In order to improve the viability of MIMO radar in electronic warfare, the relationship between radar parameters and its searching performance as well as the Radio Frequency (RF) stealth performance is firstly analyzed. An RF stealth optimization model considering both the intercept factor and the searching frame period is formulated for MIMO radar in searching mode. Based on the above model, an optimization algorithm of RF stealth for MIMO radar in searching mode is introduced, where the sub-array number, signal duty cycle, dwell time and searching frame period are controlled adaptively to optimize the RF stealth performance under the constraints of detection performance and time resource of the system. Simulation results show that with RF stealth algorithm in searching mode, MIMO radar can achieve desired detection performance and obtain better RF stealth performance compared with traditional phased array radar.

The non-equispaced along-track motion has serious impact on SAR imaging. The SAR images are geometric distorted after the along-track motion compensation, which may impair the quality of the sub-image connection and the multi-spectral SAR image fusion. When the along-track velocity error is large the remained geometric distortion after the interpolation geometric distortion correction can not be ignored. In this paper, a SAR motion compensation algorithm is presented based on Non-Uniform Fast Fourier Transform (NUFFT) directly to the azimuth non-equispaced data. The algorithm has 1 to 2 quantitative reduction in location error and geometric distortion than interpolation geometric distortion correction algorithm and has high robustness on along-track velocity error. At the same time, the amplitude and phase information can both be saved based on the proposed algorithm. The results of the NUFFT compensation for simulated data and the real SAR data verify the effectiveness of the proposed algorithm.

To deal with the clutter suppression issue in the moving target detection for the near-shore water regions with azimuth multichannel SAR systems, the multichannel steering vector of the ambiguous clutter is derived, and the multichannel signal model of the near-shore water regions in image domain is established. Based on the derived steering vector and the established signal model, ambiguous clutter suppression methods suitable for the near-shore water regions are proposed. The impact of the spatial ambiguity which is induced by the sampling with multiple channels, on the ambiguous clutter is analyzed. Then, the simulation analysis of the Ground Moving Target Indication (GMTI) performance for the near-shore water region is given. The validities of the proposed methods are verified by the simulation results.

A two-step imaging algorithm for focusing airborne parallel high squint Synthetic Aperture Radar (SAR) data is proposed in this paper. For the serious cross coupling of echo signal in bistatic high squint SAR, Linear Range Walk Correction (LRWC) is performed in range frequency-azimuth time domain to correct the large LRW induced by the high squint model of receiver and transmitter. A Modified Bistatic Point Target Reference Spectrum (MBPTRS) is derived, and residual Range Cell Migration (RCM) is corrected by Chirp Scaling (CS) method to get the focusing result. To solve the target position displacements in the focusing result, a method of target position correction that converts the focusing image to the ground plane is derived. Finally, the experimental results with simulated data validate the effectiveness of the proposed two-step imaging algorithm and the method of target position correction.

In order to investigate amplitude statistics and variation under different ocean parameters of L-band low grazing angle sea clutter, in this paper, based on the L band real sea clutter data collected in different wave height and wind direction and proper goodness of fit rules, fitting result of Rayleigh, Weibull, Log-normal, K-distribution and Pareto distribution in modeling low grazing angle data are compared. The applicability of the above models are discussed. It can provide reference for the selection of clutter model in radar target detection, improve the adaptability under maritime environment of target detection.

Dense repeater jamming not only causes false alarms, but also raises the threshold of constant false alarm ratio detector nearby the jamming, which degrades the performance of targets detection. On the other hand, the samples contaminated by jamming degrade the performance of space time adaptive processing. To deal with these issues, a method to suppress dense repeater jamming is proposed. Firstly, the directions of the jammers are estimated. Secondly, Generalized Sidelobe Canceller (GSC) is used to cancel the jamming in the spatial domain. The auxiliary channels of the GSC are the sum beams pointing at the jammers, and the covariance matrix of the GSC is estimated with the jamming samples selected from the clutter free region. The proposed method reduces the false alarms caused by the dense repeater jamming, and improves the performance of targets detection. In addition, the structure of this method is simple and easy to realize. Simulations are presented to verify the effectiveness of the proposed method.

