To evaluate the effectiveness of moving network defense, this paper presents the host security state deduce graph construction algorithm in moving network defense environment. The host security state transition model is constructed, the quantitative effectiveness evaluation method is proposed for moving network defense based on host state transition probability, and a useful reference is provided for the design of moving network defense policy. Finally, feasibility and effectiveness of the proposed model and method are illustrated and verified in a representative network example.

This study proposes a new node attack strategy of complex networks by analyzing the disadvantages of traditional strategies. The idea of the new strategy is to treat the construction problem of node attack sequence as an optimal problem rather than an evaluation problem. To achieve this strategy, the study designs a survivability index of complex networks to measure the attack effect created by a node attack sequence, then establishes a construction model of node attack sequence with the goal to maximize attack effect, and further brings forward an algorithm based on tabu search to solve the model. Experiment results from real networks and simulated networks show that the new strategy is more effective than others. 

The bot must obtain the Command and Control (C&C) information covertly and securely, which is a necessary precondition to ensure botnet work correctly and normally. For the problem that how to covertly get and share C&C information between the same type bots in local network, a C&C Information Sharing scheme based on Link-Local Multicast Name Resolution (LLMNR) protocol and Evidential (CCISLE) theory is proposed. Firstly, for measuring bot performance, two metrics are defined: running time ratio and CPU utilization rate. Secondly, the same type bots will inform their own two metrics to each other via LLMNR query packets and utilize D-S evidential theory to vote BTL (Bot Temporary Leader). Then only BTL can be proved to communicate with C&C servers and C&C information can be obtained. Lastly, BTL will share the C&C information with other bots through LLMNR query packets. The experimental results show that CCISLE can help the same type bots achieve sharing C&C information successfully. The voting algorithm based on D-S evidential theory is able to elect BTL effectively with two proposed metrics and still present better robustness when in heavy network traffic. Moreover, the traffic produced during BTL voting process also has good covertness.

Current scheduling schemes in multi-relay wireless network mainly focuse on single source wireless network with the same link status. Furthermore, the sequential-forward scheduling scheme is used usually, and the transmission efficiency is comparatively low. To solve this problem, a priority scheduling scheme based on random linear network coding is proposed. In different transmission stages, the feedback information is generated according to the packets accepting state or the linear relation among the encoding vectors. The number of the effective packets of the corresponding relay node is calculated. In the condition of different link status, the effective information of each relay node and the link transmission reliability is taken into consideration comprehensively to generate the priority index and complete scheduling. This scheme can realize cooperation transmission in multi-relays for multi-sources information. When the link status difference is obvious, the optimal forwarding node and the path can be adaptively chosen to improve the information transmission efficiency. According to the simulation results, this scheme can effectively improve network throughput and reduce the number of retransmission compared with the traditional scheduling schemes for single source wireless network.

Distributed Compressed Sensing (DCS) is an effective means to reduce the amount of data transmission and energy consumption in Wireless Sensor Network (WSN). Hierarchical Distributed Compressed Sensing (HDCS) is proposed for clustering WSN. It eliminates the temporal-spatial redundancies among data collected by the cluster members with the intra-cluster DCS, and eliminates the spatial redundancies among clusters with the inter-cluster DCS. According to the signal’s structured sparsity, a block-sparse intra-cluster joint sparsity model and a block-sparse inter-cluster joint sparsity model are constructed. Then, a hierarchical measurement scheme and a hierarchical joint reconstruction scheme are proposed for HDCS. Experimental results show that compared to general DCS, HDCS can relieve the transmission burden in the network effectively, without lowering the quality of the reconstructed signal. Moreover, it can reduce the signal reconstruction time at the Sink observably.

Software Defined Networking (SDN) and Network Function Virtualization (NFV) promote network innovation. NFV realizes logic centralized deployment of Virtualized Network Function (VNF). This paper proposes a kind of node-splitting VNF deployment model for problem of pooling deployment of VNF in virtualized Evolved Packet Core (vEPC) network. Based on the acknowledgement of virtual request traffic-aware, the model uses node-splitting algorithm to realize the dynamic adjustment of the mapping relation between VNF and physical network slices and organize the same VNFs across different domains as one pool. Compared with the traditional joint mapping algorithm of multi-function chain, the method can realize fine-grained management and overall scheduling of node resources, optimize network view, and reduce resource fragments. It is proven by network topology instance provided by SNDlib that the model can reduce resource overhead of virtual network and improve the ratio of acceptance of virtual network requests.

