methods: 该 paper 使用 Cross-layer 视角，对客户端数据集分布和个体资源进行协调优化，并采用 RIS 帮助实现更好的学习环境。
results: 数值结果表明，在非 i.i.d. 数据和不完全 CSI 下，ROAR-Fed 算法可以 convergent，并且在不同客户端资源和数据分布情况下显示出优异性。Abstract
Over-the-air federated learning (OTA-FL) integrates communication and model aggregation by exploiting the innate superposition property of wireless channels. The approach renders bandwidth efficient learning, but requires care in handling the wireless physical layer impairments. In this paper, federated edge learning is considered for a network that is heterogeneous with respect to client (edge node) data set distributions and individual client resources, under a general non-convex learning objective. We augment the wireless OTA-FL system with a Reconfigurable Intelligent Surface (RIS) to enable a propagation environment with improved learning performance in a realistic time varying physical layer. Our approach is a cross-layer perspective that jointly optimizes communication, computation and learning resources, in this general heterogeneous setting. We adapt the local computation steps and transmission power of the clients in conjunction with the RIS phase shifts. The resulting joint communication and learning algorithm, RIS-assisted Over-the-air Adaptive Resource Allocation for Federated learning (ROAR-Fed) is shown to be convergent in this general setting. Numerical results demonstrate the effectiveness of ROAR-Fed under heterogeneous (non i.i.d.) data and imperfect CSI, indicating the advantage of RIS assisted learning in this general set up.
摘要
随空 Federated Learning (OTA-FL) 利用无线通信频率层的自然superposition 特性来实现带宽效率的学习。然而，需要在无线物理层缺陷处理方面予以关注。在本文中，我们考虑了Edge federated learning 在具有不同客户（边缘节点）数据集分布和个体客户资源的网络上。我们在一般非对称学习目标下对无线OTA-FL系统进行扩展，并添加了智能表面（RIS）以实现改进的物理层媒体。我们采用了跨层视角，同时优化通信、计算和学习资源。在这种一般不同设置下，我们适应性地调整客户端的计算步骤和传输功率，并与RIS相关的相位Shift。得到的联合通信和学习算法，即RIS协助的Over-the-air Adaptive Resource Allocation for Federated learning（ROAR-Fed），在这种一般设置下被证明是收敛的。数据示ROAR-Fed在不同（非i.i.d.）数据和不完美CSI下的效果，表明RIS协助学习在这种一般设置下具有优势。
RIS-Assisted Energy Harvesting Gains for Bistatic Backscatter Networks: Performance Analysis and RIS Phase Optimization
paper_authors: Diluka Galappaththige, Fatemeh Rezaei, Chintha Tellambura, Sanjeewa Herath for: This paper aims to improve the energy autonomy of inexpensive tags in IoT networks by deploying a reconfigurable intelligent surface (RIS) to enhance RF power and overcome energy insecurities.methods: The paper explores the use of RIS to improve the energy harvesting (EH) capabilities of tags, and analyzes the impact of linear and non-linear EH models on single-tag and multi-tag scenarios. The paper also derives key metrics such as received power, harvested power, achievable rate, outage probability, bit error rate, and diversity order.results: The paper shows significant improvements in activation distance, received power, and achievable rate compared to benchmarks without RIS or with random RIS-phase design. For instance, the optimal design with a \num{200}-element RIS increases the activation distance by \qty{270}{\percent} and \qty{55}{\percent} compared to the benchmarks. The paper demonstrates that RIS deployment improves the energy autonomy of tags while maintaining the basic tag design intact.Abstract
Inexpensive tags powered by energy harvesting (EH) can realize green (energy-efficient) Internet of Things (IoT) networks. However, tags are vulnerable to energy insecurities, resulting in poor communication ranges, activation distances, and data rates. To overcome these challenges, we explore the use of a reconfigurable intelligent surface (RIS) for EH-based IoT networks. The RIS is deployed to enhance RF power at the tag, improving EH capabilities. We consider linear and non-linear EH models and analyze single-tag and multi-tag scenarios. For single-tag networks, the tag's maximum received power and the reader's signal-to-noise ratio with the optimized RIS phase-shifts are derived. Key metrics, such as received power, harvested power, achievable rate, outage probability, bit error rate, and diversity order, are also evaluated. The impact of RIS phase shift quantization errors is also studied. For the multi-tag case, an algorithm to compute the optimal RIS phase-shifts is developed. Numerical results and simulations demonstrate significant improvements compared to the benchmarks of no-RIS case and random RIS-phase design. For instance, our optimal design with a \num{200}-element RIS increases the activation distance by \qty{270}{\percent} and \qty{55}{\percent} compared to those benchmarks. In summary, RIS deployment improves the energy autonomy of tags while maintaining the basic tag design intact.
