On the Performance of Active Analog Self-Interference Cancellation Techniques for Beyond 5G Systems

The in-band full-duplex(IBFD)mechanism is of interest in beyond 5 G systems due to its potential to enhance spectral efficiency and reduce delay.To achieve the maximum gain of IBFD systems,the significant self-interference(SI)must be efficiently suppressed.The challenges of wideband selfinterference cancellation(SIC)lie in the radio frequency(RF)domain,where the performance will be limited by the hardware.This paper reviews current RF cancellation mechanisms and investigates an efficient mechanism for future wideband systems with minimum complexity.The working principle and implementation details of multi-tap cancellers are first introduced,then an optical domain-based RF canceller is reviewed,and a novel low-cost design is proposed.To minimize the cost and complexity of the canceller,the minimum required number of taps are analyzed.Simulation results show that with the commonly used 12-bits analog-to-digital converter(ADC)at the receiver,the novel optical domain-based canceller can enable efficient SIC in the 3 GPP LTE specifications compatible system within 400 MHz bandwidth.

RF self-interference cancellation by using photonic technology [Invited]

Radio frequency(RF) self-interference is a key issue for the application of in-band full-duplex communication in beyond fifth generation and sixth generation communications.Compared with electronic technology, photonic technology has the advantages of wide bandwidth and high tuning precision, exhibiting great potential to realize high interference cancellation depth over broad band.In this paper, a comprehensive overview of photonic enabled RF self-interference cancellation(SIC)is presented.The operation principle of photonic RF SIC is introduced, and the advances in implementing photonic RF SIC according to the realization mechanism of phase reversal are summarized.For further realistic applications, the multipath RF SIC and the integrated photonic RF SIC are also surveyed.Finally, the challenges and opportunities of photonic RF SIC technology are discussed.

Robust Digital Non-Linear Self-Interference Cancellation in Full Duplex Radios with Maximum Correntropy Criterion

Full duplex radio increases the frequency efficiency but its performance is limited by the self-interference （SI）. We first analyze the multiple noises in the full duplex radio system and model such noises as an α - stable distribution. Then we formulate a novel non-Gaussian SI problem. Under the maximum correntropy criterion （MCC）, a robust digital non-linear self-interference cancellation algorithm is proposed for the SI channel estimation. A gradient descent based algorithm is derived to search the optimal solution. Simulation results show that the proposed algorithm can achieve a smaller estimation error and a higher pseudo signal to interference plus noise ratio （PSINR） than the well-known least mean square （LMS） algorithm and least square （LS） algorithm.

Self-Interference Elimination by Physical Feedback Channel in CCFD for 3-D Beamforming Communication

The 3-D beamforming scheme has elite as evolving interest because of its efficiency to empower assorted techniques such as vertical and horizontal domains and emanation beamforming according to subscriber's provisions. Usually, 3-D beamforming communication is set up on FDD/TDD approach those effects on the performance of spectrum and energy efficiency. Co-frequency and CoTime Full Duplex(CCFD) is an effective solution to improve the spectrum and energy efficiency by transmitting and receiving simultaneously in frequency and time domain. While, CCFD communication often face the self-interference issue when communication occurs, simultaneously. Consequently, in this paper a self-interference elimination by physical feedback channel in CCFD for 3-D Beamforming communication scheme is proposed to improve the over-all system performance in terms of energy and spectrum efficiency. The simulation and analytical outcomes demonstrated that the proposed system is superior than the traditional one.