Traditionally, the cooperative communications usually uses Decode-and-Forward (DF) strategy. However, there is easily error propagation phenomenon by the strategy, when the quality of the communication link between source and relay is poor. To solve the problem, a novel Raptor coded cooperation scheme, which can be used in the Coded Cooperation (CC) strategy, is proposed to achieve rather high coding gains and full diversity gains in high Signal-to-Noise Ratio (SNR) regime. In this scheme, different Raptor codes are employed at the source and relay nodes, so the codeword at each node is independent and unequal. Meanwhile, the codeword at relay node is the parity check section of the codeword at the source node. Therefore, after receiving the data transmitted from different independent links, the destination node tries to decode them jointly by the intrinsic relationship among them, to obtain additionally spatial diversity gains in transmission. In addition, in order to reduce the complexity of Raptor encoding and decoding, the Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) codes are constructed by integer sequence and employed as the pre-coding. Simulations indicate that the proposed Raptor CC scheme achieves 2 dB and 1 dB performance gains compared with those of the traditional DF based one and a scheme with the combination of a Raptor code and a Distributed Space-Time Block Code (DSTBC), respectively, at Bit Error Rate (BER) of 10^-4 . Moreover, the performance improves about 2 dB and 7 dB at the outage of 10^-2 , when compared with those of the CC strategy and DF strategy, respectively.

Inspired by biologic immune system, a novel frame synchronization word identification algorithm based on artificial immune is proposed. Firstly, due to the calculation of ODN concentration of known protocol type file set, ODN library of synchronization word in corresponding protocol is constructed. Then, through uniform continuity matching between ODN library of synchronization word and relevant file set, the detecting synchronization word gene library is constructed. At last, through calculating similarity value and uniform continuity matching by using ODN library of synchronization word and detecting gene library, synchronization word can be identified exactly. The new method, which has higher accurate recognition than pattern matching algorithm suggested by simulation results, has significant potential in engineering application.

For the characteristics of amplitude and phase-modulated signals in non-cooperative burst communication like less known information, less data, and low signal to noise ratio, Modified Constant Modulus  Algorithm (MCMA) is concentrated on and a blind equalization algorithm is designed based on soft constellation information. The proposed algorithm could achieve a quick blind equalization while just using the statistics of the samples of the receiver and adopting the ideology of cyclic iteration. The scheme has a lower complexity, better flexibility while disregarding the modulation type, which made it a good choice for non-cooperative condition. The simulation indicates that the new algorithm has a superior on existing algorithms in converging speed, equalization result, and durability while keeping the performance on defensing noise, frequency offset and phase offset, and can be applied into engineering practice.

A new quadratic polynomial chaotic system is given and homogenized based on its probability density function. Then, based on the chaotic systems before and after homogenization, an S-box generation algorithm is constructed. By numerical simulation, the algorithm dynamically generates 300 S-boxes and then analyses their Differential Probability (DP) and Linear Probability (LP). The statistical results show that the uniform chaotic system can produce better performance of S-boxes.

Traditional static spectrum allocation can not adapt to the future development of wireless communication services, leading to limited profits for operators and poor Quality of Service (QoS) for users. To solve the problem, this paper proposes a three-layer spectrum sharing model including operators, users, and a spectrum leasing platform, where A operators place their excess spectrum in the leasing platform for B operators to lease. This paper considers a situation where multiple operators cooperate to share portions of spectrum but compete to serve users, then the optimal spectrum leasing strategy is studied. The goal of this paper is to find the optimal leasing strategy for both A and B operators to maximize their profits while guaranteeing the QoS for users. Numerical results show that the proposed strategy not only improves the efficiency of spectrum utilization effectively but also shows a big advantage in increasing operators’ profits.

