The request for efficient compression of hyperspectral images becomes pressing. A cluster-based lossless compression algorithm for hyperspectral images is presented. Because the spectral correlation differs in different bands, spectral band grouping algorithm is introduced to divide hyperspectral images into groups according to the correlation between each adjacent bands. The important bands which contain large useful information can be determined by using the adaptive band selection algorithm, on which k-means clustering is carried out according to the spectral vectors. The current band is predicted by using several preceding bands. For each pixel which belongs to a certain cluster, some causal neighboring pixels which have been coded are trained to get the optimal predictive coefficients. The reference bands are compressed by JPEG-LS standard while the final predictive errors are coded by Golomb-Rice. Experimental results show that the proposed methods produce competitive results when compared with other state-of-the-art algorithms.

Different inside regions of harbors show different shapes from remote sensing images. A method of harbor target recognition based on inside region is proposed. Firstly, potential sea regions are segmented from image by using histogram and dilation operations. Secondly, the coastline is partitioned into a series of feature points with polygon approximation in order to compress the shape description datum. After calculating the closure from feature points, the inside regions are extracted. Straight lines and corner structures are detected to reduce false alarms. Then the principal orientation of inside region is rotated to the same right horizontally to avoid the rotation effect. Finally, the features are extracted to measure the similarity. Experiments show that harbors are detected accurately using the proposed method. Besides, the extracted features have good invariability and can meet the need of recognition.

A linear feature extraction algorithm for Synthetic Aperture Radar (SAR) image is proposed, which is based on the low signal-to-noise quality of SAR image. Firstly, a new edge detector, which fuses the Canny operator and Ratio Of Average (ROA) operator, is used to get the edge points. Then, radon transform is carried out to get the primitive line segments. Finally, the broken lines due to speckle noise are connected by means of the heuristic link idea. The experiment results which are based on the SAR images show, the proposed algorithm can describe the linear characteristic of SAR images precisely, and it can be used for SAR auto target recognition and scene matching.

A new method for detection of maneuvering target in wideband signal and for estimation of its moving parameters is proposed. Firstly the adjacent correlation is employed to decrease the order of the echo signal. Then the signal is transformed into range frequency domain and the general two-order keystone transform is used to eliminate range curve. Thirdly a range frequency cell is selected to estimate the azimuth frequency modulation rate via the time-chirp rate transform. Fourthly a phase compensation function is constructed for phase correction. Finally the general second-order keystone transform is used again and the range IFFT and azimuth FFT are performed so that the target detection is feasible. The moving parameters can be obtained by the estimates. In the end, simulated and raw data results confirm the effectiveness of the proposed method.

By the method of stationary phase and the concept of HQBA (Half Quasi-Bistatic Angle), an exact two-dimensional spectrum of translational-invariant bistatic SAR is derived in this paper. Based on the analysis of every exponential term in the expanded spectrum, a flow chart of Range-Doppler algorithm with the computation of HQBA is proposed. Simulation results of HQBA, RCM and focused points are also provided. As they show, the proposed method can correct the RCM accurately, and improve the imaging quality.

Since the small Radar Cross Section (RCS) and complicated buried environments of shallow buried targets will lead to large numbers of false alarms in the detection results of single frame image, a novel detection method called as “prescreening-alternately backward tracking-multiframe confirmation” is proposed in this paper. Firstly, the prescreening of images is made by the Constant False Alarm Rate (CFAR) detector, then followed by a morphological filter and clustering analysis. Secondly, the clustering centers of the current frame range multi-look image are utilized to mark the potential targets for tracking, and a new alternately backward tracking method is used to obtain the potential object tracks. Finally, the tracks are employed to compute the weighted historical confidences, which are exploited to eliminate the natural clutters and confirm targets. Experimental results of the real data show that the proposed approach can acquire the regions of interest fast and robustly, reduce the false alarms obviously.

The echo signal model of MultiCarrier Modulated radar system based on OFDM (OFDM-MCM) is introduced firstly, the expression of the match filtering output is deduced based on it, and the detection probability is analyzed, then simulation of the Integrated SideLobe Ratio(ISLR) of the pulse compression output and Receiver Operating Characteristic(ROC) between the Single Carrier Modulated (SCM) radar and OFDM-MCM radar is compared. The simulation results indicate the OFDM-MCM radar has the better pulse compression performance and higher detection probability for high speed target.

