In this paper, two recursion formulae of chromatic polynomial of a maximal planar graph $G$ are obtained: when $\delta(G)=4$, let $W_4^\nu$ be a 4-wheel of $G$ with wheel-center $\nu$ and wheel-cycle $\nu_1\nu_2\nu_3\nu_4\nu_1$, then $f(G,4)=f((G,4)\circ{\nu_1,\nu_3},4)+ f((G,4)\circ{\nu_2,\nu_4},4)$; when $\delta(G)=5$, let $W_5^\nu$ a 5-wheel of $G$ with wheel-center $\nu$ and wheel-cycle $\nu_1\nu_2\nu_3\nu_4\nu_5\nu_1$, then $f(G,4)=[f(G_1,4)-f(G_1\cup{\nu_1\nu_4,\nu_1\nu_3},4)] +[f(G_2,4)-f(G_2\cup {\nu_3\nu_1,\nu_3\nu_5},4)]+ [f(G_3,4)-f(G_3\cup {\nu_1\nu_4},4)]$, $G_1=(G-\nu)\circ{\nu_2,\nu_5}$, $G_2=(G-\nu)\circ{\nu_2,\nu_4}$, $G_3=(G-\nu)\circ{\nu_3,\nu_5}$, where $“\circ”$ denotes the operation of vertex contraction. Moreover, the application of the above formulae to the proof of Four-Color Conjecture is investigated. By using these formulae, the proof of Four-Color Conjecture boils down to the study on a special class of graphs, viz., 4-chromatic-funnel pseudo uniquely-4-colorable maximal planar graphs.

The end-to-end bandwidth, the Round Trip Time (RTT) and the packet loss rate vary over many orders of magnitude in Internet, which cause significant performance degradation of Transmission Control Protocol (TCP). To cope with this, a path-adaptive TCP congestion control protocol, called INVerse Sigmoid (INVS), is proposed. INVS employs an exponential function based convex growth function of congestion window to improve the path utilization. An adaptive increase factor in the growth function is introduced to match the window growth rate with the path condition. An adaptive queue-threshold in the loss distinguishing scheme is used to enhance the performance of TCP over wireless links. The performance analysis and evaluation show that INVS improves the throughput, the fairness, the total link utilization and the RTT-fairness of TCP congestion control algorithm.

To solve the limited storage resource and the data storage reliability problem of Space Information Network (SIN), a novel Distributed Storage Strategy based on Luby Transform (LT) codes (DSSLT) is proposed. According to the proposed strategy, source data packets are transmitted quickly to every node in the network based on directional random walk. The ID-based estimation method is used to estimate the global information at the information estimation phase, the values are obtained without excessive random walks. The procedure of XORing packets is reasonable so that the distribution of code degree tends to the desired degree distribution. As presented by the analyses and simulations, random walk steps are greatly reduced compared with a representative distributed storage strategy, while improving the decoding performance.

Influence maximization is an optimization issue of finding a subset of nodes under a given diffusion model, which can maximize the spread of influence. This optimization issue has been proved to be NP-hard. Leveraging the fact that vertices in minimum vertex covering and feedback vertex set are of great importance for the connectivity of a graph, a heuristic algorithm for influence maximization based on Minimum Vertex Covering and Feedback Vertex Set (MVCFVS). Extensive experiments on various diffusion models against state of the art algorithms are carried out. Specifically, the proposed algorithm performs excellent on Independent Cascade Model (ICM) and Weighted Cascade Model (WCM), which exhibits its great advantages in terms of influence range and convergent speed.

Existing trust models can not effectively express the uncertainty of trust relationship and deal with such issues as dishonest feedbacks and strategic frauds from malicious entities in the distributed network, an adaptive trust model based on aggregating Intuitionistic Fuzzy Information (IFI) is proposed. Firstly, in order to incentivize entities providing trustworthy service and punish entities taking along malicious behavior, an approach on aggregating IFI is constructed to compute the direct trust intuitionistic fuzzy numbers which contain the latest permanence factor and the time decay factor. Then, the recommendation credibility and uniformity are defined to detect dishonest recommendation. Subsequent, an adaptive weighted approach is developed to avoid distributing the weights of direct and indirect trust subjectively. The simulation experiments demonstrate that the proposed model not only is robust on malicious attacks, but also has better adaptability and effectiveness. 