A physical layer security scheme for full-duplex communication systems with residual self-interference and non-eavesdropping CSI

We discuss the physical layer security scheme in the Full-Duplex(FD)MIMO point-to-point two-way communication system with residual self-interference,in which legitimate nodes send confidential information and null space Artificial Noise(AN)while receiving information.Because the Channel State Information(CSI)of the eavesdropper is unavailable,we optimize the covariance matrices of the information signal as well as the allocation of the antenna for transmitting and receiving to minimize the signal power consumption under the target rate constraint.As a result,the power of AN is maximized within the limit of total power,so the interception capability of the eavesdropper is suppressed as much as possible.Since self-interference cannot be completely eliminated,the optimization process of one legitimate node depends on the optimization result of the other.By substituting self-interference power in the secrecy rate formula with its average value,the joint optimization process at the two nodes is transformed into two separate and solvable optimization processes.Then,the Water-Filling Algorithm(WFA)and bisection algorithm are used to get the optimal covariance matrices of the signal.Furthermore,we derive the theoretical lower bound of ergodic achievable secrecy rate under rayleigh channels to evaluate the performance of the scheme.The simulation results show that the theoretical derivation is correct,and the actual achievable rate is very close to the target rate,which means that the approximation in the optimization is feasible.The results also show that secrecy transmission can be realized because a considerable secrecy rate can be achieved.

Polarization Oblique Projection Based Self-Interference Cancellation against PA Nonlinear Distortion in MIMO Full Duplex System

In MIMO full duplex system,power amplifier(PA) nonlinearity limits the self-interference(SI) cancellation seriously. Most existing methods need to model and estimate the PA nonlinearity in order to reconstruct the SI,however the estimation error caused by the mismatch between the estimated PA model and the actual PA property still impacts the cancellation ability,especially when the transmit power is high. In this paper we propose a polarization oblique projection based self-interference cancellation method which does not need to estimate the PA nonlinearity coefficients. It exploits the polarization state information of the signals which is immune to the PA nonlinearity,and establishes an oblique projection operator to cancel the SI. Numerical results and analysis demonstrate that it can cancel the nonlinear SI effectively. Moreover the signal to interfere plus noise ratio(SINR) and the achievable sum rate do not deteriorate when the transmit power is high. Further,the upper bound of the achievable sum rate can be more than twice that of the half duplex.

Adaptive digital self-interference cancellation based on fractional order LMS in LFMCW radar

Adaptive digital self-interference cancellation(ADSIC)is a significant method to suppress self-interference and improve the performance of the linear frequency modulated continuous wave(LFMCW)radar.Due to efficient implementation structure,the conventional method based on least mean square(LMS)is widely used,but its performance is not sufficient for LFMCW radar.To achieve a better self-interference cancellation(SIC)result and more optimal radar performance,we present an ADSIC method based on fractional order LMS(FOLMS),which utilizes the multi-path cancellation structure and adaptively updates the weight coefficients of the cancellation system.First,we derive the iterative expression of the weight coefficients by using the fractional order derivative and short-term memory principle.Then,to solve the problem that it is difficult to select the parameters of the proposed method due to the non-stationary characteristics of radar transmitted signals,we construct the performance evaluation model of LFMCW radar,and analyze the relationship between the mean square deviation and the parameters of FOLMS.Finally,the theoretical analysis and simulation results show that the proposed method has a better SIC performance than the conventional methods.

All-Digital Self-Interference Cancellation in Zero-IF Full-Duplex Transceivers

In this paper,a general scheme in digital self-interference cancellation at baseband for zero-IF full-duplex transceivers is presented. We model the self-interference signals specifically with only the nonlinear distortion signals falling in receiving band considered. A joint estimation algorithm is proposed for compensating the time delay and frequency offset taking into account the IQ amplitude and phase imbalances from mixers. The memory effect and nonlinear distortion are adaptively estimated by the de-correlated normalized least mean square(DNLMS) algorithm. Numerical simulation results demonstrate that the proposed self-interference cancellation scheme can efficiently compensate the self-interference and outperform the existing traditional solutions.