In the application of distributed-satellite Along-Track InterferometrySAR (ATI-SAR) for Ground Moving Target Indication (GMTI), measurement error of baseline will affect the system’s GMTI performance. This paper analyzes the satellite cluster’s actual flying tracks, establishes the velocity-error model caused by baseline-measurement error considering the baseline’s time-variety, proposes a novel method to measure baseline accurately and obtain perfect performance of system’s GMTI. Finally, the simulation experimental results prove the conclusion proposed.

Multi-channel SAR system can avoid the minimum antenna area constraint, thus achieving wide swath and high resolution SAR image. There are more deleterious factors in multi-channel SAR system compared with single-channel SAR system, which may degrade the quality of SAR image greatly. In this paper, all the deleterious factors in the system are analyzed and classified according to their impact on the SAR imaging processing, and approaches of array error estimation and its compensation are presented, respectively. The validity of the proposed method is verified by experimental results of measured Tri-channel SAR data.

For the needs of precision-guided striking task and to develop an image compression and translation system which based on “man-in-loop” SAR, a general task-drive intelligent and fast detection framework of SAR images is proposed according to the same character of non-specific and strong scattering in ROI of precision guided missiles. Started from practicality of the detection which need the algorithm be intelligent, fast, high performance, this framework takes two-step CFAR detection as the core step, which used the rapid structural component preview to guide the intelligent and rapid detection in original image. Theoretical analysis and experimental results show that this framework is a good detecting scheme which has same overall flow and different local implementation details for different goal, so it has strong practicality and excellent expandability.

This paper studies the problem of signal detection in clutter with unknown statistical properties for the airborne MIMO radars. Firstly, a Generalized Likelihood Ratio Test Detector (GLRTD) is proposed to improve the detection performance exploiting the spatial diversity of MIMO radar, and the theoretical expression is derived for the detection performance. Secondly, a simplified GLRTD is derived based on the block diagonal property of clutter covariance matrix to reduce both the computational complexity and the secondary range cell numbers required for clutter covariance estimation, and a closed form expression of the detection performance is given for the special case of two receiver radar elements. The results show that both proposed detectors have CFAR with respect to the covariance matrix of clutter, and can effectively detect targets in clutter.

For solving the problem of texture blurring brought by traditional inpainting method, a regional texture synthesis based inpainting algorithm is proposed. The feature in the adjacent domain of each broken pixel is analyzed for choosing the template, and the broken pixels should be excluded from the template. The optimal solution for the broken pixel is determined by matching the template in searching area. The inpainting process proceeds from the edge to the center, for improving the validity and continuity of propagating direction of the texture in the flawed region, meanwhile the blurring can be eliminated. The algorithm is available to a wide variety of real-world textures, and produces a satisfying result for human visual system.

In this paper, a new Set Partitioning In Hierarchical Trees(SPIHT) coding algorithm is proposed, which is based on a Mixed Contourlet and Wavelet Transform(MCWT) and a new spatial orientation tree (MCWT-SPIHT). In the proposed image coding algorithm, Contourlet transform is employed for the first stage then followed by wavelet transform for the coarse scale. According to the structure properties of the MCWT coefficients, a new spatial orientation tree is developed to perform the SPIHT-like coding algorithm based on SPIHT coding idea of wavelet transform. Experimental results demonstrate that the proposed algorithm is competitive to wavelet transform, Contourlet transform and Wavelet Based Contourlet Transform(WBCT) with SPIHT in terms of Peak Signal to Noise Ratio (PSNR) at low bit rate, and it contains more contours and textures in the reconstructed images.

General histogram equalization technology have two drawbacks, it makes the enhanced image have a higher contrast while improvement of contrast dependents on heavily the distribution of gray frequency. So it often leads to enhance high frequency gray level excessively while compresses low frequency gray level. In addition, the enhance process lacks purpose, so it is difficult to meet the special requirements such as to enhance the specified interesting gray level. In order to solve this problem, image enhancement algorithm combines maximum gray frequency restrict with dynamic histogram equalization is proposed in this paper. Firstly, according to analyzing the image histogram and the interested in gray range, the gray range of each sub-level mapping and the frequency control threshold are selected. Then histograms of sub-level after restricting the maximum gray frequency are redefined, by adopting histogram equalization algorithm to construct gray transfer function, mapping sub-level gray to the appointed range. Finally the enhancement result of sub-level is composed. The experimental results demonstrate that this image enhancement algorithm not only could change the situation of the excessive enhancement, but also could control the interest gray level range, and it solves the application requirement that the image contrast enhancement could be controlled.