The performance of UWB indoor positioning system is mainly affected by NLOS errors. In this paper, a channel state detection method based on channel statistics is proposed. The probability distribution function of Root Mean Square Delay Spread (RMS) and Mean Excess Delay (MED) under IEEE802.15.4a standard is modeled as standard distribution. Channel state is identified by Likelihood Ratio Test (LRT) based on KL divergence between channel instantaneous distribution and standard distribution. A localization algorithm named LRT-Chan based on LRT is proposed to improve positioning accuracy by effectively utilizing data contaminated by NLOS. Simulation results show that, LRT detection can obtain high accuracy in all UWB channels; when Anchor Nodes (ANs) with NLOS errors are not in ideal distribution, LRT-Chan algorithm can gain higher positioning accuracy.

In order to improve the spectrum efficiency in the Femtocell home Base Station (FBS) heterogeneous network, FBS and Macrocell Base Station (MBS) are usually deployed with the same frequency. However, the same frequency deployment will inevitably lead to larger co-channel interference. In order to achieve the large-scale deployment of FBS, reducing the interference of the network with the channel is particularly important. In this paper, a sub channel allocation scheme is propsed based on Q-learning.  It can ensure that FBS will not bring high cross-layer interference of MBS, while it reduces the same layer interference between two FBS. The simulation of the algorithm of FBS sparse deployment and dense deployment situation are performed, respectively. Simulation results show that this algorithm reduces the same layer interference and verifies the correctness of the theory.

To deal with dynamic network topology in Mobile Ad hoc NETworks (MANETs), a reliability-enhanced multipath source routing algorithm is proposed based on accurate path stability estimation. In order to eliminate theoretical errors existing in current approaches, statistical properties of residual path lifetime are exploited by fully introducing correlation among neighboring links’ residual link lifetime. Optimized link and path stability metric is then provided to realize a multipath-enabled routing discovery procedure and a backup path-support fast routing recovery mechanism. Simulation results show that the proposed routing algorithm can achieve fast routing discovery convergence, increase network throughput, reduce data transmission delay, and lower routing overhead. Furthermore, high network reliability can be well guaranteed even under high node mobility degree.

Two typical Vehicle-To-Vehicle (V2V) propagation channel models are proposed for the first time. One is that the channel is composed by Single-Bounce Transmit (SBT) and Single-Bounce Receive (SBR)components. The other is that the channel is composed by Double-Bounce (DB) components. Based on the two models, another model consisting of SBT, SBR, DB, and LOS components is proposed. It is assumed that the local scatterers move with random velocities in random directions and the velocity distributions of the moving scatterers with low and high speed are assumed to follow exponential and Gaussian Mixture (GM) distributions, respectively. The complex channel gains of the proposed V2V channel models are proposed, and the corresponding AutoCorrelation Function (ACF) and Doppler Power Spectral Density (PSD) are derived. The theoretical results are also compared with the available PSDs by measurements and good agreements are found between them.

The full-duplex transmission is one of the key technologies in the 5 G communication systems, due to the ability of improving spectrum efficiency. However, the performance of the full-duplex system, with the zero intermediate frequency structure, is badly impacted by the Residual Self-Interference (RSI) and In-phase/ Quadrature (I/Q) imbalance. In this paper, the OFDM full-duplex bidirectional relaying system under the RSI and I/Q Imbalance (IQI) is investigated, in a cooperative scenario where the Decode-and-Forward (DF) protocol is considered. The outage performance of the system and its closed-form expressions are derived under Rayleigh fading channels, and the influences of the IQI and RSI on system performances are analyzed, respectively. The simulation results verify the analysis, and the conclusions are given as follows. First, the outage performance improves as decreasing of the IQI and RSI. Second, the optimal improvement of outage performance is achieved by reducing the RSI and I/Q imbalance, according the route with the steepest descent method. Third, the best way for enhancing the outage performance is chosen, by the relative position between the steepest descent route and the current coordinate of IQI-RSI.