In order to satisfy the requirement of the air traffic control and the battle-filed command system, a three-dimensional (3D) tracking algorithm in distributed two-dimensional (2D) radar network is proposed. Firstly, this paper starts from the generalized measurement equation at the fusion center under the centralized framework, and derives the update equation. Then, the target 3D state is estimated by substituting the measurement term in the update equation with each local radar tracking information. Judging from the derivation, the proposed algorithm is obtained by centralized fusion method with measurement expansion and matrix transformation directly, and it is a suboptimal algorithm due to the approximation of the tracking model of single radar. Finally, Monte Carlo simulations show that the proposed method has fast convergence speed and achieves good tracking accuracy, thus it can meet the need of the real application.

SAR imaging simulator is an important tool for understanding and implementing the SAR images. In the light of the structural features of buildings, a novel fast SAR imaging simulator for urban structures based on facet projection model is proposed to meet the requirements of the SAR image interpretation applications for buildings. The geometry mapping process from the target model to the image-domain is accelerated by using simplified ray tracing algorithm, and the facet projection model is performed to reduce interpolating error from scattering facets to resolution cells. Compared with the traditional SAR image simulator, this simulator strikes a balance between accuracy and efficiency. Some experiments validate the facet projection model and demonstrate the efficiency of the simulator, which will offer a higher value of practical applications.

The joint acquisition algorithm is used for collection detection of the multi-satellite signals, given the lack of analysis and assessment on its detection performance. To make the case, the processing gain is adopted to measure the improved the level of sensitivity of the joint acquisition as opposed to the traditional acquisition; the analytic expressions of the processing gains are given respectively with the ideal assumption and the errors of the signal synchronization parameters; the detection losses caused by the delay and Doppler errors are analyzed in detail; the detection losses of the joint acquisition are compared with those of the traditional acquisition. Furthermore, some simulations are performed to verify the analytic results, which show that most of the detection loss in the joint acquisition is less than those in the traditional one.

The two-stage Weighted Least Squares (WLS) method is a well-known linear approach in Time- Difference-Of-Arrival (TDOA) and Frequency-Difference-Of-Arrival (FDOA) passive localization. But this method can only attain the CRLB in a modest noise environment and the bias of the localization result is significant for strong noise. This paper discusses a Constrained Total Least Square (CTLS) solution to the pseudo linear equations with two constrains for TDOA/FDOA localization. A unified expression for several LS solutions is derived based on Lagrange multiplier. The Constrained Weighted Least Square (CWLS) method and Constrained Least Square (CLS) localization method reduce to the special cases of the localization solution. The simulation results show that the proposed method has lower Mean Square Error (MSE) and lower bias compared with the two-stage WLS method, and it is more robust to noise.

Regional energy focusing is a crucial technology for precision energy delivery. This paper mainly focuses on one of its typical applications: PRecision Electronic Warfare (PREW), and a new regional energy focusing method under ultra-sparse array is presented. By modeling regional energy focusing under ultra-sparse array as a Semi-Definite Program (SDP), an optimization can be made for self-correlation matrix of the transmitted waveforms to provide a focal spot matched with the entire target region, meanwhile, to minimize the energy level on the surrounding interesting region. Finally, four assessment indicators are proposed to evaluate energy focusing effect. The numerical results indicate that the proposed method, with more practicability, can provide a better energy focusing performance than the existed methods under typical arrays.

This paper discusses the issue of multiple targets’ Direction Of Arrival (DOA) estimation for Spatially Spread Polarization Sensitive Array (SS-PSA). First, the signal model of sparsely uniform SS-PSA with three orthogonally oriented polarized-antenna is presented. Then the rotational invariance of the proposed uniform array is utilized to calculate the ambiguous DOA estimation by means of ESPRIT method. The spatial phase shift raised by spatially spread polarized-antenna is compensated by the ambiguous DOA estimation to obtain virtual collocated polarized-antenna. The corresponding virtual DOA estimation is calculated by the multi-dimensional angle structure among the virtual collocated polarized-antenna. Finally, the multiple targets’ DOA estimation is obtained by extracting the minimum norm of the difference between the ambiguous DOA estimation and the corresponding virtual DOA estimation. The proposed array can reduce the array mutual coupling by using the spatially spread polarized-antenna instead of conventional collocated polarized-antenna. Moreover, the DOA estimation accuracy can be improved greatly because of the extended aperture offered by the sparse array. Computer simulation results verify the effectiveness and high-accuracy of the proposed SS-PSA DOA estimation algorithm.