Directionlet transform can capture the image singularity due to possessing the multi-direction anisotropic basis functions. A texture classification algorithm based on the Mapping complex Directionlet Transform (M-DT) is proposed, which provides better directionality and approximate shift invariance. By space mapping for the texture image, then complex Directionlet transform is applied to the mapped image, and the multiscale subband coefficient energy feature is used for texture classification. The experiments using texture images from Brodatz and real SAR images indicate the proposed method outperforms wavelets and Multiscale Geometric Analysis (MGA) approaches, the potential application to image analysis by Directionlet is thus proved.

A new fast stereo edge-matching algorithm based on mountain images is presented. In order to ensure the accuracy of the match. Firstly the disparity gradient restriction across the direction of epipolar lines is used, and then on the basis of exclusionism searched the corner information close to edge point to guide the matching with restricted corners-searched range. The final match results ensure that the matching pairs in two images are one-to-one correspondences. The algorithm results show that the amalgamation of different restrictions improved the matching speed and precision.

Based on the audio amplitude distribution change caused by secret message embedding in different bit-planes, a method of secret message length estimation is presented in this paper. This method can not only discriminate the existence of secret message, but also recognize the embedding bit-plane and estimate the amount of secret message. The proposed method has been implemented on PC. The experimental result shows its good recognition performance and relatively high estimation accuracy of secret message length. The proposed method can be used effectively in audio steganalysis.

Dempster rule of combination is a useful fusion operator for decision level recognition fusion. The effective application of this rule depends on the rational construction of corresponding basic belief assignment. Considering the measurement information from each sensor in decision level recognition fusion, this paper suggests a group of principles for constructing basic belief assignment, and then presents a strategy of basic belief assignment construction based on the similarity degree between referential vector and the measurement information. The experiments on artificial data and real data of radar aerial target demonstrate the basic belief assignments constructed by the presented method can be fused by Dempster rule of combination effectively.

cDNA microarray expression data is widely used to help biomedical research. There are so many challenges when the computer and pattern recognition methods are used to process and analysis the data. In this paper, a novel hybrid cross-phenotype normalization method is proposed which deals with supervised multi-class multi-sample cDNA expression data set based on invariantly expressed genes. The algorithm can be directly used as a feature selection method for gene classifier. The result is satisfactory.

Traditional AAM (Active Appearance Models) improved methods on human facial features localization always concentrate on fitting efficiency without any concrete analysis of characteristic of the initial position and model instance, thus the location accuracy and speed are both not ideal. An initial position correction and model instance selection method based on facial features detection and simple 3D pose estimation is proposed. Adaboost algorithm is applied to pre-detection of facial features in the images firstly, then to extract features from the images that could not be detected or have been incompletely detected using facial skin properties in YCbCr color space. Finally，calculate the coordinate of the nose tip and deflection angle of the face according to features region, properly adjust the fitting center position and model instance and introduce linear algebra software ATLAS(Automatically Tuned Linear Algebra Software) into fitting process for matrixes optimization. Simulation experiments on IMM face database show that proposed method has increased the fitting accuracy rate by about 43% and the time consumption is decreased by about 62% comparing with traditional Inverse Compositional AAM Algorithm.

A novel Shuffled Particle-Pair Optimizer (SPPO) is proposed for speaker recognition based on vector quantization, which combines the advantage both in Particle Swarm Optimization (PSO) and Shuffled Frog-Leaping Algorithm (SFLA). The SPPO contains elements of local exploration and global information exchange to get global optimized speaker codebook. In this algorithm, the population is partitioned into 3 particle-pairs according to the performance, and each particle-pair consists of two particles. The particle-pairs perform simultaneously local exploration using basic operations of PSO (velocity updating and position updating) and LBG algorithm in sequence. A shufflingstrategy, in which the particles are periodically shuffled and reorganized into new particle-pairs, allows for the exchange of information between particle-pairs to move toward the global optimum. Experimental results demonstrat that the performance of this new method is much better than that of LBG, FCM, FRLVQ-FVQ, and PSO consistently with lower speaker recognition error rates, shorter computational time and higher convergence rate. The dependence of the final codebook on the selection of the initial codebook is also reduced effectively.

