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Table of Content

    30 March 2017, Volume 35 Issue 2
    Systematic Polar Coded Cooperation Based on Puncturing
    LI Kun, WU Shao-hua, GAO Xiang, ZHANG Qin-yu
    2017, 35(2):  139-148.  doi:10.3969/j.issn.0255-8297.2017.02.001
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    To design polar coded cooperation with high gain and flexible cooperation in a fading channel, systematic polar coded cooperation based on puncturing is investigated. It is shown that puncturing algorithms for non-systematic polar codes are also applicable to systematic polar codes. A quasi-uniform puncturing algorithm optimized by information bit refreezing is then applied to the systematic polar codes. Thus, systematic polar coded cooperation is proposed. Simulation results show that the proposed method significantly outperforms non-systematic polar coded cooperation. Taking the case in which the cooperation level is 50% as an example, 2.0~2.5 dB performance gain is achieved when the code length and code rate are 256 and 0.25, respectively.

    Implementation and Verification of Improved Concatenated Code Based on Software-Defined Radio
    GAO Shu-li, CHEN Wei-gang, YANG Jin-sheng
    2017, 35(2):  149-159.  doi:10.3969/j.issn.0255-8297.2017.02.002
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    A concatenated code combining an low-density parity-check (LDPC) code with a Reed-Solomon (RS) code, is designed based on the software-defined radio platform formed by universal software radio peripheral (USRP), which has compatible parameters with digital video broadcasting-terrestrial (DVB-T). Compared with the concatenated code combining a convolutional code with an RS code in DVB-T, the designed concatenated code obtains excellent error-correction performance, since LDPC performs better than the convolutional code, and the RS code can further eliminate error floor of the LDPC code. The designed code is implemented on a USRP platform. Its performance is tested in a wireless channel. The results show that high performance gain can be achieved by using the designed concatenated code as compared with the concatenated code in DVB-T.

    Precoding for Up-link Multi-user MIMO Relay Systems with Feedback Delay
    SU Jun-xu, CHEN Xiao-min, HU Xu-jun, ZHU Qiu-ming
    2017, 35(2):  160-170.  doi:10.3969/j.issn.0255-8297.2017.02.003
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    This paper proposes an optimal linear precoding scheme for uplink multi-user multiple-input multiple-output (MIMO) relay systems applicable to a channel with feedback delay and channel estimation errors. Limitations of the channel estimation method and the time delay of feedback link are considered. Design of transceiver is simplified as an optimal problem with precoding matrix variables, derived with a maximum power constraint at the relay station based on the minimum mean-square error (MMSE) criterion. The relay precoding matrix and decoding matrix are obtained, and the equalizer optimized with a linear iterative searching algorithm. Numerical simulation shows that the proposed scheme can effectively reduce the bit error rate of the system when channel feedback delay and estimation error exist.

    Applying Gate Replacement Technique Based on Double Weights to Mitigate Circuit Aging
    ZHU Jiong, YI Mao-xiang, ZHANG Yao, HU Lin-cong, LIU Xiao-hong, LIANG Hua-guo
    2017, 35(2):  171-180.  doi:10.3969/j.issn.0255-8297.2017.02.004
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    Negative bias temperature instability (NBTI) is a key factor affecting reliability of integrated circuits at the nanometer level. The NBTI effects increase transistor threshold voltage, cause aging of the circuit, and result in the circuit timing violations. To mitigate the NBTI effects of the circuit, we define delay weight and topology weight to identify critical gates more precisely. We also consider the case that the fan-in gate of a critical gate is INV. We take it as NAND1, and use NAND2 to replace INV. Thus the critical gates can be better protected. Experiments on ISCAS85 benchmark circuits based on a 45 nm transistor model show that, when the circuit timing margin is 5%, and the gate replacement technique based on double weights is used, the average delay improvement is 38.29% without considering replacement of INV. The average delay improvement is increased to 60.66% when considering INV replacement.

    Screening of SAHS Snore Based on ERB Correlation Dimension
    HOU Li-min, SHI Dan, LIU Huan-cheng, ZHANG Wei-tao
    2017, 35(2):  181-192.  doi:10.3969/j.issn.0255-8297.2017.02.005
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    This paper proposes a method for screening sleep apnea hypopnea syndrome (SAHS) by recording snore sound. Based on the equivalent rectangular bandwidth (ERB) scale used in psychoacoustics, the ERB correlation dimension (ECD) of snore is used to analyze and classify snores of different severity levels. For the training group, snore episodes were manually segmented and ECD features of snores were extracted to establish a Gaussian mixture model (GMM). The nocturnal snoring sound of the test group was validated to detect SAHS snores. The apnea hypopnea index (AHI) was estimated, to determine severity of SAHS. AHI is an average number of apneic events per hour of sleep. Compared with the polysomnography diagnosis that is a gold-standard, accuracy of SAHS severity reached 90%. The proposed method is useful in accessory examination of SAHS severity and for home uses.

    Euclidean Double Bits Embedding Hashing for Image Retrieval
    LI Lei, CEN Yi-gang, ZHAO Rui-zhen, CUI Li-hong, WANG Yan-hong
    2017, 35(2):  193-206.  doi:10.3969/j.issn.0255-8297.2017.02.006
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    We propose a double-bit embedding hashing method based on the Euclidean distance (DBE-E). Euclidean distance is used to measure similarity between the binary hash codes to better preserve similarity relations of the original feature space and improve retrieval precision. To speed computation, bit operation is used to calculate the Euclidean distance between the hash codes. It is 400 times faster than the traditional calculation method of the Euclidean distance for double-bit embedding of 64-bit hash code. Experiments on three image data sets show that the proposed method produces better results than other popular quantization strategies of hashing.

