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.

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.

Noise cancellation of a multi-reference full-wave magnetic resonance sounding signal based on a modified sigmoid variable step size least mean square algorithm

Nano-volt magnetic resonance sounding(MRS) signals are sufficiently weak so that during the actual measurement, they are affected by environmental electromagnetic noise, leading to inaccuracy of the extracted characteristic parameters and hindering effective inverse interpretation. Considering the complexity and non-homogeneous spatial distribution of environmental noise and based on the theory of adaptive noise cancellation, a model system for noise cancellation using multi-reference coils was constructed to receive MRS signals. The feasibility of this system with theoretical calculation and experiments was analyzed and a modified sigmoid variable step size least mean square(SVSLMS) algorithm for noise cancellation was presented. The simulation results show that, the multi-reference coil method performs better than the single one on both signal-to-noise ratio(SNR) improvement and signal waveform optimization after filtering, under the condition of different noise correlations in the reference coils and primary detecting coils and different SNRs. In particular, when the noise correlation is poor and the SNR<0, the SNR can be improved by more than 8 dB after filtering with multi-reference coils. And the average fitting errors for initial amplitude and relaxation time are within 5%. Compared with the normalized least mean square(NLMS) algorithm and multichannel Wiener filter and processing field test data, the effectiveness of the proposed method is verified.

Differential involvement of Wnt signaling in Bmp regulation of cancellous versus periosteal bone growth

Bone morphogenetic proteins （Bmp） are well-known to induce bone formation following chondrogenesis, but the direct role of Bmp signaling in the osteoblast lineage is not completely understood. We have recently shown that deletion of the receptor Bmprla in the osteoblast lineage with Dmpl-Cre reduces osteoblast activity in general but stimulates proliferation of preosteoblasts specifically in the cancellous bone region, resulting in diminished periosteal bone growth juxtaposed with excessive cancellous bone formation. Because expression of sclerostin （SOST）, a secreted Wnt antagonist, is notably reduced in the Bmprla- deficient osteocytes, we have genetically tested the hypothesis that increased Wnt signaling might mediate the increase in cancellous bone formation in response to Bmprla deletion. Forced expression of human SOST from a Dmpl promoter fragment partially rescues preosteoblast hyperproliferation and cancellous bone overgrowth in the Bmprla mutant mice, demonstrating functional interaction between Bmp and Wnt signaling in the cancellous bone compat^a-tent. To test whether increased Wnt signaling can compensate for the defect in periosteal growth caused by Bmprla deletion, we have generated compound mutants harboring a hyperactive mutation （A214V） in the Wnt receptor Lrp5. However, the mutant Lrp5 does not restore periosteal bone growth in the Bmprla-deficient mice. Thus, Bmp signaling restricts cancellous bone accrual partly through induction of SOST that limits preosteoblast proliferation, but promotes periosteal bone growth apparently independently of Wnt activation.

Multi-channel differencing adaptive noise cancellation with multi-kernel method

Although a various of existing techniques are able to improve the performance of detection of the weak interesting sig- nal, how to adaptively and efficiently attenuate the intricate noises especially in the case of no available reference noise signal is still the bottleneck to be overcome. According to the characteristics of sonar arrays, a multi-channel differencing method is presented to provide the prerequisite reference noise. However, the ingre- dient of obtained reference noise is too complicated to be used to effectively reduce the interference noise only using the clas- sical linear cancellation methods. Hence, a novel adaptive noise cancellation method based on the multi-kernel normalized least- mean-square algorithm consisting of weighted linear and Gaussian kernel functions is proposed, which allows to simultaneously con- sider the cancellation of linear and nonlinear components in the reference noise. The simulation results demonstrate that the out- put signal-to-noise ratio （SNR） of the novel multi-kernel adaptive filtering method outperforms the conventional linear normalized least-mean-square method and the mono-kernel normalized least- mean-square method using the realistic noise data measured in the lake experiment.

Time-shared channel identification for adaptive noise cancellation in breath sound extraction

Noise artifacts are one of the key obstacles in applying continuous monitoring and computer-assisted analysis of lung sounds. Traditional adaptive noise cancellation (ANC) methodologies work reasonably well when signal and noise are stationary and independent. Clinical lung sound auscultation encounters an acoustic environment in which breath sounds are not stationary and often correlate with noise. Consequendy, capability of ANC becomes significantly compromised. This paper introduces a new methodology for extracting authentic lung sounds from noise-corrupted measurements. Unlike traditional noise cancellation methods that rely on either frequency band separation or signal/noise independence to achieve noise reduction, this methodology combines the traditional noise canceling methods with the unique feature of time-split stages in breathing sounds. By employing a multi-sensor system, the method first employs a high-pass filter to eliminate the off-band noise, and then performs time-shared blind identification and noise cancellation with recursion from breathing cycle to cycle. Since no frequency separation or signal/noise independence is required, this method potentially has a robust and reliable capability of noise reduction, complementing the traditional methods.

