The missile-borne SAR platform has the characteristics of nonlinear trajectory and high-squint mode. A frequency-domain imaging algorithm based on local Cartesian coordinate and subregion processing is proposed. For high-squint mode, the range model is built in local Cartesian coordinate to match accurately the azimuth signal after range walk correction. To compensate the azimuth-dependent range cell migration and Doppler parameters accurately, the imaging area is divided into several subregions. The final focused image can be obtained when all the subregion images are interpolated uniformly into the ground coordinate. Finally, the point targets simulation and real SAR data verify the effectiveness of the proposed algorithm.

Traditional meter-wave radar usually suffers from the problem of Beam Split (BS) and Radar Blind Area (RBA) in the situation of low-grazing angle. To alleviate this difficulty, a Frequency Diverse Subaperturing Multiple-Input Multiple-Output (FDS-MIMO) radar is proposed and a theoretical framework for the analytical investigation of multipath characteristics is presented. The specular and perturbational multipath model is built, along with closed-form expression of the joint transmit-receive beampattern gain. Moreover, a notional concept of Multipath Mitigation Area (MMA) is defined together with the corresponding boundary conditions, and the Low Observability Rate (LOR) is defined as a performance benchmarkan to evaluate the FDS-MIMO radar beam overage capability. Next, the FDS-MIMO radar low-altitude beam coverage performance is optimized according to the soutions of the boundary conditions. Both theoretical analysis and numerical results demonstrate the advantages of FDS-MIMO radar over the conventional phased-MIMO radar in terms of low altitude beam coverage performance, and the BS and RBA of meter-wave radar is decreased by ultilizing the range-dependent beampattern.

Conventional phased array radar transmits coherent signal to form antenna pattern. By transmitting and receiving antenna reuse its aperture is always less than MIMO radar. This paper firstly analyses the same points and the difference between MIMO radar and phased array radar. It further points out that the essential advantage of MIMO radar is the digital transmitting beam forming. Second it designs a diversity phased array radar in collision avoidance atmosphere. Its transmitting part uses phase array system, while the receiving part uses the Digital BeamForming (DBF). Through the analysis for the limitation of the digits phase shifter, it proves that this radar can achieve the same virtual aperture performance as MIMO radar, while the rader can avoid to produce the orthogonal signal. Finally through the computer simulation it verifies the feasibility and effectiveness of the method. This radar system can effectively reduce the cost and improve channel consistency under the premise of promised beam width.

A new algorithm is proposed to estimate jointly the four parameters (EDOD, ADOD, EDOA,ADOA) of targets based on the double-extension of aperture degree of freedom by combining MIMO technique with Minimum redundancy array under the conditions of non-uniform rectangular array configurations both on transmitter and receiver. Firstly, the two permutation matrices are constructed by utilizing the operational properties of the Khatri-Rao product of multiple matrices. Then the new data which possesses the characteristics of the double-extension of degree of freedom is attained by performing the twice row permutating, the redundant items deleting, multi-dimensional smoothing and data folding operations on the received data. The results illustrate that: the proposed method can estimate the four parameters of targets efficiently, and the estimated parameters are paired automatically without extra pairing operation. The parameter estimation performance of the proposed method is better than those of the ALS and multi-dimension ESPRIT methods under the same simulation conditions. And the proposed method can provide much stronger parameter identifiability than the conventional ones.

A novel low sidelobe method is proposed through the improvement of the classical method of MIMO radar transmit waveform design. Firstly, two parameters, involving the lower boundary and the upper boundary of the mainlobe of the transmitted waveform, are introduced. While the value of the lower boundary is given. Secondly, a semidefinite programing optimization problem is established, whose objective function is minimization of peak-sidelobe or integrated-sideloble. The transmit waveform covariance is semi-positive and the signal power of each array element is fixed. Further, the restriction on the mainlobe fluctuation is added to the constraint of the optimization problem. What’s more, if the upper boundary is changed, the mainlobe fluctuation and sidelobe will be changed simultaneously. Finally, only once convex optimization algorithm is used to obtain the global optimal solution. The simulation results show that the proposed method has the advantages that the sidelobe is lower and can be contolled

To realize the high-resolution wide-swath mapping capability of spaceborne SAR, this paper presents a parabolic cylinder reflector based MIMO SAR system. According to the analysis of system configuration and Short-Term Shift-Orthogonal (STSO) transmitting waveforms, the specific processing method are elaborated. Taking advantage of parabolic characteristics in elevation, the narrow beams with high gain can be easily realized by the parabolic cylinder reflector. This facilitates the efficient separation of STSO transmitting waveforms by using the digital beam-forming technique, therefore, more azimuth equivalent phase centers can be obtained. After the multichannel reconstruction processing in azimuth, the echo signals from illuminated scene can be imaged by conventional imaging algorithms. The simulation results show that, the proposed system has satisfactory performance for MIMO SAR imaging.

