.

In this paper, a new approach to bi-static SAR range resolution in ground plane, based on special gradient of transit time, is developed. This new approach has more adaptability. The physical meaning of special gradient is analyzed and its temporal changing property is also researched. Detailed simulations test the validity of the approach and some methods for Bi-SAR trajectory planning, dynamically optimized based on range resolution, are provided at the end of the paper.

Besides the crosstalk δ and channel imbalance f of SAR system, calibration of the spaceborne Polarimetric SAR(PolSAR) also needs to consider the correction of Faraday rotation Ω. This paper proposes a method for estimating Faraday rotation and channel imbalance which uses the statistical characteristics of distributed targets. The method does not need to know the scattering matrixes and only requires that the two different distributed targets satisfy reciprocity and reflection symmetry. In practical applications, it would be easy to find two different kinds of distributed targets(such as forests, farmland or pasture) which meet the requirements in one scene of the SAR image. Therefore the method proposed here has practical values. Simulation experiment with real PolSAR data is carried out to validate the method.

Two-dimensional spectrum’s analytical expression is the basis of the frequency domain imaging algorithm for SAR system. A solution for the approximated two-dimensional spectrum’s analytical expression of spaceborne/airborne hybrid BSAR is presented. To overcome the difficulty of resolving analytical solution for the system’s stationary phase point, the two-dimensional spectrum’s phase is two-order expanded around the point, which is not only in the neighborhood of the system’s corresponding stationary phase point but also can be obtained analytically. Thus the spaceborne/airborne hybrid BSAR system response’s approximated spectrum is pretty close to the real one and can be expressed analytically. Taking TerraSAR-X as transmitter and PAMIR as receiver, the phase error caused by the approximation is simulated for different point targets in the image scene, and the simulated echo of point target is focused by the approximated two-dimensional spectrum. The simulation results demonstrate the validity of the proposed solution.

The major problem in air-borne Ultra-WideBand Synthetic Aperture Radar (UWB SAR) landmine detection is the too many false alarms in practical operation, while enhancement of metallic landmine double-peak feature will benefit elimination of false alarms efficiently. In this paper, based on the double-peak salience maximum criterion, the double-peak feature enhancement algorithm using the post-filter in image domain and the post-filter parameter optimization method are proposed. It is proved with field data processing results that the proposed double-peak enhancement algorithm can increase the double-peak salience of metallic landmines among those suspected targets and thus improve the final metallic landmine detection performance.

Object discrimination based on resonant properties is one of the research topics in radar detection domain. Obvious transient resonances will take place for some kinds of underground Perfectly Electrical Conductors (PEC) targets under impulse electromagnetic field illumination. In this paper, numerical simulation of such resonances has been done by three-Dimensional Finite-Difference Time-Domain(3D-FDTD) method. The calculated results are verified by impulse Ground Penetrating Radar(GPR) measurements and good agreements are obtained. The properties of the resonant signals from buried PEC targets are analyzed through Singularity Expansion Method(SEM). The possibility for identifying buried target by its poles are studied. It is shown that one can apply resonant properties to identify buried targets under some condition.

In this paper, the effect of some factors such as the size of real antenna, different ionospheric spectra and the size of ionospheric irregularities on the azimuth resolution of Synthetic Aperture Radar(SAR) is investigated. The results showed that increasing real antenna aperture size but maintaining the equivalent aperture size of the SAR system will decrease the SAR image’s azimuth resolution, however, it can smooth azimuth image; Ionosphere with Kolmogorov spectrum affects the SAR azimuth imaging more seriously than that with two-parameter spectrum; When the irregularity scale is much larger than equivalent aperture size, the impact of the ionosphere on the SAR azimuth resolution can be ignored; However, when irregularity scale is smaller than equivalent aperture size but with close magnitude, the impact of the ionosphere will result in a substantial degradation of the azimuth resolution.

The cross-range of ISAR image corresponds with the Doppler frequencies of scatterers, which is decided by the target motion. If the cross-range of ISAR image is not scaled, it is difficult to recognize by ISAR image. In this paper a novel method of interferometric ISAR imaging based on the dominant scatterers is proposed, then the features are extracted from the polar image that is obtained from InISAR image by the polar mapping. The extracted features have invariance with respect to rotation and scale. The effect of the four important parameters on imaging and recognition is discussed, the results of four experiments prove the theory analysis.