摘要
低成本的标签（标签）由能量收集（EH）能够实现绿色（能量高效）互联网络（IoT）。然而，标签受到能源不安全性的挑战，导致通信范围、活动距离和数据速率受到影响。为了解决这些挑战，我们研究使用可重新配置的智能表面（RIS）来增强标签上的RF能量，提高EH能力。我们考虑了线性和非线性EH模型，对单标签和多标签场景进行分析。在单标签网络中，我们计算了标签上最大接收功率和读取器与优化RIS相位偏移后的信号强度比。我们还评估了关键指标，如接收功率、收集功率、可达速率、失业概率、比特错误率和多样度。我们还研究了RIS相位偏移量的量化误差的影响。在多标签场景中，我们开发了计算优化RIS相位偏移的算法。numericalResults和 simulations表明，我们的优化设计可以与无RIS场景和随机RIS相位设计相比，提高标签的活动距离和数据速率。例如，我们的优化设计使用200个RIS元素可以提高标签的活动距离270%和55%。总之，RIS部署可以提高标签的能源自主性，而不需要修改标签的基本设计。
A Read Margin Enhancement Circuit with Dynamic Bias Optimization for MRAM
results: 对28奈米1Mb MRAM宽 macro进行了模拟研究，结果显示DBO电路能够在PVT变化下保持优化读偏好电压的跟踪精度高于90%，并且能够降低读出错误率，提高MRAM性能和可靠性。Abstract
This brief introduces a read bias circuit to improve readout yield of magnetic random access memories (MRAMs). A dynamic bias optimization (DBO) circuit is proposed to enable the real-time tracking of the optimal read voltage across processvoltage-temperature (PVT) variations within an MRAM array. It optimizes read performance by adjusting the read bias voltage dynamically for maximum sensing margin. Simulation results on a 28-nm 1Mb MRAM macro show that the tracking accuracy of the proposed DBO circuit remains above 90% even when the optimal sensing voltage varies up to 50%. Such dynamic tracking strategy further results in up to two orders of magnitude reduction in the bit error rate with respect to different variations, highlighting its effectiveness in enhancing MRAM performance and reliability.
摘要
Asymptotic Performance of the GSVD-Based MIMO-NOMA Communications with Rician Fading
paper_authors: Chenguang Rao, Zhiguo Ding, Kanapathippillai Cumanan, Xuchu Dai
for: 这篇论文研究了MIMO-NOMA系统中使用GSVD作为前处理算法的性能。
methods: 该论文使用了operator-valued free probability theory中的线性化技巧和决定性方法来分析通道矩阵的普通特征。
results: 该论文提出了一种迭代过程来计算通道矩阵的Cauchy转换，并通过这种方法得到了通信系统的均值数据速率。此外，当通道模型为Rayleigh折射时，也 deriv了closed-form表达式。实验结果 validate了分析结果。Abstract
In recent years, the multiple-input multiple-output (MIMO) non-orthogonal multiple-access (NOMA) systems have attracted a significant interest in the relevant research communities. As a potential precoding scheme, the generalized singular value decomposition (GSVD) can be adopted in MIMO-NOMA systems and has been proved to have high spectral efficiency. In this paper, the performance of the GSVD-based MIMO-NOMA communications with Rician fading is studied. In particular, the distribution characteristics of generalized singular values (GSVs) of channel matrices are analyzed. Two novel mathematical tools, the linearization trick and the deterministic equivalent method, which are based on operator-valued free probability theory, are exploited to derive the Cauchy transform of GSVs. An iterative process is proposed to obtain the numerical values of the Cauchy transform of GSVs, which can be exploited to derive the average data rates of the communication system. In addition, the special case when the channel is modeled as Rayleigh fading, i.e., the line-of-sight propagation is trivial, is analyzed. In this case, the closed-form expressions of average rates are derived from the proposed iterative process. Simulation results are provided to validate the derived analytical results.
