results: 在实际办公室enario中，单个小型基站的均值Signal-to-Noise Ratio提高8.50 dB，单个小型基站的均值吞吐量提高4.36 Mbps，四个小型基站的均值吞吐量提高3.19 Mbps。Abstract
We present the design and implementation of WaveFlex, the first smart surface that enhances Private LTE/5G networks operating under the shared-license framework in the Citizens Broadband Radio Service frequency band. WaveFlex works in the presence of frequency diversity: multiple nearby base stations operating on different frequencies, as dictated by a Spectrum Access System coordinator. It also handles time dynamism: due to the dynamic sharing rules of the band, base stations occasionally switch channels, especially when priority users enter the network. Finally, WaveFlex operates independently of the network itself, not requiring access to nor modification of the base station or mobile users, yet it remain compliant with and effective on prevailing cellular protocols. We have designed and fabricated WaveFlex on a custom multi-layer PCB, software defined radio-based network monitor, and supporting control software and hardware. Our experimental evaluation benchmarks an operational Private LTE network running at full line rate. Results demonstrate an 8.50 dB average SNR gain, and an average throughput gain of 4.36 Mbps for a single small cell, and 3.19 Mbps for four small cells, in a realistic indoor office scenario.
摘要
我们介绍了waveflex的设计和实现，这是首个在公民宽频服务频率带下的智能表面，用于增强共享许可的LTE/5G网络。waveflex在频率多样性和时间动态性下工作，包括多个附近基站在不同频率上运行，由 спект域访问系统协调员指定。此外，waveflex不需要访问或修改基站或移动用户，却仍然遵循现有的 celullar协议。我们设计了waveflex于自定义多层PCB、基于Software Defined Radio的网络监测器和相应的控制软件和硬件。我们的实验评估表明，一个实际的专用LTE网络在全线速度下运行，得到了8.50 dB的平均噪声比提高和4.36 Mbps的平均吞吐量提高，以及3.19 Mbps的平均吞吐量提高，在一个真实的办公室enario中。
Integrated Sensing and Channel Estimation by Exploiting Dual Timescales for Delay-Doppler Alignment Modulation
for: This paper proposes a novel ISAC framework that leverages the recently proposed delay-Doppler alignment modulation (DDAM) technique to improve the performance of integrated sensing and communication (ISAC) systems.
methods: The proposed framework uses a novel algorithm called adaptive simultaneously orthogonal matching pursuit with support refinement (ASOMP-SR) for joint environment sensing and PSI estimation, and analyzes the performance of DDAM with imperfectly sensed PSI.
results: Simulation results show that the proposed DDAM-based ISAC can achieve superior spectral efficiency and a reduced peak-to-average power ratio (PAPR) compared to standard orthogonal frequency division multiplexing (OFDM).Here’s the simplified Chinese text:
methods: 该系统使用了一种新的算法 called adaptive simultaneously orthogonal matching pursuit with support refinement（ASOMP-SR）进行环境感知和PSI估计，并分析了受到不准确感知PSI的DDAM性能。
results: 实验结果表明，提出的DDAM-based ISAC可以在spectral efficiency和peak-to-average power ratio（PAPR）方面具有superior性能，比普通的orthogonal frequency division multiplexing（OFDM）更高。Abstract
For integrated sensing and communication (ISAC) systems, the channel information essential for communication and sensing tasks fluctuates across different timescales. Specifically, wireless sensing primarily focuses on acquiring path state information (PSI) (e.g., delay, angle, and Doppler) of individual multi-path components to sense the environment, which usually evolves much more slowly than the composite channel state information (CSI) required for communications. Typically, the CSI is approximately unchanged during the channel coherence time, which characterizes the statistical properties of wireless communication channels. However, this concept is less appropriate for describing that for wireless sensing. To this end, in this paper, we introduce a new timescale to study the variation of the PSI from a channel geometric perspective, termed path invariant time, during which the PSI largely remains constant. Our analysis indicates that the path invariant time considerably exceeds the channel coherence time. Thus, capitalizing on these dual timescales of the wireless channel, in this paper, we propose a novel ISAC framework exploiting the recently proposed delay-Doppler alignment modulation (DDAM) technique. Different from most existing studies on DDAM that assume the availability of perfect PSI, in this work, we propose a novel algorithm, termed as adaptive simultaneously orthogonal matching pursuit with support refinement (ASOMP-SR), for joint environment sensing and PSI estimation. We also analyze the performance of DDAM with imperfectly sensed PSI.Simulation results unveil that the proposed DDAM-based ISAC can achieve superior spectral efficiency and a reduced peak-to-average power ratio (PAPR) compared to standard orthogonal frequency division multiplexing (OFDM).
