Table of Content

30 January 2016, Volume 34 Issue 1

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Communication Engineering

Pilot Design Based on Pseudo-random Code in Massive MIMO System

FANG Xin, ZHANG Jian-feng, CAO Hai-yan, YING Na

2016, 34(1):  1-11.  doi:10.3969/j.issn.0255-8297.2016.01.001

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To deal with pilot contamination in massive MIMO systems, an efficient pilot design scheme is proposed. Different pseudo-random codes are assigned to different cells, all using the same set of orthogonal pilots. These codes are used to scramble the user pilot in each cell to get a transmission pilot. Mean square error (MSE) performance of expected channel estimation is derived and analyzed. Simulation results show that the channel estimation performance can be effectively improved when a proper pseudo-random code is chosen with the proposed pilot design method. It can greatly enhance the downlink performance in all cells.

Null Broadening Wideband Beamforming for SDL Based Array

ZHANG Wei, XU Lin, XU Quan-xin, WANG Yong

2016, 34(1):  12-21.  doi:10.3969/j.issn.0255-8297.2016.01.002

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Traditional adaptive wideband beamforming is difficult to be implemented with hardware, and has narrow null width in direction of interference. To deal with the problem, a novel null broadening wideband beamforming algorithm based on spatial response variation (SRV) constraint is proposed. Tapped delay-lines based systems are replaced with a structure based on sensor delay-lines (SDL). At the reference frequency, the beam response in the direction of interference is limited by using a maximum constraint. An SRV constraint based algorithm is used to broaden the region of nulls. An optimal weight vector is obtained using a convex optimization tool. Simulation results show that, with the proposed algorithm, null broadening and constant beam width can be realized at the same time of wideband beamforming. When null width is set to 10° and null depth is -30 dB, a measured null width of 14.7° can be obtained, and the system has a high output signal to interference and noise ratio (SINR).

Impact of Modulation Rate on Energy Efficiency of Amplify-and-Forward Relay Transmission Links

CHEN Fang-fang, WANG Tao

2016, 34(1):  22-29.  doi:10.3969/j.issn.0255-8297.2016.01.003

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The influence of modulation rate on energy efficiency (EE) for a source-relayterminal communication link using the amplify-and-forward (AF) protocol and MQAM is studied given a prescribed error rate (BER). Transmission power consumption is calculated. The total power consumption is obtained when the circuit power consumption is taken into account. An expression of EE is derived, and the influence of modulation rate on EE studied. Simulation results show that, with the modulation rate increasing, energy efficiency increases first, and then decreases.

Joint Subcarrier Suppression and Relay Selection for Two-Way OFDM Relaying System with PLNC

SHEN Xian-li, XIE Wei, XU You-yun, XU Kui, ZHANG Dong-mei

2016, 34(1):  30-41.  doi:10.3969/j.issn.0255-8297.2016.01.004

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This paper deals with the joint subcarrier suppression and relay selection (JSSRS) problem in two-way orthogonal frequency division multiplexing (OFDM) relaying system based on physical layer network coding (PLNC) with the decode-and-forward protocol over a multipath Rayleigh fading channel. Two JSSRS schemes are proposed:JSSRS with a fixed threshold (FT-J) and JSSRS with a fixed number of subcarriers (FNS-J). In a two-way information exchange process, FT-J suppresses subcarriers by keeping the suppression threshold invariant, and FNS-J suppresses subcarriers by keeping the number of suppressed subcarriers invariant. In other words, FNS-J keeps the number of active subcarriers constant and the suppression threshold value varying. Simulation results show that FT-J and FNS-J can improve efficiency and enhance reliability of a two-way OFDM relaying system based on PLNC as compared with traditional subcarrier suppression schemes.

Signal and Information Processing

Comparison of Complex and Real Wavelet Transforms in Islanding Detection

FANG Xiao-mei, LUO Xiao-shu, JIANG Pin-qun, SONG Shu-xiang, LIAO Zhi-xian

2016, 34(1):  42-48.  doi:10.3969/j.issn.0255-8297.2016.01.005

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Islanding detection is an important issue in grid-connection of a distributed photovoltaic system. The paper compares complex and real wavelet transforms used in islanding detection. Islanding is judged by extracting and analyzing changes in the amplitude and phase of wavelet transform coefficients of the voltage at common coupling points. Simulation results show that the islanding detection method based on complex wavelet transform is more effective than that based on real wavelet transform. The complex wavelet method also solves the problem of tedious layering of characteristic signal and complicated threshold selection encountered in the real wavelet based method.

A Lattice Boltzmann Model with Statistic Region Information for Image Segmentation

WEN Jun-ling, YAN Zhuang-zhi, JIANG Jie-hui

2016, 34(1):  49-57.  doi:10.3969/j.issn.0255-8297.2016.01.006

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The lattice Boltzmann (LB) model has advantages of simple programming and faster operation, but for images with low contrast and noise, segmentation may fail. This paper proposes a novel LB model using local statistical region information. As the method can enhance contrast of the object and background, and reduce noise, it provides improved delineation accuracy. To verify effectiveness of the model, comparison experiments among the existing LB model, level set models and the proposed model are made, using real magnetic resonance (MR) images. Dice coefficient and Hausdorf distance are used as the measurement index. The results show that the proposed model produces segmentation results with precision 10 times better than the existing LB method. In addition, the computing speed is 3 times faster than level set models.