摘要
在最近几年，多输入多输出（MIMO）不对称多访问（NOMA）系统已经吸引了研究领域的广泛关注。作为MIMO-NOMA系统的可能的预编码方案，泛化协方差矩阵（GSVD）可以应用于MIMO-NOMA系统，并且已经证明具有高spectral efficiency。本文研究了GSVD基于MIMO-NOMA通信系统中的 ricain fading 的性能。特别是分析了通道矩阵的泛化协方差值（GSV）的分布特征。基于 оператор值自由概率论的两种新的数学工具——线性化技巧和deterministic equivalent方法——被利用来 derivethe Cauchy transform of GSVs。一种迭代过程被提出来获取GSVs的Cauchy transform的数值，可以用来计算通信系统的平均数据率。此外，当通道模型为Rayleigh fading，即线性视程是rivial的特殊情况也被分析。在这种情况下，通过提posed迭代过程，得到了Closed-form表达式的平均率。Simulation results are provided to validate the derived analytical results.
Uplink Power Control for Distributed Massive MIMO with 1-Bit ADCs
paper_authors: Bikshapathi Gouda, Italo Atzeni, Antti Tölli
For: 这篇论文研究了分布式巨量多输入多输出系统中基站（BS）装备1比特数字转换器（ADC）的上行功率控制问题。* Methods: 该论文使用了1比特ADC的信号干扰分析和优化策略，并提出了三种算法来优化UE传输功率和BS中的扰干。* Results: 研究发现，在多BS情况下，通过合适地调整BS中的扰干，可以使SNDR在输出 JOIN combiner中变为单modal函数，从而使UE可以有效地被多个BS服务。此外，在多UE情况下，该论文提出了最优化UE传输功率和扰干的算法，以达到最小功率和最大最小SINDR的目标。Abstract
We consider the problem of uplink power control for distributed massive multiple-input multiple-output systems where the base stations (BSs) are equipped with 1-bit analog-to-digital converters (ADCs). The scenario with a single-user equipment (UE) is first considered to provide insights into the signal-tonoise-and-distortion ratio (SNDR). With a single BS, the SNDR is a unimodal function of the UE transmit power. With multiple BSs, the SNDR at the output of the joint combiner can be made unimodal by adding properly tuned dithering at each BS. As a result, the UE can be effectively served by multiple BSs with 1-bit ADCs. Considering the signal-to-interference-plus-noise-anddistortion ratio (SINDR) in the multi-UE scenario, we aim at optimizing the UE transmit powers and the dithering at each BS based on the min-power and max-min-SINDR criteria. To this end, we propose three algorithms with different convergence and complexity properties. Numerical results show that, if the desired SINDR can only be achieved via joint combining across multiple BSs with properly tuned dithering, the optimal UE transmit power is imposed by the distance to the farthest serving BS (unlike in the unquantized case). In this context, dithering plays a crucial role in enhancing the SINDR, especially for UEs with significant path loss disparity among the serving BSs.
