Rapid prototyping of MIMO‐OFDM based on parity bit selected and permutation spreading

In this paper, a novel MIMO‐OFDM transmission scheme is developed to effectively enable multi‐access by joint code design across multiple antennas, subcarriers, OFDM frames, and users. It achieves better spectrum efficiency while improving bit error rate performance. The proposed scheme uses either parity bit selected or permutation techniques to assign spreading codes at the transmitter side. As a result, the detection at the receiver is greatly improved because of the fact that identifying the spreading code(s) directly yields the transmitted data symbols. The paper also investigates the field‐programmable gate array implementation of the proposed algorithms; optimization techniques are proposed to reduce area, power, and time. These techniques include a pipelined architecture for inverse FFT/FFT blocks, an efficient low complexity algorithm for despreading based on counters and comparators and an optimized architecture for complex matrix inversion using Gauss–Jordan elimination (GJ‐elimination). Finally, the fixed‐point optimized field‐programmable gate array architecture for MIMO‐OFDM transceiver is developed, where the maximum allowed performance loss because of quantization is defined, the tradeoffs between BER performance and area reduction are investigated. Copyright © 2015 John Wiley & Sons, Ltd.     

Reducing the power envelope fluctuation of OFDM systems using side information supported amplitude clipping approach

OFDM is an important modulation technique currently in development in the field of communications systems. OFDM signals can combat multipath propagation and fading channels and can support large data rates. However, OFDM systems are multicarrier systems and experience problems due to the required summation of sinusoids when the in‐phase subcarriers are combined, which produces high power peaks. The large power envelope fluctuations that occur at the output cause in‐band and out‐of‐band distortions that result in degraded BER performance. The literature contains many qualified approaches to resolving the peak‐to‐average power ratio problem, including selected mapping, partial transmit sequence, and amplitude clipping techniques. The simplest technique is the amplitude clipping technique, and the selected mapping and partial transmit sequence techniques are excessively complicated for real‐time implementation. In this paper, we suggest a modification to the amplitude clipping method to produce a novel clipping technique called the side information supported amplitude clipping (SI‐SAC) method. The SI‐SAC technique involves sending certain bits of extra information so that the receiver can recover all of the clipped data. The SI‐SAC technique does not add computational complexity to the system, and simulation results show that the proposed method is superior to the conventional method. The peak‐to‐average power ratio was reduced by ≈2.5 dB, and the magnitude of the mean squared error vector is the same as that of the original signal that is not clipped. In contrast, the conventional amplitude clipping method produces a mean squared error vector with a large magnitude. Copyright © 2012 John Wiley & Sons, Ltd.     

Meeting mobile's demands with multicarrier systems

With the increasing requirements for future wireless applications, OFDM, MC-CDMA, and MC-DS-CDMA have all been considered for 4G wireless systems. These systems have the ability to incorporate very large band widths without sacrificing equalization complexity. The long symbol duration is effective at mitigating ISI, and adaptive modulation or frequency diversity can be used to provide protection against destructive fades. The benefit of MC CDMA is that it experiences frequency diversity because each bit is transmitted over several independently faded subcarriers. If some subcarriers experience destructive fades, diversity combining can be used at the receiver to recover the data. This improves the BER performance over OFDM, and this improvement is more significant as the number of subcarriers is increased. The draw back of MC-CDMA is that it may experience high levels of multiuser access interference (MAI) when the channel is heavily loaded. This occurs because each chip of the PN sequence experiences independent fading, which tends to destroy the orthogonality between spreading sequences. This increases the MAI and degrades the BER performance. Although OFDM, MC-CDMA, and MC-DS-CDMA signals experience a high PAPR, synchronization issues, and ICI, the benefits greatly outweigh these disadvantages.     

Levy噪声中EMD降噪的随机共振研究

经验模态分解(empirical mode decomposition,EMD)降低噪声的同时也削弱信号能量,并会产生虚假信号,导致信号检测存在缺陷,针对这一问题,提出Levy噪声环境下经验模态分解随机共振检测方法。通过将含噪信号进行EMD分解,对分解后信号进行叠加取平均二次采样等处理方法,使其满足随机共振要求,利用自适应算法优化系统参数,进而使处理后信号能够在双稳系统中产生随机共振,达到精确检测的目的。理论分析及实验证明在Levy噪声下,此方法能实现同一特征指数下单频信号与多频信号检测,实验表明在单频信号信噪比为-28 dB情况下能有14 dB的提高,特征指数为1.8下多频信号5 Hz频谱幅值从311.8增加到724,10 Hz频谱幅值由138.9增加到143.2。此方法对在复杂噪声环境中降低剩余噪声能量同时,提高信号能量,减少虚假信号,相对于仅仅进行EMD分解无法判断信号成分,能更好的达到检测效果。     