    Blind Equalization with Adaptive Variable Step Sizes Based on Parallel Laguerre Filter
    CUI Lin, YANG Jun-an, WANG Wei, LIU Hui
    2017, 35(2):  207-216.  doi:10.3969/j.issn.0255-8297.2017.02.007
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    A blind equalization algorithm with adaptive variable step sizes based on parallel Laguerre filter is proposed to overcome problems such as long tap coefficients, and high bit error rate (BER) caused by deep fading channels. By analyzing existing filter structures and blind equalization algorithms, the proposed algorithm replaces traditional tapped delay with Laguerre sequence to make tap coefficients shorter. Meanwhile, convergence is accelerated by using a decision-directed algorithm and a fractionally spaced structure. Since the step size has a great effect on convergence speed and residual error, different algorithms with variable step sizes are compared. Based on the comparison, a revised equalization algorithm structure is devised to achieve the most suitable step sizes for high-speed common data link (CDL). Compared with traditional blind equalization algorithms, experimental results show that the proposed method improves equalization performance and reduces BERs remarkably.

    Building Facade Reconstruction on Sparse LiDAR Data Region
    LIU Ya-wen, QIN Su-shun
    2017, 35(2):  217-225.  doi:10.3969/j.issn.0255-8297.2017.02.008
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    A building facade is composed of regular and irregular geometric structures. When the prior or extracted rules of facade structure are used to reconstruct the sparse data area, unreasonable reconstructed geometric structures will appear. This paper presents a method for building façade reconstruction on LiDAR data sparse region by combining rule inference and laser data verification. Building facade reconstruction is first introduced, including initial model reconstruction from LiDAR data and refinement combining LiDAR data and images. The reconstruction method is discussed for data sparse region with a focus based on an analysis of façade regularity, prediction of missing geometry structures and verification with point cloud data. Experiments show that the method can effectively detect unreasonable reconstruction and improve reliability of facade reconstruction based on the data sparse region.

    Data Stream Ensemble Classification Based on Classifier Confidence
    LIU San-min, LIU Tao, WANG Zhong-qun, XIU Yu, LIU Yu-xia, MENG Chao
    2017, 35(2):  226-232.  doi:10.3969/j.issn.0255-8297.2017.02.009
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    A weight computation policy based on confidence is presented to deal with the problem in the sub-classifier's weight in dynamic data stream ensemble classification. The policy fully considers influence of the sample on the weight of the sub-classifier. Uncertainty of the prediction result is described by information entropy, and relationship between the classifier confidence and the samples established. Thus, the computation method of classifier's confidence is defined. According to the requirements of dynamic data stream classification and traits of concept drift, a dynamic weight ensemble model is built by batch learning and time policy. Theoretical analysis and experimental results show feasibility of the presented schema, which is better than traditional methods.

    Multi-candidate Set of Generalized Orthogonal Matching Pursuit Algorithm
    TIAN Jin-peng, LIU Xiao-juan, LIU Yan-ping, XUE Ying, ZHENG Guo-xin
    2017, 35(2):  233-243.  doi:10.3969/j.issn.0255-8297.2017.02.010
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    A multi-candidate set of generalized orthogonal matching pursuit algorithm is proposed to improve precision of greedy algorithms for compressed sensing. Multiple atoms are chosen as multiple candidates based on correlation of the inner product of observation matrix and residual. In the iteration, the multiple atoms are added to the multiple candidate sets, resulting in fast convergence of the algorithm. The candidate set with the smallest residuals is chosen as the final support set so that the sparse signal is exactly rebuild. Compared with other algorithms, experimental results show that the proposed algorithm has better recovery performance and lower recovery complexity.

    Steepest Approaching Method for Tracking Desired Thrust Vectoring of Rotor UAVs
    DENG Shi-qian, CHENG Wan-sheng, WANG Kai
    2017, 35(2):  244-256.  doi:10.3969/j.issn.0255-8297.2017.02.011
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    As for the trajectory tracking task of rotor UAVs, this paper proposes a fast approaching method based on the equivalent rotation vector of quaternion, to be used to optimize the control mode of trajectory tracking. The process is described as follows:when a thrust vectoring target is generated in the position control loop, the minimum rotation vector and minimum attitude change quaternion can be defined with this method. The desired attitude quaternion is then obtained, and provided to the attitude control loop to realize fast approaching to the desired thrust vectoring. Results of simulation and flight control system tests show that the proposed method enables thrust vectoring to track the target vector with an optimal path. Meanwhile, it can decrease the UAVs' attitude variation and tracking time. A trajectory tracking control solution is also designed by using the steepest approach method. Compared with other solutions without optimization, the solution given in this paper requires less computation. It is especially suitable for applications with low cost embedded controllers.

    Adaptive Robust Control for Uncertain Non-affine Systems with State and Input Constraints
    CHEN Long-sheng, WANG Qi
    2017, 35(2):  257-274.  doi:10.3969/j.issn.0255-8297.2017.02.012
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    Adaptive robust universal back-stepping control is presented for a class of uncertain non-affine systems with state and input constraints. The non-affine system is transformed to a time-varying system with a linear structure using the mean value theorem. The interval of time-varying uncertain parameters is calculated by considering all constraints. To handle the state constraints, a nonlinear mapping technique that maps the constrained states to a real number set is developed. Furthermore, bounded time-varying parameters and external disturbance are estimated using adaptive algorithms with projection. The estimation error is compensated by using a robust feedback technique. The controller is designed by combining back-stepping with a hyperbolic tangent function and a Nussbaum function. It can deal with the problems of input saturation and possible controller singularity caused by unknown control direction. Based on the Lyapunov stability theorem and the decoupled back-stepping method, semi-global stability of the close-loop system is proved. Simulation results show feasibility and validity of the proposed control schemes.