基于改进KNN-RF的信息补全算法

针对室内指纹定位指纹库数据在实际环境中存在数据缺失导致定位误差大的问题,本文提出了一种改进距离公式的K近邻-随机森林的信息补全算法。首先,采用高斯滤波对收集的指纹数据进行预处理,去除干扰数据项,提高数据可靠性。其次,在将指纹数据划分为训练集和测试集的基础上,采用结合欧氏距离和曼哈顿距离的KNN算法获得近邻集合样本,随后用RF算法对近邻集合训练进行优化,再把各个决策树的预测结果取平均值,得到缺失数据的预测值。最后,将改进的补全算法与KNN、改进的KNN、RF和KNN-RF补全算法进行对比。实验结果表明,本文的改进补全算法的预测准确率和精度均优于其他算法,预测的准确率达91.3%。同时本文补全算法的指纹库平均定位误差为1.82 m,相较于其他补全算法的指纹库定位误差降低了1.6%~7.2%,定位性能更好。

基于VPNRS-RF的飞机液压系统故障诊断模型

针对飞机液压系统故障诊断特征值冗余难以精准获取和准确率不高的问题,提出一种基于变精度邻域粗糙集(Variable Precision Neighborhood Rough Set,VPNRS)和随机森林(Random Forest,RF)相结合的特征选择算法,并以此为基础建立飞机液压系统故障诊断模型。VPNRS-RF算法主要是利用随机森林算法分别对变精度邻域和模糊熵粗糙集约简后的特征进行重要度排序,再次筛选后确定最优特征子集,使用最优特征子集对在线贯序极限学习机(OSELM)分类模型进行训练,从而提高故障信息获取准确率。最后以飞机起落架收放系统为例进行仿真研究,验证了VPNRS-RFOSELM模型的优越性。

基于LSTM-RF的电动钻机绞车齿轮箱故障诊断

针对提高石油电动钻机绞车齿轮箱故障诊断的准确性和效率,提出了一种基于长短期记忆网络(long short-term memory,LSTM)和随机森林(random forest,RF)融合模型。首先,运用LSTM能够从大规模数据中学习复杂特征,将这些特征作为随机森林的输入。然后,通过随机森林处理非线性和高维数据以及对特征的分类,以实现对齿轮不同故障状态的识别。最后,利用电动钻机绞车齿轮箱运行过程中的实时数据,建立了一个包含多种齿轮故障类型的综合数据集。试验结果表明,LSTM齿轮故障诊断准确率为94.67%,RF齿轮故障诊断准确率为94.34%,支持向量机齿轮故障诊断准确率为82.00%,K近邻齿轮故障诊断准确率88.33%,而融合模型LSTM-RF在齿轮故障诊断准确率方面达到了98.33%,克服了单一模型的局限性,提高了诊断准确性。研究表明了融合模型具有更优的电动钻机绞车齿轮箱故障诊断能力。

基于RF-SFLA-SVM的装配式建筑高空作业工人不安全行为预警

为有效预警装配式建筑高空作业工人不安全行为的发生趋势或状态,增强对装配式建筑工人不安全行为(PBWUBs)的管控,采用随机森林(RF)-混合蛙跳算法(SFLA)-支持向量机(SVM)模型,开展工人不安全行为预警研究。首先,采用SHEL模型分析处于高空作业危险中的PBWUBs的影响因素,并通过RF确定关键预警指标;然后,采用SFLA对SVM的参数进行寻优改进;最后,利用RF-SFLA-SVM预警高空作业PBWUBs,提出应对措施,并与其他预警模型对比。研究结果表明:基于RF-SFLA-SVM预警高空作业PBWUBs,准确率最高,为91.67%,与其他模型的预警性能相比,最高提升14%。研究结果可为高空作业PBWUBs的防控提供参考。