Based on the characteristics of short pulse non-coherent radar, the parameterized signal model is established. By analysis on the reasons of no-coherence, compensative coherent processing algorithm based on matching filter and parameter estimation is proposed. The rationality of the compensative coherent  processing is proved by the mathematical derivation as to single point target. Then, requirement for the range extended target is analyzed in theory, in the condition of approximate compensative coherent processing. Finally, the theoretical analysis results are verified by simulation.

An unambiguous acquisition scheme for BOC (m,n) signals is proposed by constituting a Synthesis Supplemental Correlation Function (SSCF) according to their features. By applying the proposed scheme, side peaks are well eliminated and an unambiguous correlation function with a single narrow peak is obtained. It is confirmed that the proposed scheme is capable of acquiring BOC (m,n) signals. It is especially compared with the traditional BPSK-like method and the results show that the SSCF scheme performs much better in the acquisition success rate and peak-to–average ratio despite the noise interference.

Atmosphere refraction error is a main error factor to affect synchronization accuracy, tracing accuracy, navigation accuracy and positioning accuracy for various radio systems. On the basis of geometrical optics, the ray tracing method can precisely make this error correction. For the problem that traditional ray
tracing method can not deal with the abnormal atmosphere, ray tracing differential form is derived and then a correction method suitable for arbitrary atmosphere is proposed. The tracing data from ground station are taken to test this method. In addition, the refractive error in evaporation duct is compared with that in
standard atmosphere. The results show that the refractive error of radio wave trapped entirely in the duct has the biggest influence. The proposed method provides technique support for improving the measurement precision of radio system in arbitrary atmosphere.

Magnetic Induction Tomography (MIT) is a contactless Electrical Impedance Tomography (EIT) technique to reconstruct the conductivity distribution of biological tissue using the principle of electromagnetic induction. In this paper, a rotating magnetic induction imaging system is constructed by using Helmholtz coil and 20 detection coils, with filtered back projection algorithm. The single target and double target detection coil measurement data are processed by the two order and four order derivative peak sharpening algorithm. The measurement data before and after processing of the reconstructed image are compared by three objective parameters. The results show that the magnetic induction imaging derivative method can effectively increase the peak sharpening image quality.

A Direction of Arrival (DOA) estimation method based on reduced-dimensional polynomial root finding technique is proposed for coprime array. Coprime array has two uniform linear subarrays with coprime inter-element spacing and antenna number. Based on the cross covariance matrix of the subarrays, the proposed method exploits the rotational invariance within the longer subarray to extend the aperture of the shorter one. After constructing the noise subspace via matrix partition and reducing the two dimensional parameter estimation problem into one dimensional root finding, automatically paired two dimensional parameters can be estimated. Finally, unambiguous DOA is determined from the intersections of the two groups of estimations, which are generated from the previously obtained two dimensional parameters. In contrast to combined MUltiple SIgnal Classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) for coprime array, the proposed algorithm achieves improved DOA estimation results and increased identifiable source number with reduced computation complexity. Furthermore, it is robust to spatial color noise. Multiple simulation results verify the effectiveness of the proposed approach.

The kernel Extreme Learning Machine (ELM) has a problem that the kernel parameter of the Gauss kernel function is hard to be optimized. As a result, training speed and classification accuracy of kernel ELM are negatively affected. To deal with that problem, a novel kernel ELM based on K interpolation simplex
method is proposed. The training process of kernel ELM is considered as an unconstrained optimal problem. Then, the Nelder-Mead Simplex Method (NMSM) is used as an optimal method to search the optimized kernel parameter, which improves the classification accuracy of kernel ELM. Furthermore, the K interpolation method is used to provide appropriate initial values for the Nelder-Mead simplex to reduce the number of iterations, and as a result, the training speed of ELM is improved. Comparative results on UCI dataset demonstrate that the novel ELM algorithm has better training speed and higher classification accuracy.