The algorithm based on quadratic phase function is efficient to estimate the parameters of the LFM signals. When it is dealing with the multi-comment LFM signals, spurious peaks arise and interference is severe. A new approach based on integrated quadratic phase function is proposed to solve the problem. The performance of the proposed approach is evaluated by simulation to show that the method presents advantages in terms of that it can suppress the spurious peaks and interference and gives a closer approach to the CRLB and a lower SNR threshold with respect to the quadratic phase function.

The active arrays can extend the virtual aperture greatly by transmitting orthogonal signals, and degrees of freedom are increased exponentially. In this paper, By transmitting orthogonal signals , virtual subarrays are designed, and the Virtual Subarrays Smoothing(VSS) algorithm is proposed for the coherent case. Virtual subarrays with identical sensors avoid the reduction of the array effective aperture, and make this approach estimate coherent returns at most. Simulation results show that the VSS algorithm is effective and need only a little sensors transmitting signals.

A novel blind channel estimator based on computing Roots of Matrices (RM) is proposed for OFDM systems. This algorithm exploits the finite alphabet property of information symbols and implements channel deconvolution by computing the Jth principle root of a low-triangular Toeplitz matrix. Therefore, RM algorithm has much lower computation complexity than searching algorithms in previous works and is able to function in the case of large channel order that is intractable by searching algorithms. Moreover, an Adaptive RM (ARM) algorithm is proposed to adjust RM estimator by steepest descent method. Simulation results indicate that RM algorithm has great accuracy comparable to the optimal exhaustive search and ARM improves the estimation performance of RM considerably.

Focusing on the problem that the orthogonality of Orthogonal Space-Time Block Codes (OSTBC) in frequency-selective fading channels is destroyed, a novel decoding scheme based on interference cancellation is proposed. This scheme adopts interference cancellation and interference nulling to cancel multipath interference, which is used in D-BLAST system. Thus the expected signals are detected effectively. Theoretical analysis and simulation result show that, compared with iterative interference cancellation decoding algorithm, this scheme can improve the bit error rate efficiently and reduce the decoding complexity at the same time. The proposed sheme is especially suitable for environments with small rank of channels.

It is often desired to widen the interference null width to enhance the robustness of the algorithm in some real anti-jamming environments. A novel space-time adaptive processing algorithm which broadens the null width is proposed in this paper. The proposed method modifies the covariance matrix of wideband jamming based on the analysis of the model of wideband signal and the rotation of the space-time steering vector. When the data mismatch is smaller, the broadening nulling algorithm can effectively suppress interference, which increases the robustness of the algorithm.

A modified EXtrinsic Information Transfer chart (EXIT chart) method is proposed. This EXIT chart is adopted as a tool to analyze the convergence behavior and to predict the performance of turbo equalization in additive non-Gaussian impulsive noise channel. The probability distribution of the extrinsic information is estimated to improve the traditional EXIT chart under symmetric α stable noise environment. Together with the Bit Error Rate (BER) analysis, the performances of turbo equalization, such as iterative trajectory, iterative convergence and the BER value at each iteration, are predicted. The experiments on the truncated turbo equalizer show that the predicted performances are consistent with the simulated results. Thus the validity of the proposed method is verified.

In OFDM systems，the channel fast variations destroy the orthogonality among sub-carriers, resulting in inter-carrier interference (ICI) which degrades the system performance. Aiming at time-varying characteristic of doubly-selective channels, a channel estimation algorithm is proposed by a new Kalman filter, and is applied to the Oversampled Complex Exponential Basis Expansion Model (OCE-BEM), changing the variable channel parameters in the period of one OFDM symbol into invariable ones. Meanwhile, this new Kalman filter is combined with the low complexity LMMSE Turbo equalizer based on ICI suppression, and CRC checkout is used to control the iteration times of the algorithm, so it need not many pilot symbols in practice, still can ensure the algorithm performance and reduce the time-delay and complexity of this algorithm.

