This paper concerns the concurrent communication interference problem that cognitive user conducts to primary user’s receiver under cognitive radio network. Adopted the Information theory viewpoint, it analyzes the interference power that cognitive user conducts to primary user’s receiver under the restrictive condition of a throughput threshold and communication outage probability for primary user. Moreover, it cites the Markov inequality to deduce out the domain of primary user’s transmission radius. Meanwhile, numerical analysis indicates that under certain conditions the correlation of the average throughput of primary user, the accessed number of cognitive user and primary user’s transmission radius is quantitatively mutual restriction. Eventually, this paper develops a network simulation platform for cognitive radio based on outage probability and analyzes the practical function relation between primary user’s throughput and transmission radius under different density of cognitive user, which validates the rationality and correctness of the model.

In this paper the frequency turbo equalization is investigated for Discrete Fourier Transformation Spread Orthogonal Frequency Division Multiplexing (DFT-S-OFDM) systems with transmitter In-phase and Quadrature Imbalance (IQI) interference caused by imperfect Zero Intermediate Frequency (ZIF) Radio Frequency (RF) front ends. Based on the widely orthogonal principle and the turbo equalization principle, the frequency Widely Linear Minimum Mean Square Error (WLMMSE) turbo equalizer for DFT-S-OFDM systems with transmitter IQI is derived. Matrix transformations are employed to further reduce the complexity. Simulation results confirm that with transmitter IQI, the proposed turbo equalizer significantly outperforms the conventional counterpart turbo equalizer with only slightly increasing of the computation complexity.

Compressed sensing offers a new wideband spectrum sensing scheme in cognitive radio. This paper presents a cooperative sensing scheme based on compressed sensing to sense channel energies without reconstructing the wideband spectrum. Multiple secondary users employ a number of wideband random filters to achieve channel energy measurements. A centralized fusion center is used to collect simultaneously the measurements where a novel cooperative recovery algorithm named Simultaneous Sparsity Adaptive Matching Pursuit (SSAMP) is utilized to reconstruct all the channel energies. Simulations show that the cooperative scheme only needs 20% of the required number of filters in additive white Gaussian noise channel and needs 40% in Raleigh fading channel. SSAMP algorithm outperforms the Simultaneous Orthogonal Matching Pursuit (SOMP) on both reconstruction quality and algorithm complexity.

The estimation of multiple timing offsets and multiple frequency offsets in cooperative relay system is investigated. A synchronization sequence based on constant amplitude zero auto-correlation sequence is constructed. Furthermore, the corresponding synchronization algorithms are proposed, which only need auto-correlation and cross-correlation operations. Simulation results show that the proposed preamble and synchronization algorithms can achieve satisfactory performance in cooperative relay system.

Considering Traffic Rate Feedback (CTRF) is proposed for Orthogonal Frequency Division Multiple (OFDM) relay system with different user traffic rate. According to user traffic rate and channel gain, CTRF adjusts dynamically the value of feedback utility function and then compares it with feedback threshold to decide feedback, which can reduce the feedback quality of the system. Meanwhile, a cross-layer scheduling criterion based on user Traffic Queue Proportional Fair (TQPF) is proposed. Finally, a feedback reducing and scheduling algorithm combining CTRF and TQPF (CTRF-TQPF) is proposed to support different traffic rate. Theoretical and simulation results show that CTRF can reduce feedback and CTRF-TQPF can meet user traffic need and reduce packet loss rate of the system.

The Triple Correlation Function (TCF) and the partial TCF of sampled m-sequence are studied and described in this paper. To recognize synchronization codes of secure communications, a recognition method is proposed firstly based on the peak feature of the partial TCF to analyze and judge frame length. At first, the partial TCF is got by operating the synchronization codes; then, the information codes and synchronization codes are distinguished by the similar peak feature; finally, the code length and the first bit of synchronization code are got. The simulation results show the method can found the frame synchronization code quickly and exactly by fewer codes and recognize synchronization codes.

A joint design of FPGA-based encoder and decoder of LDPC codes is proposed. In this new design, the LDPC encoder and decoder share the same parity-check calculation circuit and the same RAM block, resulting in significantly reduced resource consumption in hardware implementations. The design is suitable for encoding and decoding realizations based on parity-check matrix. It can accommodate full-parallel architectures both for the encoder and decoder, or partial-parallel architectures that are widely adopted nowadays. Furthermore, various decoding algorithms such as the sum-product and the min-sum algorithms can be adopted in this design. The proposed joint design method is applied to design the enoder and decoder of two different groups of LDPC codes, both with a partial-parallel structure. The implementation based on an Xinlinx XC4VLX80 FPGA shows that the designed encoder and decoder can work well in a parallel way, and only consumes slightly more hardware resources than that required by a single decoder. As a result, the proposed design can effectively reduce the hardward consumption without sacrificing the throughput.