The main change detection algorithms include forming likelihood ratio algorithm and Least Mean Square (LMS) image subtraction algorithm in Synthetic Aperture Radar (SAR) target detection. There are respective problems for two change detection algorithms: Forming likelihood ratio algorithm needs enough prior knowledge of target, clutter and noise, and LMS image subtraction algorithm is not robust enough. Considering above problems, this paper presents a robust change detection algorithm. The proposed algorithm introduces the influence factor of error on the basis of LMS image subtraction algorithm and calculates the parameters through iteration technique, which improves the robustness of change detection. Finally the results of change detection experiments based on different change detection algorithms are given to prove the robustness of the proposed algorithm in this paper.

This paper works on a critical issue of roll angle estimation in ScanSAR radiometric calibration. After a deep analysis of the relative discrepancies between constituent beams, an improved algorithm is proposed, whose estimation model takes into account both the relative gain discrepancy and the relative beam angular placement between constituent beams. By linearizing the estimation model, an iterative solution of the roll angle can be achieved by means of least square method. Through simulation the estimation accuracy of the proposed algorithm is evaluated under different SNR levels and compared with Dragosevic’s algorithm. The superiority of the proposed algorithm is proved with the results.

Remote sensing imagery plays a key role in forestry management. The increasing availability of data and their high spatial resolution make the tree crown extraction necessary and possible. Marked point processes are employed to model the tree crowns, based on the characteristics of them. The parameters of the model are optimized by RJMCMC (Reversible Jump Markov Chain Monte Carlo sampler) and Simulate annealing. New data term is proposed to give better description of the local pattern of the tree crown; Data-driven Birth-and-Death and Stochastic Diffusions are introduced to reduce the complexity of RJMCMC kernel and accelerate convergence speed. The method is verified on remote sensing image.

Influence of frequency, incident angle, soil dielectric on the penetration ability of electromagnetic wave is quantitatively analyzed. The backscattering from multilayered soil is studied. The model is validated against known solutions to special cases, which can be used in the inversion of deep soil moisture. The conclusion provides a good reference for the design of low frequency (0.1-1GHz) synthetic aperture radar and inversion of deep soil moisture.

The Digital Radio Frequency Memory Cheat Jamming (DRFMCJ) is an effective jamming method to SAR. This paper puts forword a method to generate the complex modulation LFM signal using the slope wobble in different Pulse Repetition Interval (PRI). Because the modulated form of the LFM signal in different PRI is not known to the jammer, which destroies the correlation of the jamming signal and the SAR transmitted signal in the current PRI. In this paper, the two dimension processing method to anti-jam on the range and doople fields is presented, which achieve the valid result to eliminate the digital radio frequency memory cheat jamming.

This paper presents a smoothed pseudo Wigner distribution for PN phase modulation composite reconnaissance signal recognition and deduces SPWVD functions for PRBC-LFM reconnaissance signal. By profile SPWVD distribution analysis，features related to carrier frequency, FM slope and PN parameters such as sub-pulse width, code-length and pulse cycle are extracted. Then a method for the parameter evaluation is presented. Finally, theoretical analysis results are simulated under Gaussian noise conditions. Experiments show the method is superior to these methods based on the spectral correlation method and the Wigner distribution.

Nonlinear filtering algorithms must be applied to single observer passive location and tracking system for the nonlinearity of its observation equations. MGEKF and other nonlinear filters are belong to EKF in essence, while the EKF-like algorithms share the disadvantage of linearization reduce to the unstability of filters. The filter, based on unscented transformation is named UKF, does not need linearization and shows robustness strongly; however, the convergence of UKF is poor for its underestimation of true covariance. An iterated UKF algorithm is developed, and the estimation to the covariance of filter is improved by iterating estimation. Simulation results demonstrate the tracking performance of this algorithm in different conditions.

For reducing the computation complexity of pulse period ambiguity resolution for X-ray Pulsars NAVigation (XPNAV) and improving its convenience in engineering implementation, the Optimization Model for 4 X-ray pulsars localization is presented based on the orthogonality principle. A new relation formula of period number of the Time Difference Of Arrival (TDOA) of pulses is presented, whose factors are decided by the characteristics of X-ray pulsars and whose constancy is decided by TDOA phase residue. Theoretical analysis and experimental simulation show that the new method can reduce the complexity of computation obviously. Meanwhile the relation formula of the new ambiguity resolution has constants, which can be solidified into hardware or be stored into memory unit, so that the new ambiguity resolution is easy to implement in engineering.