Uncertain factors are a common phenomenon in the real world; therefore, it is very meaningful to study on the trusted neighbor query under uncertain network conditions. This paper puts forwards a new solution. The uncertain network is modeled as uncertain weighed graph, and these definitions of the uncertain graph are given, such as sample graph, sample graph index, base network, length of feasible path and expected length of feasible path. Based on these the high-efficiency credible neighbor query algorithm for uncertain graph is put forward under constraint conditions. This algorithm is transforms the issue of neighbor query in the uncertain network equivalently to the issue of neighbor query in the base network. The theoretic analysis and experimental results show that the credible neighbor query algorithm proposed in the paper can solve the neighbor query problem in the environment of the uncertain network from non-deterministic perspective.

MIBS is a light weight block cipher for constrained resources environments such as RFID tags and sensor networks. This paper investigates the construction of zero-correlation linear approximations of 8-round MIBS and presents an attack on 13-round MIBS-80 by means of zero-correlation linear cryptanalysis with the properties of key schedule and partial-sum technique, which needs 2^62.1 known plaintexts and 2^74.9 encryptions. Furthermore, an 8-round integral distinguisher is deduced from the zero-correlation linear approximations using the relations between them, and as an application, integral attack on 11-round MIBS-80 is conducted with 2⁶⁰ chosen plaintexts and 2^59.8 encryptions.

This paper builds a performance model of multicore processor, which applies to the crypto algorithms, and some advisable suggestions and academic supports are given for its design. By introducing parallelism degree, transformation overhead and synchronization time, performance model of multicore crypto processor is built based on the Amdahl’s law and its extension, and accordingly the design space of multicore crypto processors is searched. Simulation analysis shows that the key factors influencing the performance model of multicore crypto processor are the exploitable parallelism of crypto application, the proportion of parallel part and the communication times in the process of operation.

In view of the small hiding capacity, low concealment and poor robustness of the audio carrier, a novel audio information hiding algorithm is proposed based on wavelet transform. The algorithm regulates the high-frequency wavelet coefficients in every audio segment, and then changes the energy values of the former and the latter part in each audio to hide confidential information according to the characteristic that human auditory system is not sensitive to small changes in high frequency information of audio. First, the influence of embedded depth, hidden frequency-band and segment length of carrier audio on voice quality and bit error rate is tested to choose the best parameters, then algorithm is verified for the feasibility and robustness by several kinds of common attacking means. Experimental rdsults show that the proposed algorithm, which does not require the original audio signal in the watermark extraction, not only has good concealment and large hiding capacity, but also has strong robustness for resisting the common attacking behaviors, such as noise, low-pass filter, re-sampling, re-quantitative and echo interference. In additional, the audio segment is shorter, the hiding capacity is larger.

In this paper, a green communication scheme based on physical layer security is addressed considering the energy and secrecy constraints. This scheme maximizes the secure Energy Efficiency (EE) of the network by power allocation subject to the maximum power constraint of each node and the target secrecy rate constraint of the network. Furthermore, an iterative algorithm for power allocation is developed based on fractional programming, dual decomposition, and Difference of Convex functions (DC) programming. It is verified by simulations that the proposed algorithm can lead to a significant gain of secure EE yet with some loss of secrecy rate compared with secrecy rate maximization. This is because that there is an inherent tradeoff between EE and secrecy. However, the achievable secrecy rate of the proposed scheme is still superior over that of total transmission power minimization.

This paper presents the 13-round impossible differential cryptanalysis on MIBS-80 for the first time. Firstly, this paper filters the plaintexts based on the impossible differentia of S-box in MIBS-80. Secondly, by taking advantage of the restrict relation between key in the first round and in the second round, the restrict relation between key in the first round and in the 13th round, the number of plaintexts is further reduced. To sum up, 2^18.2  times can be eliminated as big as the number of plaintexts eliminated in former impossible attacks, therefore both the time complexity and memory complexity are saved. Besides, by looking up various tables to get the needed key bits in the attack, the time complexity and memory complexity are thereafter reduced. Finally, 80 independent key bit are used to recover the main key, which ensures that only the right key is kept. The presented attack needs 2^60.1 chosen plaintexts, 2^69.5 13-round encryptions and 2^71.2 64 bit blocks, which is the best result of impossible differential attack on MIBS so far.