A new adaptive anti-collision algorithm based on binary-tree disassembly is proposed in this paper. In order to enhance the search efficiency, a big and complex binary-tree is disassembled to several small and simple binary-trees by estimating the distributing of tags. The introduction of the collision stack, as well as adjusting the search paths adaptively based on the state of slots, the performance of the new algorithm is improved further, including reducing the search timeslots and improving the throughput of timeslots. Theory and computer simulations show that the new anti-collision algorithm is practical, especially when the number of tags is large.

In DS-CDMA systems with Successive Interference Cancellation (SIC), the numbers of possible rate modes and decoding orders grow exponentially with the number of users. How to allocate rates in order to maximize the system utility is an NP problem, which involves the joint optimization of rate allocation and decoding order adjustment. This paper proposes two suboptimal greedy algorithms for addressing this NP problem. The main idea of the algorithms is that the rate mode is greedily updated step by step, then the decoding order is adjusted for the updated rate mode in every step and the feasibility of the corresponding rate mode is quickly examined according to the adjusted decoding order. The proposed algorithms have very low computational complexity and can be used to implement the quick and efficient allocation of rates. Simulation experiments validate this analysis and demonstrate the effectiveness of the algorithms.

The probability distribution of radio wave that undergoes certain number of collisions at a specific spatial location should be solved. This probability is used to model radio propagation channels with the method of stochastic rays. The maximum entropy principle in information theory is utilized to calculate the corresponding probability in the current research. Under Manhattan metric, the 2-dimensional and 3-dimensional continuous probability density functions (pdfs) and discrete probability mass functions are calculated. Under Euclidean metric, 2-dimensional and 3-dimensional continuous pdfs and discrete probability mass functions are also calculated, and the pdf of stochastic rays undergoing random walks is derived. The results of theoretical model based on stochastic rays are validated by experimental dada measured in dense urban propagation scenario. The results of the paper are important to the modeling of wireless stochastic propagation channels.

Utilizing the Householder transformation, and combining with the WY representation, a Modified Householder QR-Decomposition (M-H-QRD) algorithm is proposed firstly. In contrast to the sorted QRD (S-QRD) detection algorithm, the M-H-QRD detection algorithm has robust numerical property. Then an iterative detection algorithm for V-BLAST is proposed based on M-H-QRD. The simulation results show that the iterative detection algorithm can achieve obvious performance improvement over the S-QRD detection algorithm and the M-H-QRD detection algorithm. In contrast to the standard V-BLAST algorithm, the iterative detection algorithm has almost the same detection performance as it for high SNR, and outperforms it in the moderate and low SNR region with more robust numerical property.

The performance of distributed space-time code can be severely degraded due to timing offsets among relay nodes. Focusing on this problem, an Asynchronous Distributed Linear Convolutional Space-Time Code (ADLC-STC) is proposed in this paper. By designing a family of generating matrices with special structures, the proposed ADLC-STC can achieve full diversity order under frequency-selective channels without the synchronous assumption. Moreover, because of its linearity, the proposed ADLC-STC can be decoded by zero-forcing (ZF), MMSE, MMSE-DFE detectors. Theoretical analysis and simulation results show that, with the suboptimal detectors, the ADLC-STC can achieve full diversity order without the synchronous transmission assumption.

An improved algorithm based on the bi-directional M-BCJR algorithm for V-BLAST in the frequency selective channel is proposed in this paper. The improved algorithm improves the performance of the bi-directional M-BCJR algorithm with little complexity increase by using a new metric and using the Kullback-Leibler distance for bi-directional search. The performance of the improved algorithm is confirmed by simulations.

A Block-Level Space-Time Block Code (BL-STBC) is firstly proposed for Multi-User Multiple-Input Multiple-Output Single-Carrier Frequency Division Multiple Access (MU-MIMO SC-FDMA) systems. Next, employing the algebraic properties of the BL-STBC and a particular permutation matrix, a low-complexity algorithm is derived for the multi-user detector. Finally, the average bit error rate is given via simulation. The performance of the BL-STBC is better than the space-frequency block code, with no added complexity, if the distributed sub-carrier mapping is used.

In order to improve satellite switching performance, a new scheduling algorithm is proposed. Based on Crossbar switch fabric，the algorithm adopts serial scheduling strategy and adjusts the output port arbitrating strategy for the better equity of every port. Consequently, it increases the matching probability. The algorithm can greatly reduced the scheduling delay and loss rate. The analysis and simulation results show that the proposed algorithm has the better performance than others in average delay and cell loss rate, and has the equivalent complexity.