The dual particle filter is proposed to solve the problem of simultaneously estimating the state and the parameter of a nonlinear dynamic system. In the new filter, the sufficient statistics based particle filter is adopted to deal with sampling impoverishment arising in generic particle filter and the beta distribution, which makes good use of the prior knowledge as well as avoids tail draws for the parameter, is used to fit the parametric a posteriori probability density function. Simulation results show that both estimation accuracy and initial sensitivity of the nonlinear system are improved.

Sound source localization using microphone array provides an effective solution to speaker tracking problem under adverse environments. A new method based on weighted subspace fitting is presented for sound source localization and tracking within the framework of particle filtering. The cost function of weighted subspace fitting algorithm is extended to the wideband case, and the location of speaker is estimated using dynamical model of speaker motion and the likelihood function model based on the wideband cost function. The results of both simulations with synthetic data and experiments with real-world data show that the proposed method has good performance.

A system identification algorithm which is based on minimizing the zero-minimum target function is proposed. The target function presented in this paper is the square of the difference between the mean square error and the variance of the noise. And the minimum of the target function is zero. During the system identification process, the system mean square error, the correlation matrix of the tap inputs and the cross-correlation vector between the tap inputs of the adaptive filter and the desired response are estimated online by employing moving average method. Then, a recursive relation for updating the tap-weight vector is derived. The step size of the algorithm presented here could be adjusted adaptively according to the value of the statistics obtained online, which makes the algorithm be capable of accelerating the speed of convergence without sacrificing the steady state error. Further, the analysis of stability of the algorithm is provided, and then the convergent condition is obtained. The experimental results of the system identification setting demonstrate that the algorithm proposed here has faster convergence and smaller steady state error comparing with the algorithms mentioned in other literatures. It’s also shown that the algorithm has better stability.

A Dynamic Displacement Field (DDF) model for describing image sequence distortion is proposed. The parameterized DDF model offers a unified framework that covers all the reported image sequence distortions. Experimental results show that the DDF model is a simple and effective model for describing image sequence distortion and provides a gradually upgraded and evolutionary process for image sequence distortion correction.

A new method based on ACA (Ant Colony Algorithm) is proposed for data association in multi-target tracking. Firstly, the ACA is modified according to specific data association rule, in which the path of ACA and the length of the path are redefined by considering the effect of target moving characteristics on the association possibility. Then the ACA could be applied to find the best tour to the data association problem. Since SIS (Sequential Importance Sampling) performs well in non-linear tracking system, this paper employs it to track targets after achieving the association result with ACA. In computer simulation, examples for multi-target tracking in one-dimension and two-dimension situation are presented. Experimental results show the feasibility and effectiveness of the proposed method.

Although numerous studies measure the strengths of perceptual organization cues for grouping contour, most ignore the roles of symmetry and parallel principles in grouping contour. A hierarchy grouping model is developed. Firstly, most saliency edges are extracted as input for subsequent contour grouping. Secondly, the symmetry measure as higher grouping cues which supervises the low level grouping process. Experiments on different types of images show that the model reduces ambiguities in the intermediate representation and have higher efficiency and robustness, while holding biological plausibility.

Aiming at the conflicts between EMD(Earth Mover’s Distance)-based measure for document semantic similarity and metric axioms, which prevent EMD from being widely applied in the information retrieval and data mining, a novel EMD-based metric for document semantic similarity named Mdss_EMD is presented. Firstly, based on the analysis of drawbacks of EMD and its existing modifications, the concepts of document width and virtual term are proposed. Subsequently, by adding virtual term to initial document vector, the approach aligns the total weights of document vectors, so that all of metric axioms are satisfied. Finally, in order to improve the applicability and processing speed of the metric, the similarity distance of virtual term is designed to be elastic and EMD algorithm is also simplified. The proposed approach extends EMD to metric space, and substantially improves EMD on indexing and accuracy. The experimental results demonstrate that Mdss_EMD outperforms the original EMD and other similar measures in general.