摘要
我们考虑了分布式巨量多输入多输出系统中的上行电力控制问题，其中基站（BS）具有1比特分析类比器（ADC）。我们首先考虑了单用户设备（UE）的情况，以获得对SNDR的深入理解。单一BS情况下，SNDR是单一函数UE传输电力。多个BS情况下，通过对每个BS添加适当的测量偏差，则SNDR在多BS联合器出口可以变成单一函数。因此，UE可以从多个BS中有效地获得服务，并且使用1比特ADC。对于多UE情况下的SINDR，我们寻找了对UE传输电力和BS中的测量偏差进行优化，以达到最小电力和最大最小SINDR的目标。为此，我们提出了三种不同的算法，每个算法具有不同的参数和复杂度。实验结果显示，如果只能通过多BS联合器实现所需的SINDR，则UE传输电力将被最远的服务BS的距离所限制（不同于不量化情况下）。在这种情况下，测量偏差在增强SINDR方面扮演至关重要的角色，特别是UE对服务BS的距离差异较大。
results: 在 discrete time 中 simulated 系统，使用 turbo coding 可以实现 bit-error-rate（BER）为 $10^{-5}$， average signal-to-noise ratio（SNR）为每比特接近 0 db。Abstract
Orthogonal frequency division multiplexing (OFDM) with offset quadrature amplitude modulation (OQAM) has been widely discussed in the literature and is considered a popular waveform for 5th generation (5G) wireless telecommunications and beyond. In this work, we show that OFDM-OQAM can be generated using the Hilbert transform and is equivalent to single sideband modulation (SSB), that has roots in analog telecommunications. The transmit filter for OFDM-OQAM is complex valued whose real part is given by the pulse corresponding to the root raised cosine spectrum and the imaginary part is the Hilbert transform of the real part. The real-valued digital information (message) are passed through the transmit filter and frequency division multiplexed on orthogonal subcarriers. The message bandwidth corresponding to each subcarrier is assumed to be narrow enough so that the channel can be considered ideal. Therefore, at the receiver, a matched filter can used to recover the message. Turbo coding is used to achieve bit-error-rate (BER) as low as $10^{-5}$ at an average signal-to-noise ratio (SNR) per bit close to 0 db. The system has been simulated in discrete time.
摘要
Orthogonal frequency division multiplexing (OFDM) with offset quadrature amplitude modulation (OQAM) 已经在文献中广泛讨论，被视为5代移动通信和更进一步的各种应用的流行的波形。在这个工作中，我们展示了OFDM-OQAM可以使用希尔伯特变换生成，与单边干扰模式（SSB）相当，这种模式在分析通信中有深根。发送器的滤波器为复数值，其实部分是根提高cosinuspectrum的脉冲，幂部分是希尔伯特变换实部。接收器使用匹配滤波器来回填消息。在接收器中，使用隐藏编码来实现 bit-error-rate（BER）在10^-5以下，均值信号响应（SNR）每比特接近0 db。系统在离散时间下进行了模拟。
Adaptive Unscented Kalman Filter under Minimum Error Entropy with Fiducial Points for Non-Gaussian Systems
results: 通过实验示例，表明提出的算法在面临复杂非泛解决方案中的噪声和异常测量数据处理中具有良好的稳定性和估计精度Abstract
The minimum error entropy (MEE) has been extensively used in unscented Kalman filter (UKF) to handle impulsive noises or abnormal measurement data in non-Gaussian systems. However, the MEE-UKF has poor numerical stability due to the inverse operation of singular matrix. In this paper, a novel UKF based on minimum error entropy with fiducial points (MEEF) is proposed \textcolor{black}{to improve the problem of non-positive definite key matrix. By adding the correntropy to the error entropy, the proposed algorithm further enhances the ability of suppressing impulse noise and outliers. At the same time, considering the uncertainty of noise distribution, the modified Sage-Husa estimator of noise statistics is introduced to adaptively update the noise covariance matrix. In addition, the convergence analysis of the proposed algorithm provides a guidance for the selection of kernel width. The robustness and estimation accuracy of the proposed algorithm are manifested by the state tracking examples under complex non-Gaussian noises.