This paper discusses the cryptographic properties of Multi-output plateaued functions, the relationship among difference, Walsh spectra and the order of Multi-output plateaued functions is established. The Walsh spectra distribution of Multi-output plateaued functions is given under certain conditions. Pointed that when any nonzero linear combination of the coordinate functions of the multi-output plateaued functions are not balanced, the relationship among the number of input variables, number of output variables and the order satisfy .

Orthomorphic permutations have important application in the design of cryptosystems. Based on the one-to-one corresponding relationship between orthomorphic permutations and transversals of orthomorphic Latin square, the construction issue for orthomorphic permutations is studied, a new construction method is proposed to construct a (n+1)-bit orthomorphic permutation from a n-bit one where n＞1. The method extends to obtain a composite transversal of orthomorphic Latin square An+1 by employing a transversal of orthomorphic Latin square An and its supplementary sequence transversal, based on composite transversal of , An+1 transversal of An+1 is constructed. Using the method, 22n (n+1)-bit orthomorphic permutations from a n-bit one can be obtained.

Based on two different chaotic systems synchronization and parameter modulation, a novel method of realizing chaotic secure communication is proposed in this paper. Information signals are used to modulate some parameter of a chaotic system in the sending terminal, based on Lyapunov stability theory, the proper controllers are designed to realize two different chaotic systems globally synchronization. The appropriate nonlinear filter is designed in the receiving terminal to make the information signals recover effectively, realizing the secure communication. The simulation results show that systems realize synchronization quickly, and the recovered signals are close to the information signals and it can realize secret communication successfully, having strong security and practicability.

Electronic payment protocol is a kind of important electronic commerce protocol, and fairness is one of the desirable secure properties payment protocols should achieve. A new approach based on Hierarchical Timed Coloured Petri Nets (HTCPN) for modeling and analyzing fairness in payment protocols is proposed in this paper. In the analysis of fairness, it takes the honesty of principals and the reliability of communication channels into consideration. Compared with other formal methods, it can analyze fairness of protocol more efficiently. By this approach, a typical payment protocol IBS is modeled and analyzed, and the analysis result can prove the availability of the proposed model and approach.

To circumvent the transmission performance degradation of Orthogonal Frequency Division Multiplexing (OFDM) systems due to the nonlinear HPA, a new predistorter is presented to predistort HPA which consists of two similar single-input and single-output Neural Networks (NNs) in series. The former NN is the inverse model of HPA’s AM-AM characteristics to compensate its amplitude and the latter the model of AM-PM characteristics to compensate its phase. The phase predistortion is implemented just by its model rather its inverse model, which ensures it of much higher precision. Simulation results show that even though input back-off is as low as 2.93dB, the spectral regrowth can be reduced about 10dB. The proposed scheme can adaptively predistort HPA effectively and simply, and improve transmission performance of OFDM system greatly.

A feedback-based Adaptive Reference Picture Selection (ARPS) is proposed for improving error resilience in real-time video transmission. The novel predictive structure which the reference picture selection can be optimized with rate-distortion method is designed by taking advantage of classic reference picture selection. The bit-rate of coding with difference reference pictures is analyzed, and its impact on source distortion is discussed. By first introducing the concept of average channel cost, the propagation of channel error and its impact on channel distortion is studied. Within joint source-channel rate-distortion optimization framework, the video picture that leads to the minimum rate-distortion cost is selected as the current reference picture, which can efficiently enhance the video transmission quality and decrease the number of reconstruction frame buffers of encoder/decoder. Simulation results show that the proposed ARPS algorithm outperforms the classical ACK and NACK RPS method in different bit-rates and lost-rates in PSNR.

As the broadcasting networks have no feed back channel, the sender has no idea about the packets loss during the packets are transmitted. Signals may reduce and the Probability of Packet Loss (PPL) increases, when the terminals are on the edge of the cell or blocked by some buildings. A patching Forward Error Correction (pFEC) mechanism is proposed to provide low PPL in broadcasting networks. The mobile networks are used as the return channel to get the information of PPL, and the redundancy packets are transmitted via mobile networks for reducing the PPL. This mechanism provides the different packet loss recovery ability for different people according to the reports from receivers. The simulation results show that if the mobile networks are in a low PPL condition, the pFEC mechanism will have a good performance in decreasing the PPL, and improves the reliability and quality of service.