Image Segmentation Based on Differential Evolution and 2-D Entropy

ZHANG Li, YE Zhi-wei, WANG Ming-wei

2016, 34(1):  58-66.  doi:10.3969/j.issn.0255-8297.2016.01.007

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Image segmentation based on 2-D entropy uses local space information of images and has better segmentation results than 1-D entropy based methods, but the computation efficiency is low. Commonly used optimization algorithms such as genetic algorithm and particle swarm optimization can improve efficiency of 2-D entropy thresholding, but cannot ensure the optimal threshold values. In the present paper, an image segmentation approach based on differential evolution and 2-D entropy is proposed to avoid drawbacks of the above methods. A local search strategy is used to further improve precision of the optimal threshold. Experimental results indicate that the proposed method is robust, and can acquire the optimal threshold values with much faster running speed than the primary 2-D entropy thresholding method.

Urban Boundary Extraction by Fusing of DMSP-OLS and Landsat Images

WU Xiao-yu, ZHANG Peng-lin

2016, 34(1):  67-74.  doi:10.3969/j.issn.0255-8297.2016.01.008

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This paper proposes a fusion approach to detect the urban boundary. Two boundaries were obtained using the DMSP-OLS night light data and Landsat image data, respectively. A proper weight was chosen to fuse these two boundaries obtained from different data sets so that reliability of the final results was improved. Experimental results have shown validity of the proposed approach.

Lower Mekong River Flood Area Monitored by Multi-source Remote Sensing

LI Tong, ZHANG Li, SHEN Qian, ZHANG Bing-hua

2016, 34(1):  75-83.  doi:10.3969/j.issn.0255-8297.2016.01.009

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Remote sensing monitoring of submerged areas is an effective method to measure flooding, directly indicating severity of the disaster. This study uses MODIS, FY3A MERSI, HJ1A/B CCD and Landsat TM data to monitor time series of the flood inundation area in the Mekong River downstream in 2011, based on an optimal algorithm obtained from experiments. We evaluate the flood area with different types of vegetation using the MODIS land cover data. From the results the following recommendations are made. NWDI is the best algorithm for HJ1A/B CCD and FY3A MERSI. NDVI is more suitable for Landsat TM and MODIS data compared with other three algorithms. Cambodia and the Mekong Delta region had serious flooding disaster in October 2011, with the inundated area 6.5 times larger than the normal area. The Tonle Sap River basin was the worstaffected area, with the river widened by about 40 times. At the beginning of the flood, a large amount of water flowed into Tonle Sap Lake, which played an important role in storing flood water. Therefore, by combining advantages of multi-source remote sensing satellite data to monitor changes in the floods, we can acquire more detailed information and improve efficiency of flood detection.

Object-Based Building Extraction from Airborne LiDAR Data

FAN Jing-jing, ZHANG Hua, HAO Ming

2016, 34(1):  84-94.  doi:10.3969/j.issn.0255-8297.2016.01.010

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Based on airborne LiDAR data, an object-based method for building extraction with coarse-fine accuracies is proposed. A normalized digital surface model (nDSM) and the normalized difference (ND) are extracted from the LiDAR data. Special edge echo points are removed from the ND data using a morphological operator. Taking into consideration height and penetrability of the buildings, coarse profile of the buildings are extracted from ND and nDSM data using a threshold segmentation algorithm. A multi-resolution segmentation algorithm is then used to segment the candidate buildings by integrating intensity, and the nDSM/ND data. The segmentation result is further optimized by merging the adjacent objects with smaller brightness difference. Finally intensive buildings are extracted based on spectral and geometrical characteristics, and the spatial relations of objects. Experiment results show that the proposed method can obtain buildings with high precision, and provides a means for building extraction from airborne LiDAR data.

Prediction of Suspension Pipeline Strain by GM(1,1)-ARMA Model Based on Wavelet Transform

HUAN Ying, LAN Hui-qing, LIN Nan, ZHANG Ping

2016, 34(1):  95-105.  doi:10.3969/j.issn.0255-8297.2016.01.011

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When using an ARMA model to predict monitoring data of bridges, difference processing causes some data lose. To improve prediction accuracy, this paper makes use of the advantages of wavelet analysis, i.e., no information is lost after wavelet transform. The time series with a clear trend are divided into two parts. The low-frequency part representing strain trend is modeled using GM(1,1), and the high-frequency part representing random disturbance using ARMA. The predicted value is then obtained by combining the two parts. Validation is made with the strain data acquired from an on-line monitoring system on a Yellow River suspension bridge. The results show that prediction accuracy of the combined GM(1,1)-ARMA model is higher than the traditional ARMA. The method is applicable to early warning of similar bridges.

Nondestructive Inspection of Steel Bridge Based on Infrared Thermal Imaging

YAN Yuan, ZOU Lan-lin, ZHOU Xing-lin

2016, 34(1):  106-114.  doi:10.3969/j.issn.0255-8297.2016.01.012

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A new inspection method is proposed to detect fatigue crack on steel bridges based on stress concentration features. The relationship between stress and temperature of the component is built theoretically. Fatigue cracks can be located by calculating distortion stress based on detection of temperature distortion of the component using an infrared thermal imager. As an example, consider a plate with a hole. Relationship between stress and temperature of the hole-edge spots is studied under cycle loads. The results show that the temperature of left/right spots decrease and top/bottom spots increase when t=0.05 s, and the temperature of left/right spots increase and top/bottom spots decrease when t=0.15 s. These agree with the theoretical result, and the mode test results show feasibility of the proposed method.