In order to filter out the interference of WIMAX (3.3～3.8 GHz) and WLAN (5.125～5.825 GHz) narrowband signals to Ultra WideBand(UWB) system, a Co-Planar Waveguide (CPW) fed miniaturized tapered slot antenna with dual band-notched characteristics is proposed. The CPW structure can effectively
extend the bandwidth of the antenna and realize the full coverage of the whole UWB (3.1～10.6 GHz) frequency band. The dual band-notched characteristics (3.15～3.97 GHz and 4.94～6.05 GHz) are effectively achieved by etching the L-shaped slot in the antenna feeder and opening a pair of E-shaped slots in the
radiating patch, which can inhibit WIMAX and WLAN interference to the UWB system. The antenna is simple and compact, and the size is very small, only 40 mm×18 mm×0.813 mm. The simulated and measured results show that the antenna has good notch and gain characteristics in the ultra wideband band, and can be used in miniaturized UWB system. The method has certain reference significance for the research of notched tapered slot antenna.

An equivalent circuit method of performance estimation for hexagonal loop composite absorbing metamaterial is proposed, and the corresponding equivalent circuit model is established. Based on the Fourier analysis of hexagonal lattice distribution, the equivalent distribution periodic parameter is proposed and the
estimation method of RLC parameters is given according to the size of units. The applicability and accuracy of the equivalent circuit model for several structure dimensions are verified and compared with HFSS. A sample is fabricated and measured for further verification, which has a good broadband radar absorbing performance in
1.7～5.7 GHz.

Traffic congestion is a problem faced by cities, and it is urgent for solving this issue. Accurate short-term traffic state prediction is benefit for citizens to know the traffic information in advance, and take the measures in time to avoid the congestion. In this paper, a short-term traffic state prediction approach is proposed based on Fuzzy C-Means (FCM) clustering and Random Forest. Firstly, a novel Adaptive Multi-kernel Support Vector Machine (AMSVM) which incorporates the spatial-temporal information is used to predict the short-term traffic parameters, including the volume, the speed and the occupancy. Secondly, the historical traffic data are analyzed based on FCM algorithm, and the historical traffic state information is got. Lastly, the Random Forest (RF) algorithm is utilized to analyze the predicted short-term traffic parameters, then the final predicted short-term traffic state is obtained. This method incorporates the spatial-temporal information as well as applying the Random Forest to a new research field of short-term traffic state prediction. The experimental results demonstrate that the evaluation method of historical traffic state based on FCM is suitable for both freeway and urban road scenarios. Besides, the Random Forest has higher prediction accuracy than other common machine learning methods, thus providing the short-term traffic information timely and reliably.

For videos captured by in-car cameras, the filter-based tracking is a challenging task due to complex environments and mutable object scales. A scale adaptive tracking filter is proposed based on the background information. Firstly, the relative motion of each object is estimated by extracting features from gradient histograms between frames. Then, the object location on the next frame is determined and utilized to delimit an image block. Finally, the object scale is obtained through dynamic scaling pyramid model within image block. The proposed algorithm is examined by 27 in-car videos including 23 KITTI videos and 4 domestic videos. In experiments, the proposed algorithm suppresses effectively the interferences of environments and objects. It achieves more accurate and more robust object tracking than several popular benchmarks including KCF, DSST, SAMF, SATPLE.

Fuzzy clustering is a kind of clustering algorithm which shows superior performance in recent years, however, the algorithm is sensitive to the initial cluster center and can not obtain accurate results of clustering for the boundary samples. In order to improve the accuracy and stability of clustering, this paper proposes a
novel approach of fuzzy clustering ensemble model based on distance decision by combining multiple fuzzy clustering results. First of all, performing several times clustering for data samples by using FCM (Fuzzy CMeans), and corresponding membership matrices are obtained. Then, a new method of distance decision is
proposed, a cumulative distance matrix is constructed by the membership matrices. Finally, the distance matrix is introduced into the Density Peaks (DP) algorithm, and the final results of clustering are obtained by using the improved DP algorithm for clustering ensemble. The results of the experiment show that the clustering ensemble model proposed in this paper is more effective than other classical clustering ensemble model on the 9 data sets in UCI machine learning database.

Gaussian kernel is usually used as the similarity measure in spectral clustering algorithm, and all the available features are used to construct the similarity matrix with Euclidean distance. The complexity of the data set would affect its spectral clustering performance. Therefore, an improved spectral clustering algorithm
based on Axiomatic Fuzzy Set (AFS) is proposed. Firstly, AFS algorithm is combined to measure the similarity of more suitable data by recognizing features, and the stronger affinity matrix is generated. Then Nyström sampling algorithm is used to calculate the similarity matrix between the sampling points and the sampling points and the remaining points to reduce the computational complexity. Finally, the experiment is carried out by using different data sets and image segmentations, the effectiveness of the proposed algorithm are proved.