Full-duplex prototype based on joint passive and digital cancellation method

Recent research shows that it is possible to achieve the full-duplex system by cancelling strong self-interference signals, which can be divided into three classes respectively, i.e., passive cancellation, active cancellation and digital cancellation. This pa- per tries to achieve the full-duplex system without using active cancellation, thus a full-duplex system using a joint mechanism based on a novel passive cancellation method and a novel digital cancellation method is proposed. Therein, a good antenna place- ment guided by the theory of the antenna electromagnetic field for the passive cancellation is presented. For the proposed digital can- cellation method, unlike previous separate mechanisms, it is de- signed by using the recursive least square （RLS） algorithm jointly with passive cancellation. The self-interference channel state in- formation （CSI） is transferred as the input of digital cancellation to balance the performance and the complexity. Experimental results show that the proposed self-interference cancellation mechanism can achieve about 85 dB which is better than the previous re- search. Meanwhile, this design provides a better performance compared with half-duplex with both line-of-sight channel and non- line-of-sight channel.

Adaptive cancellation of Es layer interference using auxiliary horizontal antennas

Based on a dual-polarization high-frequency wave radar system, an adaptive system using horizontal antennas for the suppression of the Es layer interference （ELI） is deseribech The data received from the horizontal antennas were correlated with the data received from the Vertically Polarized Antennas （VPAs） to estimate and cancel the interference adaptively in the VPAs. Suppressing the interference after each coherent integration time interval, about 25 dB signal-to-interference ratio is expected with the experimentally derived data.

INTERFERENCE CANCELLATION FOR MOBILE DISPERSIVE CHANNELS

A robust interference canceller for Multi-Carrier Code Division Multiple Access(MC-CDMA) using Orthogonal Frequency Division Multiplexing (OFDM) in Rayleigh fading isproposed. This interference canceller is robust in the sense that it cancels Inter-Carriers Inter-ference (ICI) and is suitable for use in dispersive channels. To come up the effects of the signaldispersion, Doppler shifts and delay spreads on the performance of MC-CDMA systems over mo-bile fading channels, this interference canceller exploits the merit of the orthogonal signaling andpilot signals to evaluate the channel parameters. This interface canceller is well suited to work initerative turbo interference cancellation.

Iterative Signal Detection Based Soft Interference Cancellation for Satellite-Terrestrial Downlink NOMA Systems

To improve the bit error rate(BER)performance of multi-user signal detection in satelliteterrestrial downlink non-orthogonal multiple access(NOMA)systems,an iterative signal detection algorithm based on soft interference cancellation with optimal power allocation is proposed.Given that power allocation has a significant impact on BER performance,the optimal power allocation is obtained by minimizing the average BER of NOMA users.According to the allocated powers,successive interference cancellation(SIC)between NOMA users is performed in descending power order.For each user,an iterative soft interference cancellation is performed,and soft symbol probabilities are calculated for soft decision.To improve detection accuracy and without increasing the complexity,the aforementioned algorithm is optimized by adding minimum mean square error(MMSE)signal estimation before detection,and in each iteration soft symbol probabilities are utilized for soft-decision of the current user and also for the update of soft interference of the previous user.Simulation results illustrate that the optimized algorithm i.e.MMSE-IDBSIC significantly outperforms joint multi-user detection and SIC detection by 7.57dB and 8.03dB in terms of BER performance.

结合EEMD的噪声对消方法在遥测振动信号降噪中的应用

针对传统降噪方法难以兼顾飞行器遥测振动信号中细节信息损失和降噪性能之间的矛盾,提出一种集合经验模态分解(ensemble empirical mode decomposition,EEMD)和噪声对消相结合的降噪方法。信号经EEMD处理得到本征模态函数(intrinsic mode function,IMF),将第1阶IMF分量和其余IMF分量的累加和分别作为参考噪声和待降噪信号;利用核方法将信号映射到高维特征空间,利用映射到高维空间中的参考噪声和待降噪信号进行噪声对消。计算机仿真结果表明:该方法在避免信号细节信息损失的前提下具有良好的降噪性能,某次飞行器试验中实测数据处理结果证明方法有效和实用。

一种卫星隐蔽通信信号盲分离算法

重构抵消算法是卫星隐蔽通信信号分离的关键技术,算法的性能主要依赖于参数估计的精度。然而在实际环境中,参数估计误差带来的算法性能损失无法被避免。此外,对信号的重构使得该算法计算复杂度较高。针对这个问题,首先分析了参数估计误差对分离性能的影响,然后提出基于盲均衡算法的协作分离算法,提升信号分离性能的同时降低了算法的计算量。仿真实验表明,新算法相较于重构抵消算法,降低了对参数估计精度的依赖,当参数估计误差大于0.05时,信号的解调误码率降低了一个数量级左右。