摘要
“非标准几何系统中的访问频率（MEE）已经广泛使用在非标准 Kalman统计（UKF）中，以处理快速变化的数据或异常测量变量。但MEE-UKF具有对对称矩降的逆操作，导致严重的数值稳定问题。本文提出了一种基于MEE的新型UKF（MEEF），以解决这个问题。通过将correnticropy添加到错误熵中，提高了对于快速变化和偏差测量的抑制能力。同时，透过考虑随机变量的不确定性，引入修改的Sage-Husa估计器来适应更新随机矩降矩。此外，提出了修改了kernel宽度的选择指南，以确保算法的稳定性和准确性。实际应用中，提出的算法在复杂的非标准几何系统中进行了稳定追踪。”
AI-Native Transceiver Design for Near-Field Ultra-Massive MIMO: Principles and Techniques
results: 文章通过使用这两种框架，实现了近场UM-MIMO传输器的near-field beam focusing和频率域预测等功能，并且在多个关键性能指标上达到了显著的优势。Abstract
Ultra-massive multiple-input multiple-output (UM-MIMO) is a cutting-edge technology that promises to revolutionize wireless networks by providing an unprecedentedly high spectral and energy efficiency. The enlarged array aperture of UM-MIMO facilitates the accessibility of the near-field region, thereby offering a novel degree of freedom for communications and sensing. Nevertheless, the transceiver design for such systems is challenging because of the enormous system scale, the complicated channel characteristics, and the uncertainties in propagation environments. Therefore, it is critical to study scalable, low-complexity, and robust algorithms that can efficiently characterize and leverage the properties of the near-field channel. In this article, we will advocate two general frameworks from an artificial intelligence (AI)-native perspective, which are tailored for the algorithmic design of near-field UM-MIMO transceivers. Specifically, the frameworks for both iterative and non-iterative algorithms are discussed. Near-field beam focusing and channel estimation are presented as two tutorial-style examples to demonstrate the significant advantages of the proposed AI-native frameworks in terms of various key performance indicators.
摘要
ultra-massive多输入多输出（UM-MIMO）是一种最前线的技术，可以带来无 precedent的 spectral和能量效率。 UM-MIMO 的扩大数组天线可以访问近场区域，从而提供一种新的通信和感知的自由度。然而，UM-MIMO 的接收机设计具有巨大的系统规模，复杂的通道特性和传播环境的不确定性，因此需要研究可扩展、低复杂度和Robust的算法，以有效地描述和利用近场通道的特性。在这篇文章中，我们将提出两个总体框架，从人工智能（AI）原生的角度出发，用于near-field UM-MIMO 接收机的算法设计。具体来说，我们将讨论iterative和非iterative算法的框架。 near-field beam focusing和通道估计被用作两个教程风格的示例，以 Illustrate了我们提出的 AI-native 框架在不同的关键性能指标方面的显著优势。
A Covariance Adaptive Student’s t Based Kalman Filter
results: 本文的实验结果表明，使用GMM来更正TKF中测量噪声的covariance矩阵，可以提高TKF的精度和稳定性，并超过了传统的TKF。Abstract
In the classical Kalman filter(KF), the estimated state is a linear combination of the one-step predicted state and measurement state, their confidence level change when the prediction mean square error matrix and covariance matrix of measurement noise vary. The existing student's t based Kalman filter(TKF) works similarly to the way KF works, they both work well with impulse noise, but when it comes to Gaussian noise, TKF encounters an adjustment limit of the confidence level, this can lead to inaccuracies in such situations. This brief optimizes TKF by using the Gaussian mixture model(GMM), which generates a reasonable covariance matrix from the measurement noise to replace the one used in the existing algorithm and breaks the adjustment limit of the confidence level. At the end of the brief, the performance of the covariance adaptive student's t based Kalman filter(TGKF) is verified.