Due to the absorption and scattering when light is traveling in water, there are two major problems of underwater imaging: color distortion and low contrast. Traditional enhancement and restoration methods can not handle these problems very well, so, this paper proposes a new approach based on the underwater optical imaging model and a Retinex-based enhancing approach. Firstly, a simple color correction method based on statistical method is adopted to address the color distortion. Then the adaptive Wiener filter is used to optimize the initial transmission map with the boundary constraints. In order to make the result more naturalness, a weighted L₁ regularization model is proposed to enhance the luminance layer. Finally, an adaptive Gamma correction operation is adopted for post-processing. Experimental results demonstrate the effectiveness of the proposed method in restoring the original color of the scene and enhancing image contrast and the visibility.

Interacting Multiple Model Bernoulli Particle Filter (IMMBPF) is suitable for maneuvering target tracking under cluttered environment. However, when model information is introduced into particle sampling process in IMMBPF, it will lead to the number decline of particles which are applied to approaching the real state and model, and the computation load is heavy because of the interacting stage of particles in the recursion. An enhanced Multiple Model Bernoulli Particle Filter (MMBPF) is proposed to improve the effectiveness of single particle to approximate the real target state and model. The number of particles of each model is given in advance, and the posterior probability of each model is updated with the associate likelihood function, which avoids particle degeneracy without distorting the Markov property. Simulation results show that the proposed MMBPF achieves better tracking performance with fewer particles than IMMBPF.

Focus on the problem that Compressive Sensing (CS) measurement can not measure the electrical energy of pseudo random dynamic test signal accurately, in this paper, the spectral sparseness of pseudo random dynamic test signal is firstly analyzed, and dynamic test signal satisfies the measurement condition of compressive sensing is proved. Secondly, the system stable state optimization method is used to establish the deterministic compressive sensing measurement matrix, which meets the RIP (Restricted Isometry Property) condition. Finally, a new compressive sensing measurement methed for the electrical energy of pseudo random dynamic electric energy is proposed. The experimental result shows that the theoretical error of the compressive sensing measurement is superior over traditional sample power electrical energy measurement, and it can measure the pseudo random dynamic electrical energy accurately.

In inertial based self-contained pedestrian positioning systems, because the drifts of the gyroscopes grow with time, it relies on the earth magnetic field to suppress the heading errors. However, the earth magnetic field suffers from severe interference in indoor scenarios, and the magnetometer itself has measurement errors, the above reasons have dramatically limited the performance of the magnetometer-aided heading error calibration. This paper proposes a magnetic-aided heading error calibration approach. Firstly, the magnetometer is calibrated according to the motion model of the pedestrian and the calibration coefficients obtained are used to improve the accuracy of heading derived by the magnetometer. On this basis, a proved Quasi-Static magnetic Field (QSF) detection approach is proposed to extract the usable magnetic information fed into Zero velocity UPdaTe (ZUPT)- aided Extended Kalman Filter (EKF) algorithm to conduct the heading calibration. The experiment results show that the 684 meter long walk only has a position error of less than 0.5 meter and heading error of 3.2 degrees, and the position error is less than 0.2% of the total walking distance. The results indicate that the performance of the proposed method is superior to the existing approach.

The one delay tap cancellation system is weakly to suppress the co-site interference between the Very High Frequency (VHF) radios in multipath channel. To overcome this obstacle, a Radio Frequency (RF) interference cancellation scheme based on the multi-tap delay and orthogonal combination is presented, as well as a new solving attenuation coefficients method. Considering the fixed delay scale and the number of taps, this method accurately estimates the reference signal autocorrelation matrix and the cross-correlation vector between reference signals and received signal on the basis of instantaneous and iterative weighted averaging. The attenuation coefficients are achieved by solving Wiener-Hopf equation via the estimated autocorrelation matrix and cross-correlation vector. Compared with the existing approaches, this method does not need to adjust and control the amplitudes as well as the phases of reference signals simultaneously, and it improves the accuracy of estimating cross-correlation vector and autocorrelation matrix. In addition, the closed-form expression of self-interference cancellation ratio is derived through theoretically analyzing the attenuation coefficients solution. The analysis and simulation results show that the proposed method could obtain self-interference cancellation ratio of more than 90 dB, which is about 9 dB higher than the existing method. This study is significant for eliminating RF self-interference in multipath channel.