The complex fast fixed-point algorithm, also called complex FastICA, is one of the most important algorithms for Blind Signal Separation (BSS). However, the performance of this algorithm deteriorates when it is used to separate the noisy mixed sources, especially in the low SNR case, since the covariance matrix of whitened observations is not an identity matrix but a diagonal matrix. This paper bases on the present complex FastICA. First, the mixed sources defined with complex Independent Component Analysis (ICA) signal model are projected onto the signal subspace. Thus, the denoising and decorrelating from mixed signal samples can be handily achieved. Then, the learning rule of the algorithm is modified, where the effect of white Gaussian noise is taken into account. Therefore，the BSS performance of complex FastICA is improved markedly. In this paper, the learning rule of denoised noncircular FastICA (nc-FastICA) is derivated and the detailed procedure is given. Simulation results demonstrate the effectiveness of the proposed algorithm.

The joint estimation of the Direction of Arrival (DOA) and gain-phase errors can be implemented by the joint iteration method based on the eigen structure subspaces. However, when applying the method to correct the amplitude and phase error of the conformal array, the fast high-resolution spatial spectrum estimation methods can not be applied directly, because of that the space-domain steering vectors of the conformal array does not possess the Vander monde structure. On the other side, the computation of DOA estimation implemented by searching peak of spatial spectrum in 2-dimension is very large, which limits the application of joint iteration method in conformal array. To solve this problem, this paper proposes a new method for gain-phase error calibration in conformal array by virtual interpolation. The DOA estimation can be implemented rapidly by utilizing the special structure of virtual array, and the searching process of the spatial spectrum peak is eliminated, thus the computational complexity of the proposed method is low and the engineering realization of the proposed method is easy. Theoretical analysis and extensive simulations verify the effectiveness of the proposed methods, and provide a reference for the engineering applications of conformal arrays.

In view of reducing the effects of cross terms, conventional methods of parameter estimation for Linear Frequency Modulation (LFM) signals suffer from low accuracy and huge computational complexity. To solve these problems, LV’s Distribution (LVD) based method is introdused in this paper. It provides directly accurate Centroid Frequency-Chirp Rate (CFCR) representation of a LFM signal. The rescaling operator is used for the Parametric Symmetric Instantaneous Autocorrelation Function (PSIAF) to eliminate the effects of linear frequency migration on the time axis, then a two-dimensional (2-D) Fourier transform is taken over the new scaled time variables to convert a 1-D LFM signal into a 2-D single-frequency signal. The resulting signal can be represented with distinct peaks on the CFCR plane, whereas the energy of the cross terms can be ignored compared with the peaks of auto terms. The coordinate values of LFM components directly correspond to their centroid frequency and chirp rate. LVD can suppress effectively the Gaussian noise, however, the performance of the CFCR domain analysis for signals in heavy-tailed impulsive noise environment is in severe degradation. Considering this issue, an improved Fractional Lower Order LVD (FLOLVD) for the α stable distribution noise is proposed. Computer simulation results show that the proposed approach obtains high-accuracy phase estimation, and it is robust to the impulse noise as well as the Gaussian noise.

This paper proposes a Modified Reduced-Dimensional MUSIC (MRD-MUSIC) Direction Of Arrival (DOA) estimation algorithm to solve the computation-intensive problem in the two-dimensional DOA estimations. The MRD-MUSIC algorithm can distinctly reduce the computational load, since the two-dimensional DOA estimation can be decomposed into two stages of one-dimensional DOA estimations by the quadratic optimization method. In this algorithm, a one-dimensional DOA is obtained by the direct derivation of the quadratic optimization function, and the steering vectors are strongly constrained in the solving process, as a result, the derivation is closer to the optimal solution than the other’s. The simulation results verify that the theoretical derivations of this algorithm is of correctness, it does not need pair matching processes, and it has higher successful rate and precision of the angle estimation.

