Parallel Programming Design of BPSK Signal Demodulation Based on CUDA

Realizing digital signal demodulation on the general computer is an important research direction in the field of signal processing in recent years. In this paper, the algorithm of BPSK signal demodulation which has high real-time requirements is researched on the general computer. According to the characteristics of “CPU + GPU” heterogeneous computing, the parallel computation model of digital communication is put forward, and BPSK signal demodulation is realized on CUDA platform. Test results show that the computing time ratio of 1:1.7, when the bit error rate can be achieved 10?5.

Parallel Processing Design for LTE PUSCH Demodulation and Decoding Based on Multi-Core Processor

The Long Term Evolution (LTE) system imposes high requirements for dispatching delay.Moreover,very large air interface rate of LTE requires good processing capability for the devices processing the baseband signals.Consequently,the single-core processor cannot meet the requirements of LTE system.This paper analyzes how to use multi-core processors to achieve parallel processing of uplink demodulation and decoding in LTE systems and designs an approach to parallel processing.The test results prove that this approach works quite well.

Research on the Comprehensive Demodulation of Gear Tooth Crack Early Fault

The component of gear vibration signal is very complex,when a localized tooth defect such as a tooth crack is pre- sent,the engagement of the cracked tooth will induce an impulsive change with comparatively low energy to the gear mesh signal and the background noise.This paper presents a new comprehensive demodulation method which combined with amplitude envelop demodulation and phase demodulation to extract gear crack early fault.A mathematical model of gear vibration signal contain crack fault is put forward.Simulation results based on this model show that the new comprehensive demodulation method is more effective in finding fault and judging fault level then conventional single amplitude demodulation at present.

Study on the Optimized Demodulation and Decoding of the BICM-ID system coded with LDPC

The demodulation and decoding solution commonly used in the bit interleaving code modulation and the LDPC coded demodulation and decoding system of the iterative decoding （BICM-ID） is to report the soft information output from the decoder of the receiver to the demodulator as priori information for completing the decoding. However, this will give rise to the reduction of the minimum Euclidean distances between codes, so that the performances of the system decline under non-fading Gaussian channel. According to this problem, an optimized iterative demodulation decoding solution is proposed and also is analyzed using simulation. The result shows that this solution can improve the demodulation and decoding performances of LDPC coded modulation and demodulation system.

A new method of demodulating the digital frequency modulation signals

A new method of estimating the frequency-known signals from the strong background noise was presented first. Then the new method was used in the demodulation of the digital frequency modulation (FSK) signals. The new demodulation method can complete the demodulation of the FSK signals only with the carrier frequency and without any carrier phase information. The simulation results show that the performance of anti-noise of the new method is better than that of the incoherent demodulation method and the fluctuation of the carrier phase has little effect on the new method. So the new demodulation method has a fine prospect in the practical applications.

Improved multi-scale inverse bottleneck residual network based on triplet parallel attention for apple leaf disease identification