The robust Fuzzy Fisher Criterion based Semi-Fuzzy Clustering Algorithm (FFC-SFCA) for linearly separable data is presented in this paper. FFC-SFCA incorporates Fisher discrimination method with fuzzy theory using fuzzy scatter matrix. By iteratively optimizing the fuzzy Fisher criterion function, the final clustering results are obtained. FFC-SFCA exhibits its robustness and capability to obtain well separable clustering results. In addition, optimal discriminant vector and threshold of classifier can also be figured out. The experimental results for artificial and real datasets demonstrate its validity and distinctive superiority over the two conventional clustering algorithms.

In view of intermittent chaotic signal identification problem for chaotic oscillator weak signal detection, noise disturbing effect on Poincaré section is analyzed, a new identification method based on a Poincaré map is proposed and numerical simulation is done in order to validate this method. The result shows that this method archives effective identification to intermittent chaotic signal frequency, even when the output wave of phase component is hard to identify. The short-time periodic chaotic self-oscillation is restrained, a swift and validate weak signal detection under strong noise background is realized.

This paper proposes an iterative Signal-to-Noise Ratio (SNR) estimation algorithm suited to Multiple Amplitude Phase Shift Keying (M-APSK) signal based on a priori information. Given a priori, the M-PASK signal has the determinate probability distribution with flat-fading, and its logarithmic expection is differentiated to yield the relation between the SNR parameters and the data. Reliability metric is introduced to updata the parameters, then the iterative algorithm is put forward correspondingly. Compared with the foregone Memont Methods (MM), simulation results show that the new algorithm using a prior has better performance when the intrinsic information is larger than 0.4 with 4 iterations, while that without a prior only better in middle and hign SNR with 5 iterations used.

In Short Burst wireless communication and non-corporation communication, the receive data is not long enough to use in Bussgang blind equalization method. In this paper reusing data was introduced to shalvi’s blind equalization algorithm, by comparing the kurtosis of the reused data after equalizing and the original symbol, the reason of the algorithm’s valid converging was got. Base on this conclusion, the reusing data method was introduced to Bussgang algorithm. And then the factors which will influent the effect of the reusing data equalization method were analyzed. Simulation results show that reusing data equalization can reduce the symbols of the Bussgang method need to converge, it has some practical utility.

A modification is proposed to reduce the complexity of Overlap-Cut (OC) method Frequency Domain Equalization (FDE) in Code Division Multiple Access (CDMA) downlink systems. FDE based on Fast Fourier Transform/Inverse Fast Fourier Transform (FFT/IFFT) carries out single-tap equalization on received signal, moreover, its complexity is much lower than its time-domain counterpart. The analysis for the generation and the distribution of the inherent error of OC method FDE indicates some improvement to the equalizer. As a result of both theoretical analysis and simulation, a better performance is obtained with lower computation burden than conventional algorithms.

In order to realize the precise multi-beam forming, a calibration method of the amplitude and phase error among RF channels for the transmitting multi-beam array antenna system onboard satellite is proposed. This method is conducted by receiving the sum of the output signal of all RF transmitting channels, including the temporally multiplexed orthogonal codes injected from the base-band, the calibration factors for all the RF transmitting channels can be simultaneously obtained by temporal correlation of the orthogonal codes and the IDFT parallel processing technology. The calibration factors are normalized for avoiding the effects on the nonlinearity components. Computer simulation shows that the beam pattern after calibration is very close to the ideal beam pattern.

High data rates and high mobility induced Doppler shifts introduce time and frequency selectivity in wireless links. The quality of channel acquisition has a major impact on the overall system performance. In this paper, relying on a basis expansion channel model, a scheme is proposed for estimating doubly selective channel parameters . The receiver does not have to know the statistic information of the channels and will not estimate the power of noise in advance, and has low-complexity. Along with the estimation scheme, the optimal pilot sequence is derived based on minimizing mean-square error of the channel estimation. Simulation results demonstrate the performance of the proposed scheme is better than existing scheme for a range of SNR, where a frequency- selective channel is randomly generated with different Doppler spreads via Jakes’ model.