According to the Doppler shift of moving acoustic source, three methods are presented for identification of noise sources of underwater moving target with single hydrophone. Firstly, the weak Doppler shift curves are obtained accurately by windowed cross Wigner-Ville Distribution (XWVD). Then the abeam moments are estimated by frequency intersection or least square algorithm. Locations of noise sources are obtained by referring to beacon source at last. These two methods are respectively called frequency intersection method and least square method. Furthermore, based on the effect of energy dispersion caused by inner artifacts, another identification method is proposed by applying WVD to Doppler signal directly, and this cross-term method needs less computation. The water tank and sea experiment results show that performances of these proposed methods are better than the existing passing property method. Among the three methods, the least square method is the best one, next is the cross-term method, and frequency intersection method is the worst in comparison.

A novel image fusion method based on supervised intelligent learning is proposed in order to overcome the difficulty in the use of priori knowledge in image fusion. In this study, the images database for supervised learning is first constructed，then the model parameters trained with the available training datasets are used for the Takagi Sugeno Kang (TSK) fuzzy system model. Different from the classical method that needs to manage the different parameters setting manually, the proposed method can effectively preclude the problem in the optimal parameters setting. Meanwhile, some advantages are displayed in the fusion image quality and adaptation. The experimental studies on different types of images, both single and multi, also show the effectiveness of the method.

The detection to target in motion is a key technology in video analysis. This paper proposes a target detection algorithm based on a multi-scale motion attention analysis, which provides a new method for motion target detection under a global motion scene. Firstly, the noise of motion vector field is removed by filter, and according to the mechanism of visual attention, spatial-temporal motion attention model is built; then the trust degree of motion vector is suggested on the basis of validity analysis of motion vector, and decision fusion of multi-scale motion attention is accomplished by D-S theory for detecting the region of motion target. The test results of different videos show that the algorithm is able to detect precisely targets under a global motion scene, thus effectively overcoming the limitations of the traditional algorithms.

A new method extended from motion history image called Multi-Layered Mmotion History Images (MLMHI) is proposed to the representation and recognition of human activity using depth images provided by Time-Of-Fligh (TOF) camera. Firstly, the motion-energy image of the depth silhouettes is computed as the global motion information. Then, the forward-MLMHI and backward-MLMHI is computed as the local motion information based on the variable of depth. The global and local motion information constitute the MLMHI lastly. Since the Hu moments are sensitive to disjoint shapes and noise, R transform is employed to extract features from every layered-MHI and concatenated to form a feature vector. The feature vector is used as the input of Support Vector Machine (SVM) for recognition. Experimental results demonstrate the effectiveness of the proposed method.

RANdom SAmple Consensus (RANSAC) performs poor with the mass of data, high outliers ratio and complicated models. In this paper, a highly parallel voting version of RANSAC is presented. On the basis of parallelizing the hypothetical stage and generating multiple models simultaneously, a novel strategy of voting to determine whether a point belongs to inliers is proposed. Conventional search for the inliers relative to the best model is saved. On parallel platforms represented by FPGA, this algorithm can take advantage of the parallel architecture and characteristics to achieve deep-pipelined parallel computing. Experiments demonstrate the good robustness of the proposed algorithm and its considerable improvement of both speed and throughput.

Based on fast convolution algorithm, improved parallel FIR filter structures are proposed for linear- phase FIR filters where the number of taps is a multiple of parallelism. The proposed parallel FIR structures not only use fast convolution algorithm to reduce the number of sub-filters, but also exploit the symmetric coefficients of linear-phase FIR filter to reduce half the number of multiplications in sub-filter section at the expense of additional adders in pre-processing and post-processing blocks. The proposed parallel FIR structures save a large amount of hardware cost for symmetric coefficients from the reported parallel FIR filter structures, especially when the length of the filter is large. Specifically, for a 4-parallel 144-tap filter, the proposed structure saves 36 multipliers (14.3%), 23 adders (6.6%), and 35 delay elements (11.0%) from the improved Fast FIR Algorithm (FFA) structure.

To utilize effectively the reporting slots in Cooperative Spectrum Sensing (CSS) and enhance the sensing performance, a novel CSS framework is designed. The core idea of the proposed framework is that, when a Secondary User (SU) is reporting the sensing results, the following SUs continue local sensing until their turns to report. Since a half of idle reporting slots are appropriately utilized for sensing, the proposed framework behaves more efficiently. Moreover, based on Neyman-Pearson criteria, the optimal schedules for AND rule and OR rule are investigated respectively, followed by the discussions of the sensing performance gains under the proposed framework. Simulation results demonstrate that, the proposed framework enhances the CSS performance considerately without any additional sensing delay.