The Base Station (BS) selection for distributed massive MIMO system is studied. The channels between the BSs and the users are assumed to be Rician fading. First the closed-form expressions of downlink achievable rates for Matched-Filter (MF) and Zero-Forcing (ZF) precoding are derived respectively, and the power efficiency performance of the system is investigated. Based on the closed-form expressions, the approximate incremental BS selection and the approximate user priority BS selection algorithms are proposed, both of which only require the statistical Channel State Information (CSI), to maximize the system spectral efficiency. Numerical results show that the proposed algorithms perform close to the optimal one. Specifically, it is shown that the approximate user priority BS selection algorithm outperforms the approximate incremental one when the BSs utilize the MF precoding in the large scale antenna limit.

A new modulation recognition algorithm of digital communication signals based on the multi-fractal dimension characteristics is proposed. Employing preprocessing the received signal, the generalized dimension and the multi-fractal spectrum can be calculated by 2D data array. The effect of multi-fractal spectrum due to the weighted factors q is discussed in detail, the 13 multi-fractal characteristic parameters are extracted. The Support Vector Machine (SVM) classifier based on the multi-fractal dimension characteristics is designed for recognition of different modulation signals. Simulation results show that the proposed method has a good recognition performance under low SNR.

Directional Modulation (DM) technique is a hot research area for physical layer security communication in recent years. The baseband modulation signal is synthesized at the antenna level for transmitting different signal constellations at different directions. The genetic algorithm and vector method are the main synthesis algorithms for DM signal. However, these algorithms have some limitations for different communication models because of different research targets of these papers. In this paper, a DM signal synthesis algorithm based on phase beam-forming technique is proposed from the point view of that receive signal constellation of DM signal is scrambled at the undesired directions. First the phase beam function is set up for different communication models. Then the weighted values for array elements are obtained by the spatial Fourier transformation of the radiation pattern. Simulation results show that the proposed DM signal synthesis algorithm provides technological support for different communication models such as single user channel with pencil phase beam, broadcast channel with fanned phase beam and multi-access channel with orthogonal phase beam.

Physical-layer Network Coding (PNC) with Continuous Phase Modulation (CPM) attractes much attention due to its high efficiency in the throughput and the spectrum. Most present research on the detection of CPM-PNC signals is based on the assumption that signals transmitted from the two nodes arrivd at the relay haue perfect carrier synchronization or the carrier-phase offset is known. In practical applications, however, the carrier-phase offset is unavoidable and hard to estimate accurately. In this paper, a noncoherent multiple symbol detection algorithm for CPM-PNC signals is proposed to solve this problem. The proposed algorithm, which is based on the maximum likelihood principle, fully exploits the inherit memory of CPM signal and makes decision on the middle symbol by observing a group of symbols. Simulation results show that the performance of the proposed CPM-PNC noncoherent multiple symbol detection algorithm is superior. In addition, as the observation length gets larger, the performance of the proposed algorithm increases significantly and approaches that of CPM-PNC optimal coherent detection. When BER is 10^-4, compared with observation length of 1 symbol, the algorithm with observation length of 5 symbols achieves 6.7 dB performance gain.

In single-carrier modulation system with frequency domain equalization, Decision Feedback Equalizer with a Hybrid time-frequency structure (H-DFE) is attractive for its performance; the complexity is also significant, especially for very dispersive channels. Iterative Block Decision Feedback Equalizer with Hard Detection (HD-IBDFE) system performance degrades caused by errors in symbol decision and it needs to calculate the correlation factor of the transmitted and hard detected data. To solve these problems, Iterative Block Decision Feedback Equalizer with Soft Detection (SD-IBDFE) is introduced to improve the system performance. The receiver feedbacks the soft information of the equalizer’s output. The iterative channel estimation is adopted in order to deal with the time-varying underwater acoustic channels. Simulation results show that SD-IBDFE is superior to HD-IBDFE obviously for underwater acoustic channel. One underwater acoustic communication system is designed and tested in the lake. At a distance of 1.8 km with complex channel condition, the useful data rate of around 3000 bps is achieved with uncoded bit error rates 10^-3 in lake experiment.