Rapidly time-varying channels degrade the performance of the Orthogonal Frequency Division Multiplexing (OFDM) due to severe InterCarrier-Interference (ICI). The most effective method of canceling the ICI is frequency equalization. But, it relies on precise channel estimation. Basis Expansion Model (BEM) can approximate time-varying channel accurately. And since then, only some finite model parameters need to be estimated to reconstruct the channel. However, the pilot-symbol-aided parameter estimation is still significantly affected by ICI from near non-pilot-symbol. So, in this work an ICI-self-cancellation parameter estimation method is proposed for BEM, by utilizing the high correlation between subcarrier ICIs. Simulations show better performance than the simplex BEM methods.

Using a Compact Mapping Matrix (CMM) to transform a diagonal space-time coding, a design method for full-diversity space-frequency codes is proposed. Without losing the inherent space diversity of the space-time coding, the proposed space-frequency coding obtains extra frequency diversity provided by the frequency-selective fading channels and improve the performance. Further improvement is obtained by optimizing the coding gains. Exploring the diagonal structure of space-timing coding and the new research results, the proposed codes can be decoded with polynomial complexity. This facilitates the hardware implementation of the system.

A non-orthogonal decode-and-forward scheme with relay selection is proposed in order to achieve higher spectral efficiency and more cooperative diversity gain in the two-hop relay networks. In the single relay case, the relay node is available to cooperate non-orthogonally with the source node only if it can decode correctly. When there are multiple nodes in the network, a relay selection method is given to select the best relay which decodes correctly and has the best channel to destination. Asymptotic analysis of outage probability shows that the scheme with relay selection achieves the same diversity-multiplexing tradeoff as the non-orthogonal amplify-and-forward scheme, but it obtains more outage capacity at lower SNR and is easier to implement.

This paper presents a new method of intra/inter-TTI frequency hopping in E-UTRA uplink. The hopping method decides the starting frequency according to Latin square and users’ frequency resource requirements. The method that can keep single carrier transmission and avoid collision at the same time is suitable for various transmission bandwidths. The conclusion is verified by computer simulation. This method will be used in E-UTRA uplink with a good prospect of application.

A signal detection and synchronization acquisition scheme is proposed for distributed Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system. Reliable signal detection scheme and coarse time and coarse frequency estimation based on spectrum analysis method can be obtained by designing pilot symbols. And then the pilot symbols are used for POST-Fast Fourier Transform (FFT) precisely frequency and time estimation. The simulation results show that the new algorithm works well at low SNR over wireless multipath channel.

A novel image coding scheme based on sparse decomposition is proposed to improve decoded image quality and vision impact at low bit-rates. The over-complete dictionary, which is built on anisotropic refinement and rotation of 2D nonseparable Mexican hat wavelet, can efficiently capture edge characteristics present in natural images. And to improve the coding efficiency, an atom modulus which is piecewise approximated by the least squares line is proposed. Simultaneity, the stream can simply be truncated at any point to provide a SNR-adaptive bit-stream, which is very suitable for transmission in wireless communication. Experimental results show that the objective and subjective quality of decoded image is, at low bit rates, comparable to the -state- of- the art image coder, represented here by JPEG2000 and other based on Matching Pursuit methods. Also, the coding artifacts in the MP algorithm are less annoying than the ringing introduced by wavelets.

Maximize signal-to-leakage ratio strategy is proposed in multi-user multi input multi output system, which is used to design MU-VBLAST downlink. The performance of the strategy proposed in the paper exceeds that of Block Diagonalization (BD) method which is paid wide attention in MU-MIMO systems; otherwise, the MSLNR strategy is found to relax the condition on the number of transmit-receive antennas in comparison to BD method. Simulation results illustrate the resulting system performance.

It is adopted the wireless channel, limited battery energy and distributed control techniques in wireless Ad hoc networks, so the existing questions are channel safety threat and more power consumption. To solve above questions, we develop a joint source and channel virtual user safety identification method for DS-CDMA wireless Ad hoc networks. The method can protect and encrypt the header by embedding a random, safe and identifiable header. A subspace-based multi-user detection and virtual user safety identification method can be used at receiver nodes, and the virtual user safety identification method only identifies the header information. Simulation results show that our proposed scheme improves miss rate and active user estimation precision, reduces the probability of retransmission, then saves running radio module power consumption, achieves virtual user safety identification and obtains advanced channel safety.