A cyclic autocorrelation algorithm of Time Division Data Modulation Binary Offset Carrier (TDDM- BOC) signal, based on frequency domain accumulation, is proposed to estimate the signal parameters: subcarrier rate, Pseudo Noise (PN) code rate and carrier in multipath fading channel. Firstly, the cyclic autocorrelation of received TDDM-BOC signal is computed, then frequency domain accumulation is used to reduce the influence of noise. Finally, through interval measurement between the peak pulses in different slices, parameters mentioned above can be estimated. Simulation results show that the proposed algorithm is effective and works well under the condition of low Signal-to-Noise Ratio (SNR), which has a certain reference value for Bei-dou navigation receiver design.

Fluorescein Fundus Angiography (FFA) is regarded as the golden diagnostic criteria for fundus diseases. However, dislocation or rotation of the interested images on anatomic landmark (like retinal vascular branches, neovascularization), caused by inevitable eyeball movement, brings about difficulties in subsequent
quantitative analysis and progress assessment of the diseases. In order to solve the above problems, a novel method based on mutual information is proposed for automatic registration of FFA image sequence. Firstly, the vessels of image sequence are segmented by multi-scale linear filter and down sampled hereafter by image pyramid. Then, the similarity of sampled images is calculated by mutual information and the evolution strategy is adopted to optimize the registration parameters. Finally, the transformation matrix with maximum mutual information is obtained to register the FFA image. Tests with FFA image sequences of 4 patients (total 1039 frames) show that the overall registration rate of the algorithm reaches 93% and the failure rate is only 1%. Compared with the classical registration methods, the proposed method shows better comprehensive performance in terms of registration rate, computing speed as well as robustness. It lays basic foundations for quantitative analysis on FFA images and potential clinical application.

Traditionally, skin permeability evaluation, which is realized by impedance detected at a certain frequency based on macro electrodes, has the disadvantages of large measurement error, low sensitivity and difficulty in integration. In order to resolve this problem, a flexible non-symmetric interdigital microsensor is designed by analyzing the layered structure of skin and the relationship between skin permeability and impedance of Stratum Corneum(SC). The impedance of SC is measured and analyzed based on the RCW-layered impedance model. It is illustrated that the impedance magnitude  of microsensor output and model fitting parameters  can be used as the important indicators to evaluate skin permeability. It is proved that the developed sensor can be applied to distinguishing the different individuals’ skin permeability, and it strongly supports the adjustment of wearable devices related to human physiological and biochemical detection.

Cross-axis coupling interference influences greatly the measurement accuracy of Three-Dimensional (3D) Electric Field Sensor (EFS). A MEMS-based One-Dimensional (1D) Electric Field Microsensor (EFM) chip with low coupling interference is presented, and a MEMS-based 3D EFS with low cross-axis coupling
interference is developed by arranging three 1D EFM chips orthogonally. Different from previously reported 1D EFM chips sensitive to perpendicular electric field component, the proposed 1D EFM chip is designed to be symmetrical and connected to difference circuit, so that it is capable of sensing parallel electric field component perpendicular to axis of symmetry and eliminating coupling interference. The proposed 3D EFS has the advantages of small size and high integration. Experimental results reveal that in the range of 0～120 kV/m, the cross-axis sensitivities are within 3.48%, and the total measurement errors of this 3D EFS are within 7.13%.

Polar codes have outstanding error correction performance, but the code length of conventional polar codes is not compatible because of their coding method. To construct rate-compatible polar codes, a segmented puncturing method is proposed. Using the rate of polarization, the puncturing effect is measured and the
codeword is removed to make the largest rate of polarization, which is the optimal puncturing mode. As the first codeword of the optimal puncturing mode is 0, the parity check codes are introduced to detect the decoding error of preceding segments codeword. The decoding performance of the method is simulated, results
show that this method can obtain about 0.7 dB coding gain at 10–3 bit error rate compared with the traditional puncturing method, which can effectively improve the performance of the punctured polar codes.