To improve the performance of video transmission over Wireless Local Area Networks (WLAN), a dynamic mapping scheme based on Enhanced Distributed Channel Access (EDCA) is proposed. This scheme builds initially the importance-based sorting model for video data packets and computes statistically the average service rate for each access category of EDCA, and then sends dynamically the sorted video packets into different access category for transmission according to the available resources. Because the proposed scheme that modifies the still mode of packets mapping scheme in EDCA can make full use of the network resources, it improves the transmission performance for video transmission over WLAN. The experiment results show that the proposed scheme can reduces the transmission delay of packets and increases the quality of reconstruction images.

The Doppler effect is inherent in communication systems which makes the carrier synchronization critical to the whole system. In underwater communication environment, the Doppler effect is more severe due to the limited sound speed. In this paper, the Doppler effect of underwater channel is analyzed by formulas on a software-defined radio communication system. Then an effective algorithm is developed which can estimate and compensate the frequency shift. The simulation results show that this algorithm works out within the speed of 15 m/s, when the signal to noise ratio is above -22 dB. The sea experimental results show that the system can successfully achieve the carry wave synchronization with the speed to be 6 knots.

In order to study the effect of terminal moving on QoS in wireless networks, a cross-layer network calculus model is established to calculate the delay and backlog performance parameters when communication terminals are under different moving speeds. This model combines the idea of cross-layer analysis and network calculus theory, which mapping the different characteristic of network layer, link layer and physical layer into a series of network calculus components. Based on the cross-layer network calculus model, the corresponding service curve can be derived conveniently when moving terminals are under different moving speeds using network calculus theory, in addition, the backlog and delay performance parameters can be calculated. Simulation results veried that the established cross-layer network calculus model can analysis the backlog and delay performance in wireless networks under different terminal moving speeds.

An energy-efficient Location-Based Cooperative Routing (LBCR) algorithm is proposed to reduce the overall transmission power for routing in wireless networks. With theoretical analysis, appropriate relay node can reduce the transmission power of the cooperative link, given the outage probability of the link constrained at a certain target level. Based on the Adaptive Forwarding Cluster Routing (AFCR) algorithm, LBCR algorithm uses the location information of nodes to select appropriate relay node for each hop, and then combines multi-hop cooperation strategy to form the route from source node to destination node. Simulation results show that, compared with noncooperative routing algorithm and hop-by-hop cooperative routing algorithm, LBCR algorithm can obviously reduce the overall routing transmission power.

Localized network coding is a promising technique to improve the performance of a wireless multihop network when multiple concurrent unicast sessions are present in the network. However, most existing mechanisms in this field do not consider the issue that the potential diversity in packet size has a big impact on the coding efficiency. In this paper, the issue of achieving optimal per-byte coding efficiency via localized network coding is studied. An efficient localized network coding mechanism is designed to provide high per-byte coding efficiency. Simulation results show that the designed mechanism can greatly improve the network throughput as compared with existing mechanisms.

The stability of non-cooperative program game model of the capacity analysis for mobile Ad hoc networks is investigated. First of all, the evolutive equations for the send nodes flow transmit speed of non-cooperative programming game Mobile Ad hoc NETworks (MANET) capacity analysis models is obtained. Based upon this, Lyapunov function is constructed and MaπkuH stability theorem is used to get the stability of non-cooperative programming game MANET capacity analysis models. It is verified by simulation experiment that this model has good stability.

The Internet growth coupled with the variety of multicast services is creating an increasing need for multicast traffic support by routers and packet switches. However, the traditional crossbar-based multicast scheduling schemes are unable to meet the needs of high-speed switching for the low performance and high implementation complexity. In this paper, a Two-Stage Multicast Switch (TSMS) is proposed, which is a serial combination of a Multicast To Unicast (MTU) switch to copy input cells from various sources simultaneously and a Combined Input and Output Queueing (CIOQ) switch to deliver copies of multicast cells to their final destinations. Based on MTU switch, a novel Largest Fanout Cardinal Number First-Uniform Middle Buffer Allocation (LFCNF-UMBA) scheduling algorithm is designed to determine how to copy multicast cells into unicast cells. By coordinately using Maximal Matching scheduling algorithm in CIOQ switch, it is proved that speedup of 2−2/(N+1) is necessary and 2 is sufficient for a M×N TSMS to achieve 100% throughput under any admissible multicast traffic pattern, which is also verified by the simulation results.