To improve the interference and noise suppression ability of Phase-Only Beamforming (POB) and the real-time performance to obtain the optimal weight of the uon-convex POB, a phase-only Minimum Variance Distortion-less Response Beamformer (MVDRB) via the Iterative Majorization Minimization (IMM) algorithm is designed. The distortion-less response constraint is transformed into maximizing array response in the desired direction. The upper bound function of the objective function in quadratic form is derived which generates the IMM-POB model. The optimal weight in closed-form for each iteration is further deduced. Simulation analysis illustrates that the proposed IMM-POB can obtain better signal to interference and noise ratio improvement compared with the existing iterative POB algorithms and the optimal MVDRB; its interference suppression ability approximates the optimal MVDRB with better noise suppression ability; it is much less sensitive to the number of array taps compared with the optimal MVDRB; it has strong real-time performance and can be applied to large-scale array.

A Cross Covariance Matrix (CCM) based Two Dimensional (2D) Direction Of Arrival (DOA) estimation algorithm for parallel nested array is proposed. A long virtual array can be achieved based on the CCM between the two parallel nested arrays, and 2D DOA estimation can be transformed to a 1D DOA estimation problem. Thereafter, virtual snapshots are increased by exploiting the Vandermonde structure of direction matrix, and the aperture loss is minimized when constructing covariance matrix from the virtual array. Finally, the proposed algorithm employs unitary Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) and Total Least Squares (TLS) to reduce further the influence of noise and achieve automatically paired 2D DOA estimation. Compared to DOA estimation algorithms using conventional parallel array, the proposed algorithm can achieve better DOA estimation performance, identify more signals and is more robust to spatial color noise. The simulation results verify the effectiveness of the proposed algorithm.

There is a large deviation between the actual position of the missile and inertial guidance position in the final guidance stage due to the inertial navigation error, which influences seeker,s accurate on positioning to the target, so it can not meet the application needs of precision strike. Due to the special imaging geometry of the missile borne Synthetic Aperture Radar (SAR) in the descending section, the squint angle plane of the target point is different from the imaging plane, so the traditional positioning method based on Doppler angle measurement is no longer applicable. This paper uses image matching to obtain high precision ground point relative position information and the high precision slant range information between radar and target point. By constructing a Euler tetrahedral geometry model, using the scene digital elevation as a priori information to screen the reference point, the actual position of the missile in the established North-sky-East coordinate system with an origin of the target point is calculated. Then it can provide accurate information for the missile maintenance. Simulation results show that this method can meet the requirements of target positioning on missile terminal guidance stage well.

A parallel higher-order and out-of-core based Domain Decomposition Method (DDM) is proposed for analyzing the disturbed characteristics of large airborne phased radar antenna array. When the phase of main beam sweeps for the airborne phased radar antenna array, the problem is divided into two parts: radar antenna array and airborne platform. The platform which remains unchanged during the overall solution is simulated only once at the beginning, and then the relative data, such as impedance matrixes are written into hard disk using out-of-core technique. When the phase sweeps, only the phased antenna array part is concerned. Finally, the accurate results are obtained by iterative solution. This method largely reduces the CPU time and storage requirements. The numerical example demonstrates that the proposed method is very suitable for analyzing the layout of large airborne phased radar antenna array.

Excitation optimization algorithm based on Genetic Algorithm (GA) is mainly used to solve the excitation problems of array antenna beam shaping. When optimizing the excitation of array antenna by traditional genetic algorithm, the beam of array antenna is synthesized by radiation shape of elements in antenna array, and then the results will be compared with the target pattern. After several operations, the excitation will meet the deign requirements. However, in traditional genetic algorithm, neglected suppression of side lobe leads to an unsatisfactory high level side lobe. In this paper, a new method of beam synthesizing by peak beam of array antenna is proposed. By comparing the shape of synthesized beam with target beam and combining with traditional GA, the synthesized beam matching the target beam with low side lobe will be obtained. Taking a 16 elements X band micro-trip dipole linear array antenna as an example, the results of simulation show that array antenna has high level side lobe suppression at about -27.5 dBc using the method proposed in this paper, which is much better than -19 dBc side lobe suppression using traditional GA.