In order to reduce the computational complexity of computing unknown syndromes for the coefficients of the error-locator polynomial and reduce the decoding time when one is decoding, this paper proposed an algebraic decoding algorithm of (41, 21, 9) QR code without calculating the unknown syndromes
by solving the Newtonian identity. Simultaneously, an objective theoretical analysis of the computational complexity is given for the part of improvement. Besides, this paper also puts forward the simplifying conditions to determine the number of errors in the received word, which in order to further reducing the decoding time. Simulation results show that the proposed algorithm reduces the decoding time with maintaining the same decoding performance of Lin’s algorithm

To meet the diversified demand of 5G Network Slicing (NS), while ensuring the reliability of slice, to achieve the optimal allocation of network resources, considering the dynamic mapping and lightweight reliable mapping problem of network slicing, this paper proposes a joint allocation scheme of computing resources, link resources and the spectrum resources of Radio Remote Unit (RRU). Firstly, a multi-objective resource
allocation model oriented to reliability constraints is established, and the Lyapunov optimization model is introduced to ensure the queue stability and optimize the resource allocation. Then, the virtual node mapping algorithm based on queue stability and virtual link mapping algorithm based on reliability are proposed.
Finally, the time is discretized into a series of continuous time windows, and the online network slice mapping algorithm is implemented by using the time window dynamic processing of the incoming network slice request. Simulation results show that the proposed algorithm improves resource utilization and guarantees network reliability.

In order to meet different delay requirements of secondary users and improve the channel utilization, a PRP M/G/m queuing theory spectrum handoff model based on classified secondary user is proposed. Firstly, according to different delay requirements of the main service, secondary users are classified into delay-sensitive and non-delay-sensitive users. The delay-sensitive users have higher priority to access the channel. Secondly, PRP M/G/m queuing theory is adopted to establish the spectrum handoff model. Meanwhile, the extended data delivery time of secondary users with different priorities is deduced and analyzed. Then the adaptive spectrum handoff strategy for secondary users is proposed. Simulation results suggest that the proposed model can reduce the handoff delay and extended data delivery time, which can effectively ensure the QoS of high- priority secondary users and improve the overall performance.

Since the probability bias between 0 and 1 bit in a convolutional code sequence is very small, the existing method based on the probability bias in the input sequence is ineffective for the identification of a self-synchronous scrambler placed after a convolutional encoder. To solve this problem, a novel method for the blind identification of a self-synchronous scrambler is proposed. First, the scrambled convolutional code sequence is divided into blocks, and a new bit sequence is generated, in which each bit is the dot product of a scrambled bit block with a parity check vector of the convolutional code. Second, based on the criteria of maximizing the probability that the linear equations in the generated bits hold, the cost function of the feedback polynomial coefficients of the self-synchronous scrambler is established using the soft decision sequence, which is the output of the demodulator. Third, according to the characteristic of the number of terms in the feedback polynomial, the dynamic fireworks algorithm is modified by constraining the values of elements in fireworks, and the cost function is optimized using the modified dynamic fireworks algorithm. Simulation experiments show the effectiveness of the proposed algorithm. There is no need to search for the feedback polynomial exhaustively in the proposed algorithm. It is robust to the noise and the number of data required is small. Moreover, along with the increase of the number of received data or the decrease of the order of the feedback polynomial, the correct identification ratio of the proposed method increases.

For the over-long embedding lightpath and spectrum fragmentation in transparent elastic optical networks, a node-importance aware coordinated embedding algorithm is proposed. In the stage of node embedding, in order to alleviate spectrum fragmentation and to improve the compactness of node embedding, the spectrum compactness of embedding lightpath and the adjacency between embedding node and embedded nodes are evaluated, and then two node-ranking formulas are presented. Meanwhile, to reduce the probability of the success of node embedding but the failure of link embedding, a coordinated node-link embedding algorithm is proposed. When a pair of adjacent virtual nodes is successfully embedded, the virtual optical link between them is embedded instantly, while spectrum resources are allocated, which minimizes the hops of lightpath embedded by virtual optical link. The simulation results indicate that the proposed algorithm can use the least spectrum resources to accommodate more virtual optical network demands, and reduce the embedding length of virtual optical link.

Because of nowadays airborne network’s updating difficulty of pre-allocated symmetrical key, high communication cost of public key certificate and the requirement of security channel for distributed identitybased key management, identity-based dynamic key management of airborne network is proposed. It is
composed of two algorithms: self-organized generation of master key without the trusted third party and distributed management of user’s private key. Moreover, the master key share and user private partition can be delivered without the pre-established security channel by blinding them so that the scheme is easy to develop and flexible to extend. Finally, the correctness and security of the proposed scheme are proved, it is shown that it can provide the ability to resist the impersonation attack, replay attack and man-in-the-middle attack.