减少OFDM信号峰均功率比的PTS方法研究

正交频分复用（OFDM）作为一种高速信息传输的技术，具有很好的抗多径干扰能力，但它的一个主要缺点是有很高的峰均功率比（PAPR），现在已有许多解决方案用来降低OFDM信号的峰均功率比。部分传输序列（PTS）的方法可以改善OFDM符号的峰均功率比的性能，它是一种很有效的方法。文章对PTS的方法进行描述，在传统的PTS方法基础上进行改进，提出了一种减小复杂度的方法。     

改进 CEEMDAN 算法的电机轴承振动信号降噪分析

为提高传统自适应噪声完备经验模态分解算法(CEEMDAN)对电机轴承故障特征信号的精确提取率,降低重构信号失 真,提出了一种改进自适应噪声完备经验模态分解算法。 首先利用传统 CEEMDAN 对原始信号初步分解,获得若干特征分量 (IMFs)和固有模态分量,将若干 IMFs 运用熵权法进行初步故障特征信号消噪和提取,对筛选后的 IMF 分量进行二次分解和二 次筛选,获得典型故障敏感信号,再运用 SG(Savitzky-Golay)平滑滤波进行信号重构,最终实现电机轴承信号降噪。 最后利用凯 斯西储大学轴承数据进行改进算法性能分析,结果表明该方法对电机轴承信号能够有效的进行信号降噪,其信噪比相比于原始 信号提高 2. 2 dB。     

降低电力线正交频分复用系统峰均比的方法

针对比例选择映射法的峰均功率比(peak-to-average power ratio,PAPR)高于传统选择映射方法的缺点,提出了一种改进方法。这种方法通过规定新的判决准则,将部分输入信号进行缩小运算,从而达到了进一步降低电力线通信正交频分复用(orthogonal frequency division multiplexing,OFDM)系统PAPR的目的。分析及仿真结果表明,在保证系统的误比特率(bit error rate,BER)性能的前提下,与原比例选择映射法相比,改进后的方法能够进一步降低系统的PAPR,它具有算法简单、发送效率高且易于与其他电力线通信信道降低PAPR的技术结合使用等特点,在电力线信道中具有较好的实用价值。     

Selectivity and sensitivity enhancement methods for high‐data‐rate super‐regenerative receiver

This paper describes selectivity and sensitivity performance evaluations and improvement methods for an on–off keying super‐regenerative (SR) receiver. A slope‐controlled quasi‐exponential quench waveform, generated by a low‐complexity PVT‐tolerant quench generator circuit, is proposed to increase data rate and reduce the receiver 3‐dB bandwidth, thereby preventing oscillation caused by out‐of‐band injected signals and improving the receiver selectivity. The SR receiver sensitivity is also enhanced by a noise‐canceling front‐end topology with single‐ended to differential (S2D) signal converter. To exemplify these techniques, we designed an SR receiver with the proposed front‐end and quench waveform generator in a 0.18‐μm CMOS technology. Theoretical analyses and circuit simulations show 30% and 65% reduction in 3‐dB bandwidth of the SR receiver at 25 Mbps data rate by employing the proposed quench signal compared with piecewise‐linear and trapezoidal quench waveforms, respectively. Performance of the proposed front‐end is evaluated by a fast bit‐error‐rate estimation procedure, based on circuit noise simulations and statistical analyses, without the need for time‐consuming transient‐noise simulations. Accuracy of the procedure has been verified by comparing its results with transient‐noise simulations. According to the estimated bit‐error‐rate curves, the noise‐canceling topology with S2D converter enhances the SR receiver sensitivity by 9 dB. Copyright © 2017 John Wiley & Sons, Ltd.     