A novel single layer microstrip reflectarray element with multi-resonance structure is presented. The element is composed of six dipoles which are placed in parallel at a certain distance. The element has good linear polarization properties. Ansoft HFSS is used to optimize the parameters and linear reflection phase curves in two bands are achieved. A dual-band dual-polarization reflectarray composed of the elements is designed, fabricated and measured. The proposed reflectarray operates in two frequency bands within X band centered at 10 GHz and Ku band centered at 13.58 GHz. The reflectarray is offset fed by only one horn antenna for both bands in two orthogonal polarizations. Measured results show good radiation performance in both bands. A well coincide is obtained between the simulated and measured results, which demonstrate the desirable dual-band dual-polarization radiation performance of the reflectarray. The design is valuable to other reflectarray in achieving dual-band dual-polarization performance.

A Consensus-based Distributed Spherical Simplex Radial Cubature Information Filter (CD-SSRCIF) is proposed to improve the real time orbit determination accuracy and fault tolerance of multiple handheld terminals. N-simplex vertices and the moment matching method are used respectively to calculate the spherical and radial integral, and a five order spherical simplex radial rule suitable for system state dimension n≤7 is obtained. Statistical linear error propagation method is used to embed the above rule into Extended Information Filter (EIF) to achieve centralized five order cubature information filter. Then, average consistency algorithm is used to obtain the distributed equivalent expression of multi-source information accumulation in centralized filter, and constitute cascade filter. The lower filter performs an average consistency algorithm to fuse information from neighbor nodes, and output virtual measurement value. The upper filter performs five order cubature information filter with the above measurement value to output orbit state estimation in real time. The simulation results show that the five order CD-SSRCIF algorithm does not need information fusion center, and has a higher orbit determination accuracy than the three order algorithm.

Multipath is the dominant error source for high-accuracy positioning systems. It is significant for eliminating the multipath error and improving the positioning accuracy to estimate multipath parameters. There are two main disadvantages for multipath parameters estimation by using the Extended Kalman Filter (EKF): it is sensitive to the initial value; filtering results fluctuate obviously around actual values. To solve these problems, an improved multipath estimation algorithm based on Particle Filter (PF) and sliding average EKF is proposed. Firstly, PF is used to obtain rough estimation values of multipath parameters, which are set as initial estimations for EKF to reduce the initial value sensitivity. Then, the EKF filtering results are smoothed by sliding average. The smoothing results are outputted as the multipath estimation. The simulation results show that the estimation results of the proposed algorithm have smaller fluctuation magnitude compared with EKF, and it is insensitive to the initial estimation. 

For multi-constrained polarity optimization of large-scale FPRM circuits, a Multi-Objective Discrete Particle Swarm Optimization (MODPSO) algorithm is proposed. Firstly, the multi-objective decision model is established according to the delay-area trade-off of large-scale FPRM circuits. Secondly, combined with tabular technique and MODPSO, the best polarities of delay and area are searched for large-scale FPRM circuits, to obtain the Pareto optimal set for delay and area. Finally, the algorithm MODPSO is compared with the algorithm DPSO and NSGA-II on MCNC Benchmarks with PLA format, and the results verify the effectiveness of the MODPSO.

It is of great importance to control the electromagnetic spectrum and optimize the use of spectrum resource because electromagnetic interferences between different devices may cause vicious influence while combating in formation. Traditional random algorithms for the optimization of spectrum use suffer from painfully slow optimization speed. In this paper, a model of ElectroMagnetic Compatibility (EMC) network in the case of formation is developed based on the complex network theory. By maximizing the network performance in terms of both benefit and cost, this paper proposes a rule optimization algorithm of EMC network considering node importance. Both theory analysis and simulation results show that optimization speed is increased by 13.35% and the optimization performance is enhanced. The proposed algorithm not only accelerates the optimization for the use of spectrum resource but also provides a theoretical reference for practical applications.