In order to improve the robustness of the multi-cell multi-user multi-antenna downlink beamforming under the circumstance of considering the transceiver impairment and the imperfect channel information, two robust algorithms are proposed to solve the optimization issues considering two non-ideal factors. By releasing the non-convex constraints step by step, the original robust non-convex optimization issues are transformed to relatively easy-to-solve equivalent issues. The issues are effectively solved by using convex tool box, and the proposed algorithms are compared with traditional algorithms. Numerical simulations show that the proposed two algorithms can achieve better average-SINR and worst-SINR than the conventional algorithms without considering the two non-ideal factors.

This paper analyzes the optimal density and power allocation for the D2D (Device-to-Device) communication in heterogeneous networks on multi-bands with target of maximizing the D2D transmission capacity. The heterogeneous networks contain one or several cellular systems, and the D2D communication shares uplink resources with them. By utilizing stochastic geometry, it is formed as a sum capacity optimization problem for the D2D network with constraints that guarantee outage probabilities of both cellular and the D2D transmissions. Since the original problem is non-convex, the proof work is divided into two steps: first, it is proved that the power allocation problem is convex when the D2D density is fixed, which can be solved by Lagrangian method; and then that the feasible region for the D2D user density is divided into finite sub-intervals by the outage constraints and the local maximum D2D transmission capacity can be obtained by the derivative method. A sub-interval linear searching algorithm based on the above conclusions is proposed. The simulation results demonstrate the effectiveness of the proposed algorithm and show that the optimal parameters of the D2D transmission is mainly affected by the outage constraints and the interference from cellular systems.

In Massive MIMO-OFDM systems, the channel shows strong correlations in both spatial and frequency domain. Aiming at the problem that only spatial or frequency domain correlation is considered in most of the existing compressed feedback algorithms, a joint spatial-frequency compression algorithm is proposed. First, a two dimensional sparsity of channel in spatial-frequency domain is analyzed according to the compressed sensing theory. Then, a joint sparse matrix of channel is derived. Based on the joint sparse matrix, the joint spatial-frequency compression algorithm is presented. Simulation results and analysis show that, the proposed algorithm can significantly reduce the feedback load with acceptable accuracy.

This paper presents a novel subcarrier combining based multicast resource scheduling algorithm for wireless OFDM multicast systems. By dividing subcarriers into different groups in advance, the algorithm avoids invalid subcarrier pairing, and adaptively chooses the optimal scheme between subcarrier diversity and subcarrier multiplexing by deciding whether to combine subcarriers or not. Moreover, according to the characteristic of subcarrier power allocation, this scheme decouples the problem into two sub-problems of intra-subcarrier-pairing power allocation and inter-subcarrier-pairing power allocation, which further improves the performance of the system. Simulation results show that the proposed scheme properly improves the system performance with lower complexity compared with the existing schemes.

To solve the issues of the high complexity and poor performance in the equalization of high order and partial response Continuous Phase Modulation (CPM) signals, a new framework of tilted phase CPM transmitted signals is designed from the perspective of Rimoldi decomposition. A novel frequency domain equalization algorithm for high order CPM signals is proposed[0] based on the combination of single-carrier Frequency Domain Equalization (FDE) and Turbo equalization. This algorithm avoids the large matrix inversions in computation of the equalizer coefficients in time domain by transforming the signal equalization to frequency domain. Simultaneously, it improves the system performance by soft information iterative process. The analysis and simulation results show that in multipath fading channels with serious inter-symbol interference the proposed algorithm provides a relatively lower computational complexity and a performance gain of about 1.5 dB in signal-noise ratio compared with the previously proposed FDE algorithm based on symbol for fourth-order and partial response CPM signals.