An algorithm of traffic distribution forecasting based on simulated annealing is proposed, which is used to calculate the traffic density by simulated annealing. Furthermore, the weight value of traffic density is taken into account in this paper, which is introduced in traffic forecasting based on simulated annealing. The results of real statistical traffic show that the algorithms can forecast the mobile traffic distribution effectively.

A new scheduling algorithm in Parallel Packet Switch(PPS) is proposed in this paper . This algorithm eliminates out-of sequence of the cells belonging to a packet by dispatching the traffic with variable-length packet at de-multiplexer. It balances the traffic distribution to each parallel switch by a credit based mechanism. The combined input and output queued(CIOQ) mechanism is adopted with each parallel switch in this algorithm, which not only degrades the speed-up requirement of the buffer and switch, but also takes full advantage of the available research achievements of scheduling algorithm in Crossbar switches. Theoretical analysis is made on the fairness of traffic distributions, the amount of the required high-speed buffer (run in line-speed) and the stability of the network. The simulation analysis shows the good performance of this algorithm further.

The indoor broadband LAN (Local Area Network) is the extension of the Internet and is also the technique basement of the smart house in the future. This paper introduces one novel method to make up the indoor broadband network firstly with the BPL (Broadband Power Line) communication and the UWB (Ultra Wide Band) communication techniques, which make kinds of indoor equipments connected into the LAN. Then on the base of the transmission and radiation characters of the BPL, the coexistence of the BPL and the UWB is analyzed on two sides: the electromagnetic radiation and the signal analysis. After simulating the BPL signals and testing the radiation, the calculation model for BPL system is proposed to analyze the performance of the UWB BER (Bit Error Ratio) in the BPL radiation field. The result shows that two broadband communication techniques are suitable for coexistence, which supports a relevant technique basement of the normative indoor broadband LAN for the smart house.

In this paper, a novel cooperative routing protocol is proposed in Ad hoc networks. A minimal energy multinodes cooperative path is built with the cooperative transmission of neighbor nodes and comparison of total power consumption. Under the assumption that nodes can know the relative location of neighboring nodes, the distributive routing scheme can be implemented by carrying information about power consumption of route and cooperative cluster in Router Requirements (RREQ) packet. Simulation results show that the energy-saving performance can be significantly improved compared with traditional non-cooperative routing. Meanwhile, using the selection strategy of cooperative nodes, the control expense and complexity of computation can be reduced, trading off a little decline in energy-efficiency.

To solve the static traffic grooming problem in WDM mesh networks, a minimizing cost grooming policy is proposed based on the transceiver saving auxiliary graph model. The policy considers the costs of both two network resources of transceivers and wavelength links. It searches a least-cost path for each traffic request in order to get the optimized solution with the lease network cost. It assigns different values to edges of the auxiliary graph according to the cost ratio of the two resources. Minimizing the weight of a path means minimizing the resource cost of this path, and then the policy is easily achieved. Simulation results show that the network cost of the policy is always the least despite different cost ratios of the two resources.

A compact multi-signature is a special digital signature that allows multiple signers to generate a signature on the same message with the property that the length of the signature is almost same as that of an individual signature. An efficient identity based compact multi-signature scheme from RSA is proposed in this paper. The efficiency of the new scheme is improved by 50% than that of Bellare and Neven’s scheme. The signature length of the new scheme is almost same as that of a single RSA signature, as the identity based public key is used, the goal to design a compact multi-signature is nearly achieved. The security of the new scheme is proved under the assumption of RSA in the random oracle model.

An energy-balanced connected coverage model is proposed for solve the problems that limited energy of sensor nodes and imbalanced energy consumption of minimal connected cover methods make against the lifespan of wireless sensor networks. The model uses Voronoi diagram and Delaunay tessellation to partition wireless sensor network and to distinguish the redundancy nodes overlapping target region, uses hop to sink node to stratify nodes. And then, a method to choose closeable nodes is introduced. The simulation results indicate that the network educed by the non-minimal connected cover set constructed by the model can balance the node energy consumption, use optimized route and weaken the influence of the key points on route.

in this paper, an energy efficient Adaptive Fusion Mobile-agent-based Routing algorithm (AFMR) is presented in Wireless Sensor Networks (WSN), where AFMR can provide energy efficient Mobile Agent (MA) routing algorithm for correlated data gathering. AFMR is used to not only jointly optimize over the costs for both data transmission and data fusion, but also evaluate the cost and benefit of the data fusion, in order to adaptively adjust whether fusion shall be performed for minimizing the total energy consumption when MA migrates to a particular node. Simulation results show that AFMR achieves better performance than existing MA routing algorithm including TSP and FMR from perspectives of energy consumption in a variety of correlated data gathering applications.