Traffic split provisioning scheme leads to extra guard band and equipment ports occupation, which decreases the spectrum utilization and increases the energy consumption for elastic optical networks. To address the problem, a spectrum-aware traffic split-merge spectrum resource allocation strategy is proposed. When a new request comes, the total link spectrum consecutiveness for each path is calculated. And the spectral block with the highest spectrum consecutiveness is selected to transmit the request. If the number of frequency slots required by the request exceeds the size of any available spectral block in all paths, the demand is split into multiple sub-demands and allocates them into multiple spectral blocks with relatively higher spectrum consecutiveness. When an available spectral block which meets the requested number of frequency slots is detected on the transmission path, the sub-demands are merged. And spectrum consecutiveness is introduced in the decision criterion for the traffic merge operation. Simulation results indicate that the proposed strategy can significantly reduce the bandwidth blocking probability and save the energy consumption for the elastic optical networks.

Jamming resource distribution of cooperative identification friend or foe via secondary radar is researched by introducing Discrete Cuckoo Search (DCS) algorithm. The jamming effect evaluation rules and indexes are given, and the aim function and distribution model are given. According to the analysis, distribution models can be changed into one-to-one model and much-to-little model, which can be solved by DCS algorithm. Owing to the slow searching speed and low precision in the Levy flights later stage, the crossover and variation are introduced into DCS algorithm, which gets Improved Discrete Cuckoo Search (IDCS) algorithm. The simulation results show that the jamming effect judging index is effective, the IDCS algorithm has a faster convergence speed than the DCS algorithm, and it has a better searching optimization speed than Improved Genetic Algorithm (IGA).

In the case that the jammer platform rotates or is pointed in all different directions for radar detcting, the tolerance analysis is made between the conventional retrodirective cross-eye and the orthogonal four jamming elements. In the analysis procedure, angle factor is introduced. A new criterion called Angle Factor Specific Boundary Value (AFSBV) is proposed to evaluate the performance of the two scenarios. The closed-form solutions for the phase shift and amplitude gain are derived in the following sections. In the case of rotating jammer platform, the maximum value of angle factor specific boundary value is obtained. The results for the amplitude and phase can satisfy the case that the jammer platform rotates or is pointed in all directions for radar detecting.

According to the characteristic of navigation receiver in the missile, the anti-jamming model of high dynamic conditions is built. Taking into account the characteristic of interferences in high dynamic conditions and the shortcomings of traditional null widening methods, a novel Statistical Space Time Null Widening (SSTNW) method is proposed. The proposed method can suppress interferences effectively in high dynamic conditions and interferences position disturbed by non-ideal factors, i.e., it may improve the robustness of anti-jamming algorithm of navigation receiver in the missile remarkably. Simulation results show the feasibleness and effectiveness of the proposed method.

This paper aims at the issue of accelerating moving target parameter estimation and imaging. The SAR echo spectrum of target with acceleration is calculated, and the necessity of estimation and compensation of the three-order moving target echo phase to imaging and movement parameter estimation is analyzed. Then, a Novel algorithm is proposed to estimate range cell migration rate and range velocity by Hough transform, compensate the range cell migration by phase compensation, and estimate the three-order phase using three-order Local Polynomial Fourier Transform (LPFT). Using the parameter estimated by Hough transform, the movement parameters can be precisely estimated and image well focused without increasing the calculation significantly. Simulated data processing results are provided to demonstrate the effectiveness of the proposed algorithm.