Accurate diagnosis of apple leaf diseases is crucial for improving the quality of apple production and promoting the development of the apple industry. However, apple leaf diseases do not differ significantly from image texture and structural information. The difficulties in disease feature extraction in complex backgrounds slow the related research progress. To address the problems, this paper proposes an improved multi-scale inverse bottleneck residual network model based on a triplet parallel attention mechanism, which is built upon ResNet-50, while improving and combining the inception module and ResNext inverse bottleneck blocks, to recognize seven types of apple leaf(including six diseases of alternaria leaf spot, brown spot, grey spot, mosaic, rust, scab, and one healthy). First, the 3×3 convolutions in some of the residual modules are replaced by multi-scale residual convolutions, the convolution kernels of different sizes contained in each branch of the multi-scale convolution are applied to extract feature maps of different sizes, and the outputs of these branches are multi-scale fused by summing to enrich the output features of the images. Second, the global layer-wise dynamic coordinated inverse bottleneck structure is used to reduce the network feature loss. The inverse bottleneck structure makes the image information less lossy when transforming from different dimensional feature spaces. The fusion of multi-scale and layer-wise dynamic coordinated inverse bottlenecks makes the model effectively balances computational efficiency and feature representation capability, and more robust with a combination of horizontal and vertical features in the fine identification of apple leaf diseases. Finally, after each improved module, a triplet parallel attention module is integrated with cross-dimensional interactions among channels through rotations and residual transformations, which improves the parallel search efficiency of important features and the recognition rate of the network with relatively small computational costs while the dimensional dependencies are improved. To verify the validity of the model in this paper, we uniformly enhance apple leaf disease images screened from the public data sets of Plant Village, Baidu Flying Paddle, and the Internet. The final processed image count is 14,000. The ablation study, pre-processing comparison, and method comparison are conducted on the processed datasets. The experimental results demonstrate that the proposed method reaches 98.73% accuracy on the adopted datasets, which is 1.82% higher than the classical ResNet-50 model, and 0.29% better than the apple leaf disease datasets before preprocessing. It also achieves competitive results in apple leaf disease identification compared to some state-ofthe-art methods.

High Speed VCSEL-Based Parallel Optical Transmission Modules

Design and fabrication of a parallel optical transmitter are reported. The optimized 12 channel parallel optical transmitter,with each channel＇s data rate up to 3Gbit/s,is designed, assembled, and measured. A top-emitting 850nm vertical cavity surface emitting laser（VCSEL） array is adopted as the light source,and the VCSEL chip is directly wire bonded to a 12 channel driver IC. The outputs of the VCSEL array are directly butt coupled into a 12 channel fiber array. Small form factor pluggable （SFP） packaging technology is used in the module to support hot pluggable in application. The performance results of the module are demonstrated. At an operating current of 8mA, an eye diagram at 3Gbit/s is achieved with an optical output of more than 1mW.

30Gbit/s Parallel Optical Receiver Module

A 30Gbit/s receptor module is developed with a CMOS integrated receiver chip（IC） and a GaAs-based 1 × 12 photo detector array of PIN-type. Parallel technology is adopted in this module to realize a high-speed receiver module with medium speed devices. A high-speed printed circuit board（PCB） is designed and produced. The IC chip and the PD array are packaged on the PCB by chip-on-board technology. Flip chip alignment is used for the PD array accurately assembled on the module so that a plug-type optical port is built. Test results show that the module can receive parallel signals at 30Gbit/s. The sensitivity of the module is - 13.6dBm for 10^-13 BER.

STIFFNESS ANALYSIS OF THE MAIN MODULE FOR PARALLEL MACHINE TOOLS BY FINITE ELEMENT ANALYSIS

With the aid of commercial finite element analysis software package ANSYS,investigations are made on the contributions of main components to stiffness of the main module for parallel machine tools,and it is found that the frame is the main contributor.Then,influences of constraints,strut length and working ways of the main module have also been investigated.It can be concluded that when one of the main planes of the frame without linear drive unit is constrained,the largest whole stiffness can be acquired.And,the stiffness is much better when the main module is used in a vertical machine tool instead of a horizontal one.Finally,the principle of stiffness variation is summarized when the mobile platform reaches various positions within its working space and when various loads are applied.These achievements have provided critical instructions for the design of the main module for parallel machine tools.

BER Performance of Soft Decision Modulations Based on PCSS System

Recently,soft decision modulations become the highlight of parallel combinatory spread spectrum ( PCSS) system. Existing soft decision BPSK and APK modulations are given and compared in the thesis. In order to apply soft decision QPSK modulation based on PCSS system,the correlation of superposition PN sequences is discussed. A weighted summation algorithm is adopted in QPSK demodulation to recover the whole orthogonal correlation of the superposition sequences; meanwhile the bit error rate of weighting soft decision QPSK modulation is simulated. The simulation results show that the bit error rate performance of proposed soft decision QPSK modulation based on PCSS system is better than that of hard decision modulation. The method proposed can be widely adopted in engineering application.