This paper introduces the concept of time-frequency channels into multi-radio multi-channel 802.11 wireless mesh networks for the first time. Time-frequency channels are gotten by dividing wireless resource from two dimensions: time and frequency. This division scheme increases the number of channels, makes channel division much fine, and does preparation for improvement of the channel utilization rate. The quasi-dynamic channel allocation algorithm is proposed based on the time-frequency channel. This algorithm shall be combined with other fix channel allocation algorithms to realize quasi-dynamic channel allocation and achieve maximum throughput with the load changes on each link. Firstly, this algorithm distributes same number of time-frequency channels to each link and the left time-frequency channels are taken as common channels. During the communication process, every link shall make use of its own channels and idle common channels. If the channels assigned to a link are not enough and some channels of other links are idle, this link can occupy these idle channels temporarily. Theory analyses and simulation results prove that the algorithm can improve the throughput of the system effectively.

Multicast based stream scheduling algorithm can reduce server and network bandwidth consumption efficiently. But recent studies have indicated that user VCR interactive operations can severely penalize the scalability of these stream protocols. A new stream scheduling scheme, called Regular Multicast Fixed Scheduling (RMFS), is proposed to support interactive playback control in video-on-demand system. RMFS adopts the class-based admission control mechanism to admit client requests and consolidates the unicast stream through stream merging mechanism. The optimal multicast interval, the optimal request threshold and server channel capacity requirements for the RMFS scheme are all analyzed. Extensive simulation results verify the correctness of the analytical model and the feasibility of the presented RMFS.

The multiple-plane and multiple-stage (MPMS) switching fabric has attractive scalability features that make it appealing as an alternative for scalable routers. However, scheduling packets in MPMS fabric is complex. In this paper, a novel scheduling scheme is proposed with bandwidth guarantees for the MPMS fabric. It can deliver 100% throughput under Bernoulli uniform traffic, 92% throughput in the worst case under nonuniform traffic and allocate bandwidth according to reserved bandwidth under overloaded traffic.

Aimed to testing interconnect network that includes 3-stage programmable switches in FPGA, this paper proposes a novel size-independent approach based on a matching theory to minimize the number of test configurations. By constructing the graph of structure test, this paper presents a slicing scheme based on the path pace of the graph, and a method that applies the minimum coverage and maximum matching principle from the graph theory to obtain the minimum number of test configurations. For different interconnect network structure, the number of test configurations in the proposed method is reduced by at least 10% compared with other methods.

This paper, with the analysis of the propagation characteristics in a lossy cylindrical waveguide and using small-signal theoretical dispersion relation, presents study on the device stability with influence of the absolute instability and the backward wave oscillation in TE₀₁-mode lossy dielectric-load gyrotron traveling wave amplifier. The numerical results show that lossy dielectric-load can heighten the start oscillation current of absolute instability, and increase depends on the magnetic field strength and the perpendicular-to-parallel velocity ratio of the electrons; The thickness of the lossy waveguide increases the start oscillation length of backward wave oscillation. The combined appropriate selection of the lossy waveguide thickness, permittivity, voltage, the applied magnetic field and the velocity ratio can effectively give attention to bandwith and instability to ensure the stable operation of the gyrotron traveling wave amplifier.

An ellipse-like UWB dipole is investigated in this paper. By designing a novel antenna structure, which can effectively reduce the current reflection at the end of dipole, the input impedance is improved, and the bandwidth is widened. The dipole is more effective than the resistance loaded bow-tie antenna. In this article, the dipole is analyzed and designed by an EM simulation tool and a sample antenna is produced based on the design results. The VSWR and radiation pattern of the proposed antenna are measured and the results prove the validity of the simulation. The results indicate that the novel antenna has a wide bandwidth and a good radiation performance.

For the synthesis of the symmetrical sparse linear arrays with some thinned rate, only taking some elements rounds the end of the aperture into account will have the same effect on the peak side lobe level with taking all the elements into account. Using statistical method ,the distribution characteristic of elements of many optimum thinned arrays are studied in this paper firstly, then a aperture release model is presented to synthesize the symmetrical thinned arrays, this model can reduce the computing burden and improve the efficiency in the optimization without expense of performance. Finally, some test and analysis to testify the advantages are presented.