In this paper, the optimal grid size is studied based on link model reachable with probability in realistic environment. Reaching probabilities of neighboring grids and path are analyzed, and the effects of node density and grid size on reaching probabilities is studied, and optimal grid size of which maximize energy efficiency and network average packet delivery ratio is analyzed theoretically. A scheme of combination of packet delivery ratio and energy efficiency to select grid size is proposed, which maximizes network lifetime when meet user’s requirements. The grid routing is simulated and analyzed, the results show the optimal grid size of theoretical value and simulation value to be equal almost, and the grid size selecting scheme of combining packet delivery ratio and energy efficiency can prolong network lifetime efficiently.

Traditional localization methods usually can not handle sensor networks which are affected by several practical factors, such as anisotropic deployment terrain, imprecise anchor node position and noisy range measurements. In this paper, a robust region localization approach is proposed to naturally address these factors by constructing a global constraint set. A projection method is given to compute feasible geographic region, which can assuredly bound actual node position. The infeasible holes within the region are also computed using non-convex constraints. To enhance the practicability of this method, an iterative and distributed implementation based on clustering. Simulation results show that the algorithm is not affected by deployment terrain and measurement noise, thus it is applicable for sensor networks.

Firstly, it is found that the physical communication link of WSNs takes on lost, asymmetric characteristics according to experimental measurements. Secondly, some typical reliable transmission mechanisms of link layer provide a certain degree of reliability, but low path efficiency and high energy costs. Therefore, an efficiency-centric link Group-based Acknowledgement Mechanism(GAM) is presented in the paper, and its performance is analyzed theoretically based on the evaluation metrics, such as path efficiency, buffer requirements, and etc. Finally, the results compared with traditional reliable transmission mechanisms based on the existing MicaZ platform show that the GAM presented in the paper particularly meets the requirements of the high reliability, low real-time applications of WSNs for its high path efficiency and constant cache occupation.

The problem of data transmission in energy-constrained wireless sensor networks is modeled into a network utility maximization problem. This model describes the coupled nature of the energy consumption among different sensor nodes. The network utility maximization is solved by introducing the slack variables and using dual decomposition techniques, and a distributed energy control algorithm is obtained. Simulation results show that, the distributed algorithm can converge to the Pareto optimal tradeoff between data rates and energy consumption for all sensor nodes.

Theoretical model of a double cusp gun is analyzed; model of magnetic cusp is built up. By using of EGUN and MAGIC, a double cusp gun producing large orbit gyration electron beam is designed, with beam velocity ratio of 1.38 and axial velocity spread 3.7%. The distribution of electron beam velocity ratio and axial velocity spread on axis is analyzed, then the variety magnetic cusp transition length affects on beam parameters is discussed, which provides some reference for double magnetic cusp gun design.

A multi-tap broadband channel model is established according to Power-Azimuth-Spectrum(PAS), Doppler-Power-Spectral-Density(DPSD), Power-Delay-Profile(PDP) and the antenna structures of both transmitter and receiver. An improved shaping-filter method, which can eliminate correlation of different taps by adding a random phase-shift, is proposed to simulate the independent fading channel. A simulation platform of the wireless MIMO channel is proposed using Matlab, then simulate the MIMO channel model based on 3GPP standard. The simulation results show that the obtained channel characteristics are close to the theory results, which proofs the effectiveness of the improved channel model proposed in the paper.

An approach to available bandwidth measurement in IPv6 networks called Packet Train Time Stamp (PTTS) is proposed. A new packet train (M^h-L-M^t) is designed in which the measurement packets have the IPv6 time stamp extension header and the load packets reflect the characteristic of the networks. The source sends probe packet train (M^h-L-M^t), the current router time is recorded in each measurement packets. Processing these time stamp by the bandwidth statistic algorithm, the value of available bandwidth is acquired. Using the flow label and traffic class fields in the IPv6 header, the test class and stream is designed in order to reduce the influence of cross traffic. This approach is verified through simulation.