Orthogonal Frequency Division-Linear Frequency Modulation (OFD-LFM) signal is widely used in Multiple Input Multiple Output (MIMO) radar systems. For solving the problems of the auto-correlation sidelobes of the spatial synthesized signals, an analysis is made of the inherent sidelobe property. Furthermore, OFD-LFM with various frequency steps is proposed and the waveform design method is given. The optimization model is established based on the temporal property and spatial property jointly. Then, the frequency steps and initial phases are optimized by Sequential Quadratic Programming (SQP). The transmitted power of the designed waveform is approximately equal in all directions, and the spatial synthesized signals have good correlation properties.

The matrix CFAR detector is proposed according to information geometry theory, but its constant false alarm property is not analysed, and the matrix CFAR’s detection performance still needs to be improved. Firstly, the matrix CFAR’s constant false alarm property is analysed according to the normal law on matrix manifold, on this basis an improved matrix CFAR detector is proposed with replacing the geodesic distance with KULLBACK-LEIBLER Divergence (KLD). Finally, simulation experiments verify that the improved method has better detection performance.

Bistatic forward looking low frequency Ultra Wide Band (UWB) Synthetic Aperture Radar (SAR) has both complicated imaging geometry and strong range-azimuth coupling, which increases the difficulty of high-precision imaging extremely. In order to solve this problem, this paper proposes an approach based on Fast Factorized Back Projection (FFBP) algorithm to focus the low frequency UWB Bistatic Forward-looking SAR (BFSAR) data. First, based on the imaging geometry of BFSAR, the principle and implementation of Back Projection (BP) algorithm are presented. Then, the phase error in FFBP algorithm is analyzed, and the formula of the phase error in bistatic forward looking SAR is derived. The implementation of FFBP algorithm is presented, and the computational burden of BP algorithm and FFBP algorithm are estimated and compared. Finally, the simulation experiment is progressed, and the results prove the correctness of analysis and the validity of the proposed approach.

To identify the out-of-database targets in the process of radar ground target recognition with High Resolution Range Profile (HRRP), this paper proposes an improved radar ground target identifier based on the distribution of the space of training features. In the training phase, a K-Means clustering strategy based on the pre-process of correlation coefficient is utilized to divide the space of training dataset. Then each sub-space boundary is determined by Support Vector Domain Description (SVDD) based on the distribution of the sample space. Finally, it can decide the category of target with the sub-space boundary and the weighted K-neighbors principle. This method can work without the template of out-of-database samples, which improves the effectiveness of target identification. Due to the fact that the feature space of different targets has the characteristic of non-uniform aggregation under different attitudes, a procedure of region partition is applied to training dataset. Thus computational load is relieved with a decrease in search operation of template matching. The requirement of real-time processing can be satisfied. Finally, the experiments against both simulation and real data verify its excellent performance of identification and real-time processing capability.

To resolve the conflict between the amount of image data and the channel bandwidth, a Region Of Interest (ROI) coding method based on JPEG2000 is proposed in this paper. The mainstream methods for JPEG2000 ROI coding have a difficulty in balancing ROI quality and system computation, and have a hidden trouble in losing background completely at a low bit rate. The proposed method achieves ROI coding by precisely controlling the accuracy of background coefficients in each subband. The human visual property is introduced to obtain better visual effect with limited background codestream. Also, the Very Large Scale Integration (VLSI) design of the proposed method for the rectangle ROI is proposed. This design can be suitable for the mainstream ROI methods for JPEG2000 by some necessary adjustments. Experimental results show that the proposed method obtains an excellent performance in ROI quality and visual effect of the reconstructed images, supports arbitrary ROI shape coding, and is compatible with the standard. The VLSI design only adds one clock cycle on the coding time of JPEG2000 system, has a high throughput, and satisfies real-time applications.

As a conventional unit in interferometric imager, correlator has a wide range of applications to get visibility functions. THz imager has more and more applied to security check and military scouting area. To solve the phase synchronization problem in high speed digital correlator, which is designed for THz interferometer, this paper presents a cross synchronization scheme based on low hardware cost FPGA controller. A high speed multichannel digital correlator is presented under this scheme. In this correlator, sampling rate can reach as high as 5 GHz, effective number of ADC is greater than or equal to 6 bit, integration time is adjustable. Interference fringes are presented by constructing a 0.44 THz interferometer out of this correlator and related THz microwave devices. The fringe’s linear phase error is better than 2°. The research could provide important reference value about the design of THz interferometric imager in future.