It is found by the experiment that the ghost mode oscillation appears in an output window when the centric axes of two section rectangular waveguides and a cylindrical waveguide in the middle are not on the same line. The ghost mode oscillation may result in sparkling and even cracking of the window. In this paper, a method for suppressing the ghost mode oscillation in S band broadband klystron is discussed through the simulation, analysis and experiment for improving the configuration of the cylindrical waveguide in the output window with little effect on the voltage standing wave coefficient in the operating frequency band.

The cylindrical two-dimensional wind sensor employing flow meters is not accurate enough for surface wind measurement. By analyzing the data from wind tunnel experiments, a model is proposed to describe the diametrical pressure differences developed by the flow around a circular cylinder. A method is derived from the model for two-dimensional wind measurement by detecting the diametrical pressure differences. When the proposed method is applied to the data from wind tunnel tests in range of 2~40 m/s, the relative wind speed errors and the wind direction errors are no more than ±(0.2+0.03 V) m/s and ±5° respectively. The proposed method is more accurate than the cylindrical two-dimensional wind sensor using flow meters. Without moving parts, the method is immune to mechanical wear and inertia.

Due to the large transaction number and tiny value in micropayment, it is not practical to authenticate each transaction. Micali et al. (2002) propose a lottery-based micropayment to integrate multiple micropayment to one macro-payment that is worth using complicated authentication. Liu-Yan scheme (2013) guarantees the result is verifiable by involving all participants’ data. However, there still exists a flaw that the malicious bank maybe obtain the illegal benefit by controlling the specific purchaser not be selected to execute the macro-payment, moreover, this attack can not be detected. In this paper, the flaw is firstly described, then, an improved version is proposed. Specifically the model “multiple purchasers to 1 merchant”in Liu-Yan’s scheme is replaced with a new model “1 purchaser to 1 merchant”, which guarantees the fairness and verifiability for all using the commitment technique.

For blind estimation of Pseudo-random Noise (PN) codes in Non-Periodic Long and Short Codes Direct Sequence Spread Spectrum (NPLSC-DSSS) signals, the Triple Correlation Function (TCF) common peak theory of m-sequence and probability function of NPLSC-DSSS signals’ TCF estimate are given firstly. Then sequences of TCF peaks are built with their conjugate sets’ features, binary hypothesis test model and accurate detection algorithm of TCF common peaks using goodness of fit test are proposed. Meanwhile, many false peaks are eliminated to improve the estimation performance using the property of forward and backward TCF peaks and cumulative-sum’s increasing trend of TCF peaks in conjugate sets. Lastly, the primitive polynomials of long and short pseudo-random codes can be estimated with the matrix’s oblique elementary method. Simulations show that the proposed method can effectively estimate the PN codes of NPLSC-DSSS signal at low Signal-to-Noise Ratio (SNR).

In coding theory, the (minimum) distance of a code is a very important invariant, which always determines the error-correcting capability of the code. Let R be an arbitrary commutative finite chain ring, a is a generator of the unique maximal ideal and R* is the multiplicative group of units of R. In this paper, for any w∈R*, by using the generator polynomials of (1+aw)-constacyclic codes of any length over R, higher torsion codes of such codes are calculated. The Hamming distance of all (1+aw)-constacyclic codes of any length over R is determined and the exact homogeneous distance of some such codes is obtained. The result provides a theoretical basis for encoding and decoding for such constacyclic codes.

This paper proposes a hybrid electromagnetic field inverse scattering imaging method based on the advantages of the qualitative and quantitative imaging methods，and it is applied to rebuilding the space distribution information of electric parameters for multi objects. First, the prior knowledge of the Region Of Interesting (ROI) of target, object shape and target number is reconstructed by using Direct Sampling Method (DSM). Then, the geometry information of the objects and the space iteratively corrected distribution information of electric parameters is reconstructed by  Subspace-based Optimization quantitative Method(SOM). The experimental result for the scattering field data of Fresnel laboratory shows that the imaging accuracy of this method is comparable to SOM. More over, the proposed technique greatly reduces the computational complexity and improves the convergence speed.