基于DBSCAN-RF洪水分类的洪水预报应用研究

【目的】洪水分类预报能有效提高洪水预报准确性,为防灾减灾工作提供科学依据。【方法】针对分类因子和分类算法优选问题,以海河流域徒骇河宫家闸上游为例进行研究,(1)充分考虑产汇流影响因素与洪水特征,选取洪峰流量、洪水总量、时段洪量、洪水历时、起历时、落历时、峰度、偏度、涨水仰角、落水仰角、C_(s)、C_(v)、前3 d面雨量、前10 d面雨量、累计面雨量及最大面雨量等16维分类因子,使用主成分投影法(Principal Component Analysis,PCA)对分类因子降维提高计算效率;(2)基于密度聚类(Density-Based Spatial Clustering of Applications with Noise,DBSCAN)-随机森林(Random Forest,RF)算法进行洪水分类,减少对分类先验知识的依赖,提高了分类精度;(3)在徒骇河流域进行了方法应用,选择适用于半干旱半湿润地区的超渗-蓄满同时作用的产流模型及单位线汇流模型进行洪水分类预报研究,分别针对各类洪水进行模型率定。【结果】结果表明:轮廓系数为0.7015,表明DBSCAN算法聚类效果理想,基于RF算法的洪水分类准确率为91.67%,分类效果理想;经洪水分类预报,NSE系数均高于0.8,分类预报结果优于直接预报。【结论】结果说明:基于DBSCAN-RF洪水分类的洪水预报能较好地反映研究区域洪水演进过程,为研究区域洪水预报及防灾减灾工作提供依据。

RIS辅助的混合RF/FSO系统物理层安全性能分析

【目的】针对自由空间光(FSO)链路和射频(RF)链路的保密信息容易被外部窃听者窃听的问题,为提升混合RF/FSO通信系统的保密性能,同时考虑到实际工程中FSO链路往往无法满足视距条件且不同天线分支之间会由于收发模块小型化产生相关性,需要对可重构智能表面(RIS)辅助的混合RF/FSO系统的安全性能进行研究,以得到系统安全性能与RIS部署位置和天线相关性程度等参数的关系。【方法】文章考虑单个窃听者,分别针对RF和FSO链路进行窃听,RF链路服从任意相关的Nakagami-m分布,FSO链路服从Gamma-Gamma分布。采用解码转发协议,推导得到了两种窃听场景下通信系统的安全中断概率(SOP)和严格正安全容量概率(SPSC)的闭合表达式,并对SOP进行了渐近分析。此外还利用Matlab软件进行了仿真实验,通过蒙特卡洛仿真来验证所推导公式的准确性。【结果】仿真结果表明,将RIS部署在靠近接收端的位置可以降低系统的SOP,RF主信道的信道质量与窃听信道相比较好时,天线相关性程度的增加会使系统的SOP上升。【结论】RIS辅助的FSO链路相比RF链路具有更好的安全性,虽然多天线分集技术能够有效提高系统的安全性能,但是类似指向误差和大气湍流引起的衰落,天线相关性也会对系统的安全性能造成损害,通过降低天线相关性程度能有效提升系统的安全性。

基于RF-RNN模型的DNS隐蔽信道检测方法

为提高检测隐蔽信道的灵敏度,提出一种基于随机森林(Random Forest,RF)和循环神经网络(Recurrent Neural Network,RNN)的域名系统(Domain Name System,DNS)隐蔽信道检测方法。该方法采用域名检测作为主要手段,使用RF模型对域名进行分类,通过深度学习方法挖掘更高阶的特征表示。实验结果表明,与单一模型相比,该方法在检测准确性和健壮性方面均取得了显著提升。

基于RF-GWO的水利工程地质渗透系数智能反演分析

地质渗透系数是准确分析水利工程渗流的关键参数。针对传统反演方法计算效率低、精度差的问题,采用有限元正演模型和正交试验设计构建渗透系数反演样本集,建立了基于随机森林(RF)算法的渗流计算代理模型;在此基础上,引入灰狼优化(GWO)算法,提出了基于RF-GWO的渗透系数智能反演方法,并以Z抽水蓄能电站为研究案例进行了验证。结果表明:RF模型对各钻孔水位预测结果均接近实测值,性能优于CART和BP模型;GWO可搜寻到地质最佳渗透系数,钻孔水位反演结果合理,相对误差最大为0.42%,精度满足工程要求,计算的天然渗流场分布形态也符合一般山体渗流场分布规律。建立的反演模型能够快速准确地推断工程区地层渗透系数,具有实际工程应用价值。