摘要
经 classical Kalman filter（KF），估计状态是一个线性组合于一步预测状态和测量状态，其信度水平随预测均值方差矩阵和测量噪声均值矩阵的变化而变化。现有的学生t基于Kalman filter（TKF）与KF相似，它们都能够处理冲击噪声，但在 Gaussian 噪声时，TKF会遇到信度水平调整限制，这可能导致准确性下降。本文优化TKF使用 Gaussian mixture model（GMM）生成测量噪声的合理协方差矩阵，并让信度水平不再受限制。文章结尾，covariance adaptive student's t based Kalman filter（TGKF）的性能得到了验证。
Multi-user beamforming in RIS-aided communications and experimental validations
results: 实验结果表明，在使用智能表面的情况下，系统的 Spectral Efficiency 提高了 13.48bps/Hz，对应的接收功率提高了 26.6dB和17.5dB。Abstract
Reconfigurable intelligent surface (RIS) is a promising technology for future wireless communications due to its capability of optimizing the propagation environments. Nevertheless, in literature, there are few prototypes serving multiple users. In this paper, we propose a whole flow of channel estimation and beamforming design for RIS, and set up an RIS-aided multi-user system for experimental validations. Specifically, we combine a channel sparsification step with generalized approximate message passing (GAMP) algorithm, and propose to generate the measurement matrix as Rademacher distribution to obtain the channel state information (CSI). To generate the reflection coefficients with the aim of maximizing the spectral efficiency, we propose a quadratic transform-based low-rank multi-user beamforming (QTLM) algorithm. Our proposed algorithms exploit the sparsity and low-rank properties of the channel, which has the advantages of light calculation and fast convergence. Based on the universal software radio peripheral devices, we built a complete testbed working at 5.8GHz and implemented all the proposed algorithms to verify the possibility of RIS assisting multi-user systems. Experimental results show that the system has obtained an average spectral efficiency increase of 13.48bps/Hz, with respective received power gains of 26.6dB and 17.5dB for two users, compared with the case when RIS is powered-off.
摘要
《可重配置智能表面（RIS）是未来无线通信技术的前景之一，因其可以优化传播环境。然而，在文献中，有很少的多用户体系。在这篇论文中，我们提出了渠道估计和扬射设计的整体流程，并设置了基于RIS的多用户系统 для实验验证。具体来说，我们将渠道简化步骤与通用简化消息传递算法（GAMP）相结合，并提议使用拉德美纳分布生成测量矩阵来获取渠道状态信息（CSI）。为了通过扬射矩阵来最大化спектル效率，我们提议使用quadratic transform-based low-rank multi-user beamforming（QTLM）算法。我们的提议算法利用渠道的稀疏和低级特性，具有轻量级计算和快速收敛的优点。基于通用软件无线通信外围设备，我们建立了工作在5.8GHz频率上的完整测试床，并实现了所有的提议算法，以验证RIS助け多用户系统的可能性。实验结果显示，系统在RIS启用下获得了平均spectral efficiency提高13.48bps/Hz，与RIS灭活时的相比，分别提高了接收功率26.6dB和17.5dB。
Energy-efficient Integrated Sensing and Communication System and DNLFM Waveform
for: 本研究旨在提高Integrated sensing and communication (ISAC)系统的能效性。
methods: 本文提出了针对ISAC系统的专门探测信号，并在探测和通信信号之间进行时频匹配窗口。此外，本文还提出了使用Discrete non-linear frequency modulation (DNLFM)来实现时间频率匹配和自适应窗口重量。
results: simulations 结果表明，提出的方法可以提高ISAC系统的能效性。Abstract
Integrated sensing and communication (ISAC) is a key enabler of 6G. Unlike communication radio links, the sensing signal requires to experience round trips from many scatters. Therefore, sensing is more power-sensitive and faces a severer multi-target interference. In this paper, the ISAC system employs dedicated sensing signals, which can be reused as the communication reference signal. This paper proposes to add time-frequency matched windows at both the transmitting and receiving sides, which avoids mismatch loss and increases energy efficiency. Discrete non-linear frequency modulation (DNLFM) is further proposed to achieve both time-domain constant modulus and frequency-domain arbitrary windowing weights. DNLFM uses very few Newton iterations and a simple geometrically-equivalent method to generate, which greatly reduces the complex numerical integral in the conventional method. Moreover, the spatial-domain matched window is proposed to achieve low sidelobes. The simulation results show that the proposed methods gain a higher energy efficiency than conventional methods.