Interleaved thinned arrays sharing aperture based on the aperture ratio of reuse is an effective way to realize airborne multifunction. A new method to interleave thinned linear arrays is proposed in this paper based on the modified Iterative Fast Fourier Transform (IFFT) algorithm. The sub-arrays spectrum energy distributed is achieved evenly by making the Fourier transform to linear array antennas’ excitation, analyzing the frequency spectrum and selecting the incentive crossly to ensure the positions of the thinned sub-array antennas. On this basis, the iterative FFT algorithm is adopted to thin the linear array. The simulations show that compare with the difference sets and the genetic algorithm, this technique can ensure the first subarray under the condition of thinned optimization, at the same time, the Peak Sidelobe Level (PSL) of the second subarray is similar to the first sub-array. It means that the new method is effective to restrain the side lobe levels and useful to interleaved array optimization.

When using Back Propagation (BP) neural network to recognize the spatial target, the high dimensional input features induce the complexity of the network structure and the poor performance of the recognition. In this paper, a new recognition method based on Spectral Regression (SR) feature dimension reduction and BP neural network is proposed for the above difficulties. Firstly, the HOG features are extracted from the spatial object, and then the feature dimensions are reduced by SR. Finally, the BP classifier is used to train the data. Experimental results show that the proposed method is better than the traditional dimension reduction methods such as PCA, KPCA, LPP, KLPP in dimension reduction and recognition, which can juggle real-time and accuracy, thus improving the recognition performance.

Coordinate Descent (CD) is a promising method for large scale pattern classification issues with straightforward operation and fast convergence speed. In this paper, inspired by v-soft margin Support Vector Machine (v-SVM) for pattern classification, a new v-Soft Margin Logistic Regression Classifier (v-SMLRC) is proposed for pattern classification to enhance the generalization performance of Logistic Regression Classifier (LRC). The dual of v-SMLRC can be regarded as CDdual problem with equality constraint and then a new large scale pattern classification method called v-SMLRC-CDdual is proposed. The proposed v-SMLRC-CDdual can maximize the inner-class margin and effectively enhance the generalization performance of LRC. Empirical results conducted with large scale document datasets demonstrate that the proposed method is effective and comparable to other related methods.

In order to solve the problem of lack of discriminability in the l₁-norm constraint sparse representation, visual tracking via locality-sensitive kernel sparse representation is proposed. To improve the linear discriminable power, the candidates’ Scale-Invariant Feature Transform (SIFT) is mapped into high dimension kernel space using the Gaussian kernel function. The locality-sensitive kernel sparse representation is acquired in the kernel space. The candidates’ representation are obtained after multi-scale maximum pooling. Finally, the candidates’ representation is put into the classifier and the candidate with the biggest Support Vector Machines (SVMs) score is recognized as the target. And the experiments demonstrate that the robustness of the proposed algorithm is improved due to the use of the data locality under the kernel sparse representation.

Frequency Diverse Array (FDA) radar is a new radar technique proposed in recent years. FDA uses a small frequency increments across its array elements to provide a range-dependent transmit beampattern, which overcomes the disadvantages of a phased-array providing range-independent beampattern, and offers many promising advantages for radar applications. This paper introduces the concepts, principles and application characteristics of FDA radar, makes an overview of recent FDA radar literature, and discusses FDA radar promising applications, along with existing technical challenges.

A low Radar Cross Section (RCS) and broadband Magneto-Electric (ME) dipole patch antenna from 7.81 GHz to 13.65 GHz covering the whole X band is designed and fabricated. Metal patches printed on the substrate form the electric dipoles, three metallic vias connected to the radiation patches and the metal ground account for the magnetic dipole radiation. The whole antenna is connected with a T-shaped feed structure which excites electric and magnetic dipoles simultaneously. Numerical and experimental results incident that the RCS of the ME dipole patch antenna can be reduced in the whole bandwidth which the largest value is up to 17.9 dB by cutting slots on the ground and optimizing the size, shape, position of the slots. Also, the antenna shows advanced performances such as stable gain and almost consistent pattern in E and H plane.