一种基于改进NLMS的多雷达主瓣干扰抑制方法

远程探测场景下弹载主瓣干扰因与目标角度间隔小,单站抗干扰方法性能下降严重。多雷达通过合理布站可有效“分辨”目标和干扰,被认为是可有效抑制主瓣干扰的途径。针对当前多雷达抗主瓣干扰方法普遍存在收敛速度慢的问题,提出一种基于改进归一化最小均方(NLMS)的多雷达对消抗主瓣干扰方法,并通过理论推导给出了其应用条件。该方法通过定义消散因子实现对步长的自适应控制从而达到快速收敛的目的,仿真结果表明该方法在收敛速度及收敛后均方误差(MSE)上具有明显优势。最后通过外场试验进一步验证该方法的性能,在满足布站条件且干噪比≥30 dB的前提下,信噪比改善可达19 dB以上,具有较高的应用价值。

自动增益控制系统对干扰抵消算法的影响分析

为扩大信号采集处理接收机的动态范围,一般在A/D转换器前引入自动增益控制(Automatic Gain Control,AGC)系统。在实际工程中,信号采集之前打开AGC系统,会导致依赖信号功率抬升进行识别干扰起始位置的信号检测失败。针对该问题,简要说明了干扰抵消技术的处理流程。为进一步查找问题,阐述了AGC电路设计与控制流程;通过分析,给出了引入AGC系统后对采集数据波形的影响。根据分析结果,调整了搜索干扰信号起始位置的算法,试验验证了实测数据与分析结果吻合,证明了调整后干扰抵消算法的有效性。

短波多音信号并行干扰消除解调算法

为了对抗严重的多径效应,短波通信系统经常采用多音并行方式进行信息传输,结合快速傅里叶(FFT)算法对信号进行调制和解调。部分通信系统的帧周期不满足载波间正交的条件,传统算法采用截断每帧信号的方式恢复载波正交条件后使用FFT算法进行解调,削弱了信号的空间分集增益。针对以上问题提出一种基于并行干扰消除策略的多音信号并行解调算法,通过构建干扰消除矩阵,在不牺牲信号帧长度的前提下实现解调,仿真实验证明了所提算法的有效性。

机载相控阵雷达气象信号处理研究

机载气象雷达作为一种重要的气象监测手段,被广泛应用到国防和民用,它能够通过间歇的接收云层中粒子的散射回波来实时远方的气象状况,保证飞机的安全飞行。相控阵雷达作为目前功能最为强大的雷达,它不仅能通过多普勒效应检测到能检测到气象目标的位置、强度、运动方向和内部粒子活跃程度,而且其波束可以快速捷变,能够对气象目标区域进行全空域扫描,因此机载相控阵雷达在气象检测方面有着突出的优势。本文在相控阵雷达上,采用MTI杂波对消和脉冲对算法实现了气象目标检测,并对其在实测数据上的效果进行了详细分析。实验结果表明,本文的方法能够准确地检测到气象目标的位置和强度,并且计算量小,工程化容易,因此具有重要的研究意义和较大的应用价值。

基于自适应滤波器的皮带机动态称重信号处理方法

针对目前皮带机动态称重系统的称重信号存在噪声或干扰的问题,提出了一种改进自适应噪声消除(IANC)的称重信号处理方法。建立了皮带机动态称重系统动态响应过程的数学模型。设计了结合卡尔曼和最小均方的算法(KF-LMS),提升了ANC噪声消除的性能。实验阶段,通过模拟和搭建实验平台对所提方法进行测试。结果表明,与LMS,NLMS,SLMS等算法相比,所提的KF-LMS算法在皮带机动态称重信号处理中具有良好性能,具备较高的可靠性和称重精度。实验结果验证了所提方法的有效性和实用性,该模型具有广阔的应用前景。

一种具有纹波消除技术的10 bit SAR ADC

逐次逼近寄存器模数转换器(SAR ADC)在逐次逼近的过程中,电容的切换会使参考电压上出现参考纹波噪声,该噪声会影响比较器的判定,进而输出错误的比较结果。针对该问题,基于CMOS 0.5μm工艺,设计了一种具有纹波消除技术的10 bit SAR ADC。通过增加纹波至比较器输入端的额外路径,将参考纹波满摆幅输入至比较器中;同时设计了消除数模转换器(DAC)模块,对参考纹波进行采样和输入,通过反转纹波噪声的极性,消除参考纹波对ADC输出的影响。该设计将信噪比(SNR)提高到56.75 dB,将有效位数(ENOB)提升到9.14 bit,将积分非线性(INL)从-1~5 LSB降低到-0.2~0.3 LSB,将微分非线性(DNL)从-3~4 LSB降低到-0.5~0.5 LSB。

一种改进型KB-RLS算法在自干扰对消中的工程应用

在自适应自干扰对消的过程中,结合实际的工程应用需求(收敛精度高、收敛速度快、算法复杂度低),提出了一种改进型保持平衡-递推最小二乘法(KB-RLS)算法,并进行了相应的硬件架构搭建。在此架构上,抓取了实际电磁环境中的信号进行仿真测试,并将改进型算法和已有的经典RLS算法进行对比。结果表明,该算法在工程应用中,对实际环境下的复杂电磁信号,能获得更好的对消效果。

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.