基于毫米波传感器的呼吸检测与去噪方法研究

利用毫米波传感器测量较远人体目标的呼吸信号时,容易受到环境杂波的干扰,导致信号中含有较多噪声。因此提出了一种新的GA-VMD-WT去噪方法。方法针对呼吸信号的特点,借助排列熵设计适应度函数,采用GA算法优化VMD参数,以获得最优模态分量个数K和惩罚因子α,再用优化得到的VMD参数对噪声信号分解,然后对分解结果小波阈值去噪,最后重建得到去噪信号。该方法不仅避免了VMD分解时出现的过分解问题,并且仿真实验显示,与各传统的去噪算法相比较,信噪比分别提高了8.5025dB,7.6642dB,3.3637dB。实测信号实验结果表明,所提方法去噪效果好,可以保留更多有用信号的信息。     

中压电力线通信自适应OFDM系统背景噪声抑制技术研究

针对中压电力线通信自适应OFDM系统缺乏抗噪声干扰措施的问题,介绍了一种低复杂度的子空间迭代算法用以抑制背景噪声。该方法基于子空间理论来分解含噪OFDM信号的特征空间,并在信号失真最小的约束条件下,应用拉格朗日最优极值法来获得理想信号的最佳估计。针对经典子空间方法求特征值分解时的高计算量,该方法采用重复一维子空间迭代的办法来降低计算复杂度。构建了结合信噪比门限与注水原理的自适应OFDM系统,并仿真比较背景噪声抑制前后的系统性能。结果表明,该方法能够进一步改善误比特率性能,提高信噪比。应用该方案可优化自适应OFDM系统在PLC中的应用。     

Flexible Spectrum and Power Allocation for OFDM Unlicensed Wireless Systems

Future generations of communication systems will benefit from cognitive radio technology, which significantly improves the efficient usage of the finite radio spectrum resource. In this paper we present a wireless unlicensed system that successfully coexists with the licensed systems in the same spectrum range. The proposed unlicensed system determines the level of signals and noise in each frequency band and properly adjusts the spectrum and power allocations subject to rate constraints. It employs orthogonal frequency-division multiplexing (OFDM) modulation and distributes each transmitted bit energy over all the bands using a novel concept of bit spectrum patterns. A distributed optimization problem is formulated as a dynamic selection of spectrum patterns and power allocations that are better suited to the available spectrum range without degrading the licensed system performance. Bit spectrum patterns are designed based on a normalized gradient approach and the transmission powers are minimized for a predefined quality of service (QoS). At the optimal equilibrium point, the receiver that employs a conventional correlation operation with the replica of the transmitted signal will have the same efficiency as the minimum mean-squared error (MMSE) receiver in the presence of noise and licensed systems. Additionally, the proposed approach maximizes the unlicensed system capacity for the optimal spectrum and power allocations. The performance of the proposed algorithm is verified through simulations.      

OFDM系统减小PAPR的方法

OFDM(Orthogonal Frequency Division Multiplexing),中文含义为正交频分复用,它是一种多载波调制技术.由于具有良好的抗多径性能,适用于高速的数据传输,OFDM成为近年来人们研究的热点.但是,由于它存在峰平功率比(PAPR)较高的问题,限制了它在实际系统中的应用.本文从概率问题出发,提出了序列预处理的方法,它不在于降低信号幅度的最大值,而是降低信息序列中峰值出现的概率.经过仿真证明序列预处理的方法有良好的效果.     

改进自适应 CEEMD 方法在心电信号去噪中的应用

针对传统经验模式分解(EMD)方法存在的模式混淆问题,以及总体平均经验模式分解(EEMD)不具备完备性和计算量太大的缺陷,提出一种改进的自适应互补集合经验模式分解(CEEMD)方法。该方法在分析加噪准则的基础上,引入峰值误差(PE)作为加噪评价指标,来自适应确定最佳加噪幅值;然后利用原始信号的幅值标准差以及加入噪声的幅值标准差的比值系数,对不同信号自适应获取总体平均次数;最后将该方法运用到由美国麻省理工学院建立的MIT-BIH心电数据库中,很好地实现了对目标信号的去噪。实验表明,所提方法的平均信噪比(SNR)达到了19.249 7、均方根误差(RMSE)仅为0.047 3,平均平滑度指标R只有0.030 5。算法有效地去除了原始心电信号噪声,改善了信号的平滑度,提高了运算效率。     

基于ICEEMDAN与小波包分解的脉搏信号联合去噪

针对脉搏信号非线性、非平稳,且难以去噪的问题,提出了一种基于改进的自适应噪声集合经验模态分解(ICEEMDAN)与小波包分解(WPD)相结合的联合去噪方法,对采集的脉搏信号进行去噪处理。首先对噪声信号进行ICEEMDAN模态分解,产生一系列的固有模态函数(IMF),再将这些IMF分量分别与原信号进行相关系数的计算,比较相关系数的值,然后进行信号的重组,最后对重组后的信号进行小波包分解,提取得到降噪后的脉搏信号。利用仿真数据、实际采集的脉搏信号进行实验分析,将该方法与集合经验模态分解(EEMD)进行了对比,并比较了这两种方法的信噪比(SNR)和均方根误差(RMSE)。实验结果表明：基于ICEEMDAN-WPD的联合去噪方法能更有效地去除噪声,并更好地保留脉搏信号的特征。     