Based on OFDM amplify-and-forward cooperative relay system, in order to reduce the transmission bit error rate, while increasing the channel capacity and improving the usability, the paper presents a practical limited bits feedback precoding method where the source node precoder and the relay node precoder are jointly optimized. Through the use of the two downlink with three nodes, the two-hop cooperative communications are achieved, and the precoding matrices are designed using both orthogonal triangular (QR) decomposition and Singular Value Decomposition (SVD), in which the source node precoder contains only one precoding matrix per OFDM frame. By choosing a better codebook, the quantization precoders are feedbacked to the transmitter. The simulation results indicate that the proposed method is able to improve the system average sum-rate, reduce the error rate and improve the performance of outage probability, indicating a chance of better usability as result of fewer bits.

Single-channel blind separation of several time-frequency overlapping communication signals, which has  potential and wide application, is a hot and intractable point in the field of communication signal processing. The modulation type and source number are necessary for blind separation of several mixed signals received by single channel. In this paper, cycle frequencies of second-order and fourth-order cyclic cumulants of digital modulation signals are investigated. Based on the features of cycle frequencies, a novel method for modulation identification and source number estimation is proposed for single-channel mixed communication signals, and an algorithm is presented. The proposed approach does not need the prior information such as power, carrier frequency, symbol rate, time recovery and so on, and can effectively identify the source number and modulation type of each source when the signal received by single channel is a random mixture of several kinds of typical communication signals (BPSK, QPSK, OQPSK, MSK etc.). Through simulations under different conditions, the performance of the proposed algorithm is examined, and its effectiveness is also demonstrated.

One of the key technologies in smart grid is an efficient, reliable and secure two-way communication system for meter data collection. Forming wireless mesh network with advanced electricity devices (smart meters), which have the communication capabilities for meter data collection, faces challenge on network communication performance caused by application layer data traffic. When a large number of data occur in emergence, the smart meter near the local LAN gateway faces great communicaton pressure, and it probably leads to extreme data congestion. Therefore, a new traffic scheduling algorithm is proposed based on the idea of the joint of muti-gateway to release the congestion of system. First, the muti-gateway mesh network is analyzed to study the main factors affecting network performance. Second, a new traffic scheduling algorithm is proposed with the idea of weighted queue of node. Simulation data show that compared with other algorithms, the new algorithm can release significantly the congestion of burst data, and it reduces effectively the latency and obtains a good balance among the throughput of the system gateways, which can improve the network communication performance.

The 3D cipher is a new block cipher proposed in CANS 2008. The design principles of 3D are built on the AES, but it is different from the other known block cipher as it uses the three dimensional structure. In this paper, some 6-round impossible differential distinguishers are created, and hence extended to breakable 11-round 3D cipher based on these distinguishers. As a result, the time complexity of 10-round impossible differential attack on 3D is reduced to 2^318.8 . The technique of precomputation is widely applied, which offers a meaningful reference both on the actual attack of block cipher and to enhancement of efficient computation process.

Erasure codes and regenerating codes can guarantee data reliability, but fail to provide data confidential when some nodes are observed by eavesdropper. Thus, two regenerating code schemes satisfying the security property against the eavesdropper are proposed in this paper. Combining the All-or-Nothing transform and exact repair regenerating codes, the proposed schemes not only ensure that an intruder eavesdropping limited number of nodes are unable to obtain any meaningful information about the original data symbols, but also provide data reliability with low repair bandwidth. Furthermore, a general construction method is presented, and the security is proved, and the performance of the proposed scheme is evaluated by a serial of experiments. The result shows that the proposed schemes achieve faster encode/decode procedures and better secrecy capacity compared with other secure regenerating coding schemes or threshold storage schemes.

LRU has been widely used in single-core processor, while Chip Multi-Processors (CMP) employ a large Last-Level Cache (LLC) which is shared among the multiple cores. With the increasement of the LLC capacity and associativity, and the grows of working set of multicore’s applications, the performance gap between the LRU and the theoretical optimal replacement algorithms gets wider and wider. This paper proposes an Average partition LRU algorithm based on Frequency (ALRU-F). The algorithm has maintained the working set at Cache and drive out the ignore block. Also, a Cache line stealing strategy is proposed to realize a Block partition LRU replacement algorithm based on Frequency (BLRU-F). The result of experiments shows that comparing to the traditional LRU algorithm, the proposed ALRU-F algorithm reduces the miss rate by 26.59%, and improves the Instruction Per Clock (IPC) by 13.59 % with little change of power consumption. Comparing to the traditional LRU and BLRU-F algorithms, the proposed algorithm reduces the Cache miss rate by 33.72% and improves the IPC by 16.59%.