A novel one-dimensional discrete chaotic criterion is firstly constructed by studying the modular operation of the discrete dynamical systems. The judgement of the Marotto theorem is used to prove that the suggested dynamical systems are chaotic. Secondly, several special chaotic systems satisfied with the conditions
of this paper are given, and the bifurcation diagram and Lyapunov exponential spectrum are also analyzed. Numerical simulations show that the proposed chaotic systems have the positive Lyapunov exponent, which indicates the accuracy of the proposed theory. Additionally, a Pseudo-Random Number Generator (PRNG) is
also designed based on the given new chaotic system. Using SP800-22 test suit, the results show that the output sequence of PRNG has good pseudorandom. Finally, as an application of the PRNG, an image encryption algorithm is given. The proposed encryption scheme is highly secure Key space of 2⁷⁴⁷ and can resist against the statistical and exhaustive attacks based on the experimental results.

For personalized search based on location service, the trusted third-party server and peer node are used as the main method for privacy preserving. However, entirely trusted third-party server or peer node does not exist in real life. In order to address this problem, a method of privacy preserving on the location of mobile
users is proposed when using personalized search. The method is used to convert the user’s location information into distance information and generate the user model according to the user’s query type, forming a query matrix with user location information, then the matrix is used to encrypt the user’s query and conceal the user information in the query matrix. Finally, according to the calculation of the security inner product, the K file with the highest relevance score is returned to the user. It is evident from the security analysis that the proposed method can effectively protect the user’s query privacy and location privacy. The analysis and experimental results show that the proposed method can greatly shorten the time of index construction and reduce the communication overhead. While providing users with location based personalized search results, the method is able to remedy the defects of small-screen mobile devices.

In order to improve the energy efficiency and reliability of Wireless Body Area Networks (WBANs), this paper takes full consideration of characteristics of WBANs, such as limited resources, frequent channel quality fluctuations, heterogeneous data traffic, and proposes a Cross-Layer Optimization scheme based on link quality prediction (CLO algorithm). Through the loose coupling of physical layer, network layer and MAC layer, the transmission power of every sensor node is adaptively chosen, and the energy-efficient end-to-end routing is established. Simulation results show that the proposed scheme can improve the energy efficiency and transmission reliability of WBANs as compared with the existing single layer protocols.

For the problem of the production of complex operations, this paper uses workflow technology and takes the completion time as constraint, and proposes a Virtual Iterative Reduction Algorithm (VIRA) to achieve better production accuracy in the constraint completion time. By virtualizing tasks in mutual constraint into a virtual
node, the algorithm uses inverse iterative way to determine a path that completion time and production accuracy get balance. By comparison, the virtual iterative reduction algorithm can increase the production accuracy in the constraint completion time, and it is found to improve the accuracy of the algorithm by changing the deadline, the number of tasks and other parameters.

The existing hardware task scheduling algorithms describe task imperfectly and ignore the compactness of time dimension. The task downloading time is considered for improving the task attribute, and the 3D-resource model with the two dimensional resource of device and time is established, in order to abstract
the issue of task layout into a special three-dimensional space placement issue. With this model, it is concluded that the existing algorithms can not overcome the unpredictability of the task and the diversity of resource occupancy, leading low scheduling success rate and resource utilization rate. To solve the problem, a three
dimensional reconfigurable task scheduling algorithm called 3D_RTSA is proposed. A scheduling strategy based on task urgency and a layout strategy based on 3D fragmentation are designed and implemented. Compared with the other 4 algorithms, the results show that the scheduling success rate of 3D_RTSA is 3%,
21%, 28%, 35% higher than that of GC, Look-aheadest, SPSA and DTI algorithms under the condition of heavy load and small task C30, and the utilization ratio of resources is 5% and 18% higher than that of Look-aheadest and SPSA algorithm under the condition of light load and large task C50. Besides, the time complexity of the algorithm is not increased

A construction of aperiodic Inter-Group Complementary (IGC) sequence sets is proposed based on orthogonal matrices. The Zero Correlation Zone (ZCZ) length of the proposed aperiodic IGC sequence set can be chosen flexibly, and the parameters are optimal in terms of the corresponding theoretical bound. Moreover, binary and polyphase aperiodic IGC sequence sets can be obtained utilizing binary and polyphase orthogonal matrices. The presented IGC sequences can work in both synchronous and asynchronous Code Division Multiple Access (CDMA) communication systems.