To provide end-to-end QoS provisioning in heterogeneous wireless networks and meet the requirements of existing and future network applications, is a challenge in next generation networks. QoS mapping is an effective technology to resolve the problem. In this paper, a QoS Mapping Technology based on Flow Aggregate (QMT-FA) is proposed to assure end-to-end QoS for multimedia services over heterogeneous wireless networks. The proposed method establishes virtual Flow Processing Plan (FPP) above physical network, and allows QoS class mapping in intermediate networks to be transparent over FPP. Then a Mapping Evaluator (ME) entity sitting at a gateway/router determines appropriate QoS mapping to the new network at the network edge. Through mapping services into multidimensional space and designing normal data structure, the method shields the effect of intermediate network QoS mapping, assures the end-to-end QoS of multimedia services in heterogeneous wireless networks, resolves scalability problem, and reduces management complexity and implementational difficulty. Numerical and simulation results are given to demonstrate the effectiveness of the proposed method.

In surveillance wireless sensor networks, the reliable transport of urgent information is a key issue for accurate reporting of events. This paper studies the characteristics of urgent information, and proposes a Reliable Transport Protocol for Urgent Information (RTP-UI) in wireless sensor network. RTP-UI uses a novel congestion control mechanism, combining the current queue length with the queue length change rate as metric of congestion degree. Each node calculates its congestion degree locally and adopts different rate adjustment (bandwidth allocation) schemes depending on their different states. Extensive simulation results show that RTP-UI provides a high reliable transport mechanism for urgent information.

With the manner of storing-carrying-forwarding, nodes can communicate with each other in opportunistic network, but the limited buffer should be used reasonably. Based on message redundancy estimating, an adaptive buffer management mechanism is proposed in this paper. According to the node’s activity degree and the number of message copies, the status of message transmitting in the network can be predicted; moreover, with the parameter of message redundancy, the decision on message receiving and forwarding can be made dynamically. Numerical results show that the methods to evaluate node’s activity degree and number of message copies are accurate; furthermore, comparing with other buffer management mechanisms, the proposed mechanism can improve message delivery rate effectively, reduce latency and overhead ratio.

Path traverse is a kind of important software testing method of software test. However, as the number of paths of software is usually exponential, to test every path is unpractical. From the point view of software security test, the execution of critical code fragments in the binary program is more interested. The critical code fragments are the statements which call the danger function, the functions with high cyclomatic complexity and the code fragments with loop-writing memory. In this paper, a data auto-generation method is presented, which covers the critical code area, this approach is based upon binary program and does not need the source code of the test program. These paths which can reach the critical code areas are automatically obtained by a method called path backtracking, and are automatically generated test data for these paths by a method called path leading. It is based on the symbolic execution and concrete execution, regulates the test input step by step and uses the constraint solver to generate the test cases. Theory analysis and experiment results indicate that the method of path leading can reduce the execution number of test data generation contrast with existing methods of generating test data for a given path, the method of path leading improves the efficiency of test data generation.

Based on binary periodic complementary sequence sets, constructions of binary or quaternary periodic complementary sequence sets with Zero Correlation Zone (ZCZ) are proposed. The resultant binary ZCZ periodic complementary sequence set is constructed by interleaving technique and shift sequences. And the resultant quaternary ZCZ periodic complementary set is based on the inverse Gray mapping. If the initial periodic complementary set is optimal, both binary and quaternary ZCZ periodic complementary sets are optimal with respect to the theoretical bound. Moreover, the proposed approach provides flexible choices for ZCZ length.

In the paper, the partial Hilbert spectrum near the frequency of the target ridge and average bandwidth of the real sea clutter data is analyzed, and the influence of the target and polarization on the ridge and the average bandwidth of the partial Hilbert spectrum are discussed. As shown of the result, the appearance of the target will smooth its ridge and decrease its average bandwidth, on the base of the result, a novel method is proposed to detect the weak target in the sea clutter, where the average bandwidth is calculated by the partial Hilbert spectrum near the frequency of the target ridge to extract the difference of the target and the sea clutter, then it is used as the detection statistic to detect the weak target in the sea clutter. Compared with the target detection method directly using the box dimension and the Cell Average-Constant False Alarm Rate (CA-CFAR, 100 pulses), the proposed method improves the detection performance of the weak target in the sea clutter distinctly.