A novel DWT method for ECG noise elimination

An electrocardiogram (ECG) often contains various types of noises and artifacts that might lead to wrong analysis. Recently, many techniques based on discrete wavelet transform (DWT) for ECG noise elimination have been proposed. Determination of the number of decomposition levels, which could vary with the sampling rate (frequency sampling), is one of the main issues in DWT. This letter presents an automatic index, called mean power frequency (MPF) and is independent of the sampling rate, for stopping decomposing process when it achieves the optimum number of decomposition levels. The effectiveness of this scheme is expressed by the signal‐to‐noise ratio (SNR), mean square error (MSE), and correlation coefficient (CC) between the pure and corrected ECG. The results indicate that the applied method can remove Gaussian noise efficiently. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

基于小波理论和HT-LMD的电能质量扰动检测方法

针对含噪声的暂态电能质量扰动检测问题,提出了一种基于小波自适应去噪的改进HT-LMD(HilbertHuang and Local Mean Decomposition)分解检测方法。分析了局部均值分解检测扰动的优缺点以及噪声对LMD检测方法的影响,提出了采用小波分解与重构和自适应阈值技术以及基于正交性判据(Orthogonality Criterion,OC)新的HT-LMD检测方法。小波自适应去噪技术能减弱噪声对LMD分解影响,正交性判据能减少分解的迭代次数。典型暂态电能质量扰动模拟信号和实测信号的检测结果表明,所提方法能在有效提高LMD方法检测电能质量扰动效果同时很好地保留原有暂态扰动信号奇异性特征,提高了检测和定位精度。     

正交频分复用前置编码技术在宽带电力线通信中的应用

基于正交频分复用(OFDM)的概念,提出在宽带电力线通信(PLC)中应用前置编码改进常用编码OFDM的新技术;在分析常用编码OFDM技术应用于宽带电力线通信时存在的缺点的基础上,给出了具体的前置编码方案;还在实际低压电力载波通道模型上对这两种技术进行了宽带电力线通信模拟仿真实验,仿真结果表明,应用前置编码OFDM技术可显著减小传输信号的误码率,并可简化基于常用编码OFDM技术的通信系统实现的复杂性.     

局部放电干扰评价参数信噪比的二阶估计

针对实测局部放电(partial discharge,PD)信号去噪的盲目性,提出对PD信号受干扰程度先作估计评价再决定是否需要去噪的思想。运用二阶统计理论,对构造的实测PD信号相关矩阵进行奇异值分解,将得到的奇异值空间划分为代表信号能量和噪声能量的子空间,建立表征信号和噪声能量大小的判别规则,对PD信号受干扰程度评价参数信噪比(signal-to-noise ratio,SNR)进行二阶估计。通过对模拟与实测PD信号的SNR二阶估计对比分析表明,该二阶估计能很好地判断PD信号受干扰程度,为后续PD信号的去噪处理提供理论依据。     

基于EEMD与KICA的局部放电窄带干扰抑制

窄带干扰严重时可能完全淹没局部放电信号,给局部放电检测工作带来巨大困难。针对局放信号经验模态分解模态混叠现象,提出采用集合经验模态分解与核独立分量分析抑制局部放电窄带干扰的方法。在局放信号叠加不同频率、不同幅值的窄带干扰情况下,该方法能较好地提取出局放信号,有效提高信噪比且信号失真小。仿真和现场测试信号的处理结果均验证了所提方法的有效性。     

不同标准类型的OFDM信号识别方法

目前正交频分复用（OFDM）信号识别研究已有众多方法,但不同标准类型的OFDM信号识别的研究尚不多见。针对这类问题,提出了一种不同标准类型的OFDM信号识别方法。该方法首先提出基于逼近采样信号频谱截止频率的过采样率估计方法,依据估计出的过采样率,采用改进的时域可变延迟自相关方法估计出OFDM信号的子载波个数,然后基于高阶累积量的二阶和四阶的组合特征量估计出空载波个数,最后将估计出来的子载波个数和空载波个数与标准协议相比较,从而识别出不同标准协议的OFDM信号。仿真实验结果表明,该方法在低信噪比多径信道下有效地实现了不同标准类型的OFDM信号识别。