Piecewise linear detection for direct superposition modulation

Considering high-order digital modulation schemes, the bottleneck in consumer products is the detector rather than the modulator. The complexity of the optimal a posteriori probability （APP） detector increases exponentially with respect to the number of modulated bits per data symbol. Thus, it is necessary to develop low-complexity detection algorithms with an APP-like performance, especially when performing iterative detection, for example in conjunction with bit interleaved coded modulation. We show that a special case of superposition modulation, dubbed Direct Superposition Modulation （DSM）, is particularly suitable for complexity reduction at the receiver side. As opposed to square QAM, DSM achieves capacity without active signal shaping. The main contribution is a low-cost detection algorithm for DSM, which enables iterative detection by taking a priori information into account. This algorithm exploits the approximate piecewise linear behavior of the soft outputs of an APP detector over the entire range of detector input values. A theoretical analysis and simulation results demonstrate that at least max-log APP performance can be reached, while the complexity is significantly reduced compared to classical APP detection.

Demodulator for Chaotic Secure Communication Based on Proportional-integral Feedback Design

A scheme of chaotic secure communication based on the parameter modulation and the inversion of a chaotic dynamical system is analyzed. According to this scheme, information signal is modulated by a bifurcation parameter of the transmitter, which is in chaotic state. In the receiver, a proportional integral feedback demodulator is used to demodulate the information signal, which only uses the available synchronizing error as well as stateness of receiver. The purpose of this demodulator is proposed to overcome the influence of differentiation operation, nonlinear part and singularities in chaotic system. Numerical simulation is proposed to show the effectiveness of this demodulator.

High efficiency spreading spectrum modulation using double orthogonal complex sequences

This paper presents a novel scheme of high efficiency spreading spectrum modulation using double orthogonal complex sequences （DoCS）. In this scheme, input data bit-stream is split into many groups with length M. Each group is then mapped into a word of width M and then utihzed to select one sequence from 2u-2 DoCS sequences each with length L. After that, the selected sequence is modulated on carrier in quadrature phase shift keying （QPSK） mode. In addition, a new method named forward phase correction （FPC） is put forward for carrier recovery. Theoretical analysis and bit-error-ratio（BER） experiment results indicate that the proposed scheme has better performance than the conventional direct sequence spread spectrum（DSSS） scheme both in bandwidth efficiency and processing gain of the receiver.

Symbol detection based on Voronoi surfaces with emphasis on superposition modulation

A challenging task when applying high-order digital modulation schemes is the complexity of the detector. Particularly, the complexity of the optimal a posteriori probability （APP） detector increases exponentially with respect to the number of bits per data symbol. This statement is also true for the Max-Log-APP detector, which is a common simplification of the APP detector. Thus it is important to design new detection algorithms which combine a sufficient performance with low complexity. In this contribution, a detection algorithm for two- dimensional digital modulation schemes which cannot be split-up into real and imaginary parts （like phase shift keying and phase-shifted snperposition modulation （PSM）） is proposed with emphasis on PSM with equal power allocation. This algorithm exploits the relationship between Max-Log-APP detection and a Voronoi diagram to determine planar surfaces of the soft outputs over the entire range of detector input values. As opposed to state-of-the-art detectors based on Voronoi surfaces, a priori information is taken into account, enabling iterative processing. Since the algorithm achieves Max-Log-APP performance, even in the presence of a priori information, this implies a great potential for complexity reduction compared to the classical APP detection.