In High Range-Resolution (HRR) radar, a target extends probably more than one range bins and the parametric adaptive detection is studied in this paper for such distributed target, where the disturbances in both primary and secondary data are represented by a vector autoregressive model with random spatial covariance matrix. Subsequently, the corresponding detectors are derived according to Bayesian one-Step Parametric Generalized Likelihood Ratio Test (B1S-PGLRT) and Bayesian two-Step Parametric GLRT (B2S-PGLRT) decision rules. However, the former leads to no close formulation and the latter has the similar detection architecture with the classic Parametric Adaptive Matched Filter (PAMF), using Maximum A-Posteriori (MAP) estimator instead of Maximum Likelihood Estimator (MLE), of the spatial covariance matrix. Meanwhile, the normalized version for B2S-PGLRT is also given. Finally, the processing steps and its computation issues are analyzed for the Bayesian parametric detectors and their detection performances are evaluated via Monte Carlo simulations. The results show that the parametric matched filter in Bayesian framework is better than GLRT, when the training data are not sufficient.

The Ultra Wide-Band Short-Pulse (UWB-SP) radar used for detecting targets is a promising technique in fire rescue operations, police awareness, urban-warfare, life-threatening and other fields, and it can be used for noncontact measurement of the tracking and imaging of moving target behind walls. As the Shape Estimation Algorithm based on BST (Boundary Scattering Transform) and Extraction of Directly scattered waves (SEABED) algorithm (a new target localization and identification algorithm) based on the UWB-SP radar is not applicable for that application, this paper proposes a new algorithm to obtain the target shape imaging and track it synchronously using triangle localization method and the difference of time delay. In this paper, the proposed algorithm based on a system model built in the near field can effectively estimate the velocity and track of moving target with the imaging result. Simulation results show that the effect of the wall can be removed visibly and the purpose of the imaging and tracking of moving target can be realized well.

The ability to reconstructing the terrain height profile of MIMO InSAR outperforms the ordinary multibaseline InSAR. One key technology of MIMO InSAR is the echo separation on the receiver. The available orthogonal signals introduce great cross-interferences between different MIMO Channels due to their inadequate orthogonality. An equivalent MIMO InSAR imaging mode without transmitting orthogonal signals is presented in this paper, whose echo separation do not depend on the orthogonality of transmitting signals. Instead, the elements of this MIMO InSAR system transmit alternately in different pulse duration under this mode, hence the mainlobe echoes of different transmitting signals appear in different pulse duration coordinately. The cross-interferences are suppressed sufficiently with low sidelobe transmitting pattern in elevation. Furthermore, the multichannel azimuth processing based ScanSAR technique is employed in this MIMO InSAR imaging mode to improve its swath width and azimuth resolution. The numerical simulations prove the validation of the proposed mode.

Time delay Active Radar Calibrator (ARC) is the crucial equipment for image quality evaluation and radiation calibration of Synthetic Aperture Radar (SAR). The technique of time delay in ARC will reduce the influence of local noise and improve the measure precision. However, the image quality of time delay ARC will be influenced inevitably, especially for high-resolution SAR. In this paper, the analysis model for image quality influence of ARC induced by time delay for high-resolution SAR is established. The effects induced by different time delay, including peak power, 3 dB width of main lobe, Peak Side Lobe Ratio (PSLR) and Integrated Side Lobe Ratio (ISLR) are analyzed quantificationally. A correction method of time delay is proposed, and the validity of the method is proved through simulation.

The channel imbalances will reduce the performances of the multi-channel synthetic-bandwidth SAR system, so measures should be taken to correct them. In this paper, a correction method based on the raw data is presented. Before acquiring the synthetic-bandwidth signals, the system is switched to emit and receive single sub-band signals, and then the channel imbalances are extracted from the Doppler spectra between different channels. In the method, the additional inner calibration circuits can be left out, which will simplify the system design. Finally, the practicability of this method is confirmed by the processing of the real data which obtained by the displaced phase center multiple-beam SAR system.   