基于RF-GA的热磨机生产参数优化方法

热磨机是纤维板生产中最重要的设备之一;热磨机的综合能耗在纤维板生产的整体能源消耗中占比显著,优化生产参数以降低热磨机能耗一直是纤维板生产的要求之一。以华北某纤维板企业采集的数据为依据,针对影响比能耗(SEC)和纤维质量(QF)的多个生产参数,用粒子群算法优化的BP神经网络、支持向量机(SVM)和随机森林(RF)建立比能耗和纤维质量预测模型,经对比确定最佳比能耗和纤维质量预测模型;后基于最佳预测模型构建生产参数优化模型,采用遗传算法(GA)对其求解得到最佳生产参数,以此提出基于RF-GA模型的热磨机生产参数优化方法。结果表明,热磨机各生产参数之间存在较强耦合关系,且与比能耗和纤维质量为非线性关联;粒子群算法对机器学习算法中超参数的优化是必要的,可以有效降低机器学习算法误差;选取5组不同纤维质量下的数据,采用建立的热磨机生产参数优化方法优化后,比能耗平均下降6.9kW·h/t、降幅为5.22%。该研究验证了RF-GA热磨机生产参数优化方法的可行性,能够应用于生产参数的优化,有效地实现节能降耗的目标,并为热磨机生产参数的设定提供依据。

多尺度数据条件下基于优化RF算法的工程机械可靠性仿真

工程机械是建筑工程的关键设备,其可靠性的高低直接影响到工程的生产效率,为了给项目工程提供可靠性较高的机械设备,提出多尺度数据条件下基于优化RF算法的工程机械可靠性分析方法。构建工程机械设备等效模型,确定工程机械设备的组成结构与材料,模拟工程机械设备工作流程,确定可靠性影响因素。采集工程机械设备多尺度数据,利用优化RF算法,通过决策树构建、特征提取等步骤,识别工程机械设备工作状态。计算工程机械可靠性指标的具体取值,实现工程机械的可靠性分析。通过仿真测试实验得出结论:与传统分析方法相比,优化设计方法的机械可靠性分析误差降低了0.033,通过可靠性分析方法的应用能够有效提升工程产品的生产合格率,由此证明优化设计方法在分析精度和应用性能方面具有明显优势。

融合改进RF算法的人体姿态识别方法在运动训练领域的应用

对人体姿态识别及现代智能化工程设计成为人机交互领域的重要研究方向进行了研究;在实现更高效、智能的人体姿态识别中,采用了基于DBSCAN-RF算法的分类训练器,同时对RF算法加以改进,引入了HD-SMOTE方法;该方法的技术创新和独特之处在于结合了密度聚类和随机森林的优点,能够有效地处理带有噪声的数据集,并具有较高的计算效率和可扩展性;通过实验测试,DBSCAN-RF算法的识别召回率最高达到了98.64%,相比于传统的RF算法、K-means-RF以及Mean-shift-RF算法,其数值分别增加了6.37%、4.28%、3.95%;同时,DBSCAN-RF算法在跌倒和正常走路的识别召回率分别达到了95.31%和96.48%;此外,DBSCAN-RF算法的测试时间均低于62 ms;经实际应用满足了现代智能化的人体姿态识别工程上的应用,为现代智能化的人体姿态识别提供了可靠的技术支持。

基于AT86RF231的无线扩频语音通信方案

随着无线通信技术的发展,适配多种应用场景的短距离无线通信技术应运而生。ZigBee技术是一种近距离、低复杂度、低功耗、低数据速率、低成本的双向无线通信技术。由于传输的时延不固定,ZigBee不适合实时语音通信。为改善时延问题,文章设计了一种以ZigBee芯片AT86RF231为通信芯片的语音对讲系统,使用芯片的MAC层和物理层,通过FPGA控制收发时序,实现了实时无线语音通信,满足了某系统的无线语音通信要求。