基于Labview的分布式光纤光栅信号解调技术研究

分布式光纤光栅信号解调中受到通信信道的码间干扰导致信道均衡性不好,提出基于Labview的分布式光纤光栅信号解调技术。采用连续时间采样技术构建分布式光纤光栅信号采集模型,对信号输出的功率谱密度特征进行相位调制处理,在离散的维纳模型下提取分布式光纤光栅信号的偏移中心频率和单边带功率谱密度特征信息,通过Labview的调制解调技术实现对信号的调制解调处理,最后采用抗相位噪声干扰的星座图分析方法分析光纤光栅信号解调的抗干扰性和误码抑制能力。仿真结果得知,该方法进行分布式光纤光栅信号解调的抗干扰性较好,提高了信道的频谱带宽,降低了频率中心偏移,传输误码率低于0.05%,信号的传输延时维持在30μs左右,具有较强的应用性。

串联补偿无线电能传输变换器载波通信研究

无线电能传输(WPT)负载电压、电流等状态信息需送到原边进行闭环控制和监控处理,副边到原边的通信至关重要。首先介绍了电容调制的WPT系统拓扑和工作原理,电容调制与否使得系统拓扑发生变化,未调制时原、副边拓扑为串/串(S/S)结构;调制时原、副边拓扑为串/串并(S/SP)结构。调制电容的投切形成两种状态来传递通信信息,且该状态变化可以反映到原边电流上。其次采用幅移键控(ASK)解调电路对原边电流处理即可还原通信信号,为提高解调精度和抗干扰能力,对ASK解调电路进行改进。最后通过仿真和实验验证了方案的有效性,实验结果表明,该系统在100 W的运行功率、2~5 kHz的通信频率下,可以精准完成副边到原边的通信。

双模三维索引调制差分混沌移位键控系统的设计及性能分析

针对传统差分混沌移位键控系统速率低、误码性能差的问题,提出了一种双模三维索引调制差分混沌移位键控系统。该系统利用时隙、正交码和顺序索引,在选中与未选中的时隙上均传输信息比特。在接收端,通过采用降噪技术,减小了噪声的方差,提升了系统误码性能。推导了在加性白高斯噪声信道和多径瑞利衰落信道下的比特差错率公式。仿真结果显示,与相似的混沌键控系统相比,所提系统具备更高的数据速率和更为优越的误码性能。

基于Simulink的2PSK调制与解调系统的仿真分析

分析2PSK调制和解调的原理,采用Matlab环境下的Simulink仿真工具箱实现2PSK调制及解调系统的仿真建模与分析。仿真实验表明,仿真结果和理论分析内容一致,验证了仿真模型的正确性。该方法有助于相关研究者直观地理解相移调制与解调系统的组成及工作原理,对实际工程应用也有一定的借鉴作用。

用于新型符号的频偏补偿和解调的算法与电路

为提高传统脉冲位置调制(pulse position modulation,PPM)符号的频谱效率,提出了一种新型码片内4-PPM符号调制方法,在实现1 Gbit/s通信速率的同时,又大大减少所需频谱资源。可在解调时,该符号调制的误码率性能受到发射端时钟和接收端本地时钟之间的频率偏移的极大影响。针对此问题,又提出了一种在模拟域对该符号进行频偏补偿,并实现符号同步和高速数据解调的算法与电路。该电路系统通过消除接收数据和本地时钟的初始相差、提取两者的频偏信息、周期性改变本地时钟的瞬时相位3步实现频偏补偿,并同时在第3步利用本地时钟对接收数据进行解调。为提高相位插值器(phase interpolator,PI)的线性度,本文将延迟锁定环与PI相结合。在2π的插值范围内,实现插值区间32个,插值步长992个,分辨率2.016 ps,最大差分非线性(differential nonlinearity,DNL)0.183°,最大积分非线性(integral nonlinearity,INL)0.325°。此外,本文提出的相位控制算法有效避免了由电流毛刺所引起的输出相位突变。电路基于UMC 40 nm CMOS RF LP工艺进行设计与仿真。仿真结果表明:本文所提出的算法与电路,在典型工艺角下,将接收数据和本地时钟间的50×10^(-6)频率偏差度降至1.03×10^(-6),频偏补偿准确度达到97.94%,并实现1 Gbit/s的解调速率。该方法对高速PPM数据同步与解调具有良好的工程应用价值。