The issue of joint estimation of Direction Of Departure (DOD), Direction Of Arrive (DOA) and polarization for MIMO radar with electromagnetic vector sensors is investigated. A novel bistatic MIMO radar system with multiple transmit sensors and multiple receive electromagnetic vector sensors is proposed. Three joint parameter estimation algorithms, which are, respectively, termed as four-dimensional MUSIC, ESPRIT and iterative one-dimensional (1D) MUSIC, are presented. The iterative 1D-MUSIC algorithm first uses the internal structure of the vector sensors to obtain a set of initialize DOA estimates, and then two 1D-MUSIC searches are employed to get the DOD and DOA estimates in succession, finally a polarization ESPRIT algorithm is proposed for polarization estimation. The iterative 1D-MUSIC algorithm is suitable for irregular array geometry, imposes less constraints on the receive array geometries, and requires no two-dimensional or high-dimensional searching. Moreover, this algorithm can improve the DOA estimation performance by extending the array aperture. The CRB for the issue under consideration is also derived. Simulations show that the estimation accuracy of the iterative 1D-MUSIC algorithm is closest to the CRB, compared with those of the previous two algorithms.

Positioning method aims to get the geographical coordinates of each pixel in SAR images. It is necessary to calibrate the parameters of the positioning model to increase precision. This paper presents a method based on sensitivity equations to calibrate the positioning model by linearizing the position errors. Then a method of joint calibration of the positioning model over large areas including several scenes is proposed, and it can achieve the positioning of large areas with few Ground Control Points (GCPs) by using Corresponding Points (CPs) between adjoining scenes. The results show that with few GCPs the accuracy of this method is better than polynomial ortho-rectification model and range-Doppler model.

By emitting H- and V-polarized pulses adjacently and receiving echoes with duo-polarized channels, multidimensional waveform encoding fully-polarimetric Synthetic Aperture Radar (SAR) can obtain all polarimetric components in one Pulse Repetition Interval (PRI). However, different polarized echoes will overlap under this mode, and thus should be separated effectively to realize fully-polarimetric remote sensing. To solve this problem, this paper proposes a new elevation Digital BeamForming (DBF) approach, which systematically integrates Finite Impulse Response (FIR) filters into the null-steering beamformer, to separate echoes. Compared with conventional null-steering beamfoming, FIR filters in the approach can deal with the issue of pulse extension well, thereby achieving better separation results. In the paper, detailed signal processing procedures, along with the block diagram of the new DBF, are provided. Simulation results are given to demonstrate the validation of the proposed approach.

Synthetic Aperture Radar (SAR) plays a very important role in ocean remote sensing. Current movement and ocean wave transmission are crucial constituent part of ocean dynamic information. However, regular SAR ocean image processing treats SAR image as transient state, and can not get dynamic information. This paper gets several sequent time interval images from one image using sub-aperture division method. An optimized phase correlation method is proposed to match the corresponding parts of sequence SAR images. According to the movement quantity and direction, the ocean waves movement tendency can be got. Experimental results show that the optimized method presents 1/10 resolution accuracy and noise robustness. For the same ships in sequence images, the proposed matching method and the “ship wake” method are used to calculate the ship speed. Two results are very close to each other, which proves the proposed method is effective.

The SAR raw signal simulator in the time domain by the target-by-target method is inefficient, while the simulator in the two-dimensional (2-D) frequency domain can not be directly used to generate the Terrain Observation by Progressive Scans (TOPS) raw data. As for this issue, an efficient TOPS raw data simulation approach is proposed. In the range direction, the 1-D convolution between echoes of referenced point target and scattering coefficient of the imaged scene is introduced, while raw data is simulated and stored by the pulse-by-pulse method in azimuth. The processing steps of the simulator are given in detail, and its computational complexity is analyzed. Simulated echoes of the proposed simulator and the accurate time domain simulator are compared. Finally, the imaging and interferometry results of the simulated data are given to validate the effectiveness of the proposed approach.

In order to construct a high-dimensional data approximate model in the purpose of the best coverage of the distribution of high-dimensional samples, the classification algorithm of multiple observation samples based on L1 norm convex hull data description is proposed. The convex hull for each class in the train set and multiple observation samples in the test set is constructed as the first step. So the classification of multiple observation samples is transformed to the similarity of convex hulls. If the test convex hull and every train hull are not overlapping, L1 norm distance measure is used to solve the similarity of convex hulls. Otherwise, L1 norm distance measure is used to solve the similarity of reduced convex hulls. Then the nearest neighbor classifier is used to solve the classification of multiple observation samples. Experiments on three types of databases show that the proposed method is valid and efficient.