The effect of channel estimation error on the performance of Multiple-Input Multiple-Output (MIMO) Zero-Forcing (ZF) receivers in uncorrelated Rayleigh flat fading channels is investigated, and a novel algorithm of power allocation and adaptive modulation is proposed in this paper to maximize the system effective throughput. To reduce the channel estimation error’s effect on actual system throughput, the SNR derived at the transmitter is modified, which is used in power allocation and adaptive modulation. With the sum of transmit power limited, the power allocation of transmit antennas uses spatial water-filling theorem and bit allocation, and ensures the power of the antenna with high modulation data symbols. The numerical results show that the system effective throughput of the proposed algorithm is near optimal with acceptable implementation complexity, which is suitable for the actual system.

A significance coding algorithm based on layer model is proposed. Without changing the context template of JPEG2000, the proposed scheme uses an explicit layer template to dynamically arrange the scan path of wavelet coefficients. Experimental results show that the proposed scheme provides better autocorrelation outputted bit stream than stripe scanning of JPEG2000 and Hilbert curve scan; and the proposed scheme improves over stripe scanning and Hilbert curve scanning in terms of average bit rates by 1.06% and 0.57%, respectively. Moreover, the proposed scheme achieves an improvement 1.08% over context quantization optimization algorithms based on JPEG2000 in terms of average bit rates.

Most fault localization techniques is based on time windows. The size of time windows impacts on the accuracy of the algorithms greatly. This paper takes weighted bipartite graph as fault propagation model and proposes a heuristic fault localization algorithm based on Incremental Bayesian Suspected Degree (IBSD) to eliminate the above shortcomings. IBSD sequentially analyzes the incoming symptoms in an event-driven way and incrementally computes the Bayesian Suspected Degree and determine the most probable fault set for the current observed symptoms. Simulation results show that the algorithm has high fault detection ratio as well as low false positive ratio and has a good performance even in the presence of unobserved alarms. The algorithm which has a polynomial computational complexity could be applied to large scale communication network.

Two handoff queuing schemes of Opportunistic Spectrum Access (OSA) system are proposed for non-real-time services. For each scheme, a two-dimensional Markov chain analysis is presented and the blocking probability, force termination probability and bandwidth utilization are obtained. Numerical results show that the handoff queuing schemes can greatly reduce forced termination probability and the bandwidth utilization can be improved by 26% compared to the handoff channel reservation scheme with high blocking probability and low bandwidth utilization. The simulation results are observed to match closely with the numerical analysis.

This paper studies the data transmission control with FC-AE-ASM (Fibre Channel-Avionics Environment- Anonymous Subscriber Messaging) network. The periodic task model in real-time communication is adopted. Based on the basic principle of FC-AE-ASM network, a data transmission control scheme is proposed based on the time slice rotation. The necessary and sufficient condition of guaranteeing data deadlines under the data transmission control scheme is derived. Taking the achievable link occupation ratio in the worst case as the main index, the superiority of the control scheme is also derived and finally tested with OPNET simulation results.

Based on the small-world and power-law characters of P2P, the IPS is proposed to identify the P2P super nodes. IPS adopts packets sampling to identify seed nodes. Then according to the traffic relationship between the P2P nodes, IPS identifies all the other P2P nodes originating from the seed nodes. Finally, IPS regards the nodes with large connection degree as super nodes and outputs them. The validity of proposed method is verified by the experiments using Internet traces.

Logic gates and QCA wires can be implemented by Quantum-dot Cellular Automata (QCA). In this paper, one bit, four bit and eight bit comparators are designed based on QCA. QCADesigner is used to simulate the circuits. The results show that the proposed comparators are of correct logic function. Analysis shows that the latency of proposed circuits does not increase linearly with bit size. Hence the proposed circuit has good delay property.

This paper presents a novel PLL self-calibration scheme based on Frequency-to-Voltage (F2V) Converting technique, which is fast and applicable for the Phase-Locked Loop(PLL) using a multi-band ring Voltage Controlled Oscillator (VCO) in the clock generation module of a FPGA device. Designs of key modules in the self-calibration circuit are detailed, and simulation of the full system is performed. Simulation results indicate that the system can self-calibrate quickly and properly in case of process variation or reference frequency switch. The clock generator using the proposed self-calibration circuit can obtain a wide frequency operating range while maintaining a relatively low VCO gain and it locks fast, as make it suitable for FPGA clock generation.