In this study, the virtual network mapping issue in network visualization area and its current research progress are reviewed, and the main issues in admission control and algorithm performance evaluation for existing virtual network mapping algorithm are pointed out. Then the virtual network mapping approximation algorithm with admission control is proposed, and the competitive analysis of this algorithm is provided. Experiment result shows that the proposed algorithm increases the physical network resource load balancing metric and the coefficient of utilization, hence it can improve the virtual network construction request acceptance ratio and the income profit of physical network service provider.

Considering that the characteristic of Logistic chaos system varies in the relationship of the parameter μ, and the feature of that the relative entropy reflects the lack of equilibrium, this paper proposes a new method to estimate the characteristic of Logistic chaos system based on symbolic relative entropy. Numerical simulations prove that, Logistic chaos system possesses the property of time irreversibility which increases with parameter μ and is irrelevant with initial value x₀. Accordingly, a novel quantifiable nonlinear dynamical behavior index is obtained, which provides the theoretical basis for understanding Logistic chaos characteristic and chaos control.

The design ideas and performance process of a super-wide band and two channels output circuit on a klystron are presented. A super-wide band two-channel double-gap coupled-cavity output circuit, whose bandwidth is over 550 MHz, is designed at S band by Ansoft HFSS. A channel switch structure is designed, and the resonance parameters of the two channels are determined. Then, a conclusion is made that channels can be switched easily through tuning the coupled-slot without changing the parameters of the two cavities. The frequencies of each mode in the double-gap coupled-cavity output circuit are simulated through calculating the model by Ansoft HFSS. The frequencies of each mode accord with the “cold test” mainly. The gap impedance of double-gap coupled-cavity, which is simulated by analysis of equivalent lumped element circuit, also accords with the “cold test” very well.

The multijunction waveguide array antenna is one of the key components for plasma heating and current drive on EAST superconducting Tokamak device, and its structure performance determines the plasma current heating and drive efficiency. When the plasma current rupture, the eddy currents are induced in the antenna because of the plasma current decay in a short period. These induced currents interact with the strong static magnetic field to produce forces and torques in the antenna, which will damage the structure of the antenna. Electromagnetic analysis of 4.6 GHz Lower Hybrid Wave (LHW) antenna in EAST is investigated. The forces and torques of LHW antenna are performed using the finite element method. Then the electromagnetic stresses and displacements due to electromagnetic loads are also calculated. The simulation results offer guidance for the design and manufacture of the antenna.

A stable Fixed-Outline Floorplanning (FOF) algorithm for soft module is proposed in this paper. It takes the Normalized Polish Expression (NPE) as a floorplan solution, using the shape curve adding algorithm and the interpolation technique to compute the best floorplan of a NPE. The Simulated Annealing (SA) algorithm is used to search the solution space. A post-floorplanning optimization method based on the new Insertion After Delete (IAD) operator is adopted to optimize those SA floorplan solutions which fail to meet the fixed-outline constraints. The experimental results on eight GSRC and MCNC benchmarks show that the proposed algorithm can not only achieve a nearly 100% floorplanning success rate under fixed-outline constraints with 1% white space but can also obtain better total wirelength than previous works. Besides, the proposed algortihtm has a greater advantage in the runtime over the similar SA-based algorithms.

In the Gaussian noise background, an algorithm is proposed to jointly estimate the multiuser DOA and self-calibrate the mutual coupling error for Uniform Linear Array (ULA). First, the generalized spatial feature vector of each user is estimated by utilizing the Joint Approximative Diagonalization of Eigen (JADE) matrix method. Second a transformation matrix is defined, and based on which the generalized spatial feature vector is converted to the one which is related with part elements of the ULA. Then the multiuser coherent DOA estimates are obtained on the basis of the oblique projection and Forward and Backward Spatial Smoothing　(FBSS) methods. Finally, a mutual coupling self-calibration method is presented by utilizing the estimates of the DOA and the generalized spatial feature vector of each user. The computer simulation indicates that the algorithm has higher performance of DOA estimation accuracy and successful rate. The simulation results also demonstrate that, the proposed algorithm is universal for the situations where the mutual coupling error is known or not with white or colored additive Gaussian noise.