Image splicing is the most fundamental operation of creating an image forgery, thus the detection and localization of image splicing attract increasing attention recently. In this paper, a blind and passive approach of splicing localization is proposed based on original image estimation. By color filter array interpolation, the original image of the test image is estimated and the coherence of the pixels’ neighbor is re-constructed. Using a comparison between the test image and the estimated original one in edge pixels, the localization is implemented. Experimental results show the good performance of the proposed method.

Based on global sparse representation of image and local property of the patch, an efficient compressive imaging algorithm is proposed, which combined two priors: the low dimensional manifold property of local image patch and the sparse representation of analytic contourlet. The iterative hard threshold and manifold projection method are used to reconstruct images. To reduce the computational complexity, the union of a group of linear sub-manifolds is used to approximate the nonlinear manifold which tiling the whole space of patch. The initial classification is obtained based on the dominant orientation of the local image patch, then the base of every linear subspace is obtained by sparse orthogonal transform over the blocks corresponding to each class. Experimental results show that the proposed algorithm can reconstruct an image more efficiently both in the Peak Signal-to-Noise Ratio (PSNR) and visual quality than the current algorithms.

Hilbert-Huang Transform (HHT) is a fully data driven adaptive non-stationary signal time-frequency analysis method. But the Hilbert energy spectrum curve of speech signal is fluctuate in strong noise environment，it has a great influence to voice activity detection. So an effective voice activity detection algorithm is proposed based on HHT and Order Statistics Filter (OSF) in this paper. This method first decompose noise signal into intrinsic mode functions by empirical mode decomposition. Then the Hilbert energy spectrum is synthesized by adaptive weight selection of each intrinsic mode functions, through OSF to smooth the energy spectrum. Finally, the speech and noise divergence is judged by means of the smoothed energy spectrum. Experimental results show obviously that under complex noisy environment, this method is still able to effectively detect the speech signal, and reduce the error detection rate in low signal to noise ratio conditions.

In order to analyze the performance of Single-Carrier (SC) 60 GHz communication system, a structure of physical layer is designed based on IEEE 802.11ad standard. The impacts of hardware impairments on the communication performance are studied, including phase noise and non-linear distortion of Power Amplifier (PA), and the non-linear distortion is more significant. Simulation results indicate that the performance degradation caused by hardware impairments is much less for π/2-BPSK and π/2-QPSK modulation than that for π/2-16QAM modulation. To get a high bit rate and acceptable performance, π/2-QPSK modulation is a good choice in general, and π/2-16QAM is better when hardware impairments are trivial.

The handoff mechanism, a key technology to support the user seamless mobile services in wireless communication system, has a great impact on users’ services experiences and application. This paper presents the auxiliary handoff mechanism based on context and particle filter algorithms, using particle filter algorithms to predict the mobile station location next time accurately, the user context information plaies an auxiliary supporting role. This method is a pre-handoff decision-making mechanism, to provide fast, accurate and reliable basis for decisions, and reserve resources in advance, significantly improve the QoS of network. Theoretical analysis and simulation results show that location prediction is closer to true trajectory of the user, the RMSE of position and velocity is smaller, greatly improve the success rate of handoff.

Zero-correlation linear cryptanalysis is a newly proposed attack of block ciphers. The first step of this cryptanalysis is to construct a zero-correlation linear hull whose correlation value is 0. This paper investigates the construction of zero-correlation linear hull for CLEFIA-like structure with Substitution-Permutation (SP)-type round function. And a new method of finding (4n+1) round zero-correlation linear hull of this structure is proposed. By the proposed method, large amount of zero-correlation linear hulls of 9 round CLEFIA are obtained.

To lower cost of testing digital integrated circuits, compressing precomputed test set is an effective resolution way. A dictionary compression scheme using entry derivative and two-level coding is proposed based on digits of index far fewer than that of dictionary entry and enormous don’t-care bits in test data. The introduced cyclic shift operation can arbitrarily shift don’t-care bits in order without losing them so that derivative performances of entries are expanded and number of non-entry vectors is decreased. In addition, two-level regular coding is adopted to reduce volume of code words and complexity of decompression circuit. The experimental results show that the proposed scheme can farther heighten test data compression ratio and decrease test time.