摘要
integration of sensing and communication (ISAC) is a key enabler of 6G. Unlike communication radio links, the sensing signal requires to experience round trips from many scatters. Therefore, sensing is more power-sensitive and faces a severer multi-target interference. In this paper, the ISAC system employs dedicated sensing signals, which can be reused as the communication reference signal. This paper proposes to add time-frequency matched windows at both the transmitting and receiving sides, which avoids mismatch loss and increases energy efficiency. Discrete non-linear frequency modulation (DNLFM) is further proposed to achieve both time-domain constant modulus and frequency-domain arbitrary windowing weights. DNLFM uses very few Newton iterations and a simple geometrically-equivalent method to generate, which greatly reduces the complex numerical integral in the conventional method. Moreover, the spatial-domain matched window is proposed to achieve low sidelobes. The simulation results show that the proposed methods gain a higher energy efficiency than conventional methods.Here's the text in Traditional Chinese if you prefer:integration of sensing and communication (ISAC) is a key enabler of 6G. Unlike communication radio links, the sensing signal requires to experience round trips from many scatters. Therefore, sensing is more power-sensitive and faces a severer multi-target interference. In this paper, the ISAC system employs dedicated sensing signals, which can be reused as the communication reference signal. This paper proposes to add time-frequency matched windows at both the transmitting and receiving sides, which avoids mismatch loss and increases energy efficiency. Discrete non-linear frequency modulation (DNLFM) is further proposed to achieve both time-domain constant modulus and frequency-domain arbitrary windowing weights. DNLFM uses very few Newton iterations and a simple geometrically-equivalent method to generate, which greatly reduces the complex numerical integral in the conventional method. Moreover, the spatial-domain matched window is proposed to achieve low sidelobes. The simulation results show that the proposed methods gain a higher energy efficiency than conventional methods.
Improving Axial Resolution of Optical Resolution Photoacoustic Microscopy with Advanced Frequency Domain Eigenspace Based Minimum Variance Beamforming Method
results: 对于25MHz OR-PAM系统，我们发现了axial point spread function的半峰宽度从69.3μm降低到16.89μm，表明了axial resolution的显著提高。Abstract
Optical resolution photoacoustic microscopy (OR-PAM) leverages optical focusing and acoustic detection for microscopic optical absorption imaging. Intrinsically it owns high optical lateral resolution and poor acoustic axial resolution. Such anisometric resolution hinders good 3-D visualization; thus 2-D maximum amplitude projection images are commonly presented in the literature. Since its axial resolution is limited by the bandwidth of acoustic detectors, ultrahigh frequency, and wideband detectors with Wiener deconvolution have been proposed to address this issue. Nonetheless, they also introduce other issues such as severe high-frequency attenuation and limited imaging depth. In this work, we view axial resolution improvement as an axial signal reconstruction problem, and the axial resolution degradation is caused by axial sidelobe interference. We propose an advanced frequency-domain eigenspace-based minimum variance (F-EIBMV) beamforming technique to suppress axial sidelobe interference and noises. This method can simultaneously enhance the axial resolution and contrast of OR-PAM. For a 25-MHz OR-PAM system, the full-width at half-maximum of an axial point spread function decreased significantly from 69.3 $\mu$m to 16.89 $\mu$m, indicating a significant improvement in axial resolution.
摘要