摘要
for integrated sensing and communication (ISAC) systems, the channel information that is essential for communication and sensing tasks changes over different time scales. Specifically, wireless sensing primarily focuses on acquiring path state information (PSI) (e.g., delay, angle, and Doppler) of individual multi-path components to sense the environment, which usually evolves much more slowly than the composite channel state information (CSI) required for communications. Typically, the CSI is approximately unchanged during the channel coherence time, which characterizes the statistical properties of wireless communication channels. However, this concept is less appropriate for describing that for wireless sensing. To this end, in this paper, we introduce a new timescale to study the variation of the PSI from a channel geometric perspective, termed path invariant time, during which the PSI largely remains constant. Our analysis indicates that the path invariant time considerably exceeds the channel coherence time. Thus, capitalizing on these dual timescales of the wireless channel, in this paper, we propose a novel ISAC framework exploiting the recently proposed delay-Doppler alignment modulation (DDAM) technique. Different from most existing studies on DDAM that assume the availability of perfect PSI, in this work, we propose a novel algorithm, termed as adaptive simultaneously orthogonal matching pursuit with support refinement (ASOMP-SR), for joint environment sensing and PSI estimation. We also analyze the performance of DDAM with imperfectly sensed PSI.Simulation results unveil that the proposed DDAM-based ISAC can achieve superior spectral efficiency and a reduced peak-to-average power ratio (PAPR) compared to standard orthogonal frequency division multiplexing (OFDM).Here's the word-for-word translation in Simplified Chinese:for 集成感知通信 (ISAC) 系统，通信和感知任务中的通道信息变化在不同的时间尺度上。特别是无线感知主要关注于获取路径状态信息 (PSI)（例如延迟、角度和Doppler）个体多 path 组件来感知环境，这通常比通信通道的Statistical properties 更慢地发展。通常情况下，通道准确性时间内，通信通道的 CSI 保持相对不变。但这个概念对于无线感知来说 less appropriate。为此，在这篇论文中，我们引入了一个新的时间尺度，用于研究 wireless channel 的 PSI 变化，并将其称为 path invariant time， durante el cual la PSI se mantiene prácticamente constante。我们的分析表明，path invariant time 远大于通道准确性时间。因此，基于这两个时间尺度的 wireless channel，在这篇论文中，我们提出了一种新的 ISAC 框架，利用最近提出的 delay-Doppler alignment modulation (DDAM) 技术。与大多数现有研究中的 DDAM 假设完美 PSI 可用，在这种工作中，我们提出了一种新的算法，称为 adaptive simultaneously orthogonal matching pursuit with support refinement (ASOMP-SR)，用于joint 环境感知和 PSI 估计。我们还分析了 DDAM 中的 PSI 估计不准确情况。Simulation results 显示，我们的提议的 DDAM-based ISAC 可以在 spectral efficiency 和 peak-to-average power ratio (PAPR) 两个方面获得更高的性能，相比标准 orthogonal frequency division multiplexing (OFDM)。
Imaging of nonlinear materials via the Monotonicity Principle
results: 研究提供了一些初步结果，并给出了一些扩展的数值示例。Abstract
The topic of inverse problems, related to Maxwell's equations, in the presence of nonlinear materials is quite new in literature. The lack of contributions in this area can be ascribed to the significant challenges that such problems pose. Retrieving the spatial behaviour of some unknown physical property, starting from boundary measurements, is a nonlinear and highly ill-posed problem even in the presence of linear materials. And the complexity exponentially grows when the focus is on nonlinear material properties. Recently, the Monotonicity Principle has been extended to nonlinear materials under very general assumptions. Starting from the theoretical background given by this extension, we develop a first real-time inversion method for the inverse obstacle problem in the presence of nonlinear materials. The Monotonicity Principle is the foundation of a class of non-iterative algorithms for tomography of linear materials. It has been successfully applied to various problems, governed by different PDEs. In the linear case, MP based inversion methods ensure excellent performances and compatibility with real-time applications. We focus on problems governed by elliptical PDEs and, as an example of application, we treat the Magnetostatic Permeability Tomography problem, in which the aim is to retrieve the spatial behaviour of magnetic permeability through boundary measurements in DC operations. In this paper, we provide some preliminary results giving the foundation of our method and extended numerical examples.
摘要
topic of inverse problems related to Maxwell's equations in the presence of nonlinear materials is quite new in literature. lack of contributions in this area can be ascribed to the significant challenges that such problems pose. Retrieving the spatial behavior of some unknown physical property starting from boundary measurements is a nonlinear and highly ill-posed problem even in the presence of linear materials. And the complexity exponentially grows when the focus is on nonlinear material properties. Recently, the Monotonicity Principle has been extended to nonlinear materials under very general assumptions. Starting from the theoretical background given by this extension, we develop a first real-time inversion method for the inverse obstacle problem in the presence of nonlinear materials. Monotonicity Principle is the foundation of a class of non-iterative algorithms for tomography of linear materials. It has been successfully applied to various problems, governed by different PDEs. In the linear case, MP-based inversion methods ensure excellent performances and compatibility with real-time applications. We focus on problems governed by elliptical PDEs and, as an example of application, we treat the Magnetostatic Permeability Tomography problem, in which the aim is to retrieve the spatial behavior of magnetic permeability through boundary measurements in DC operations. In this paper, we provide some preliminary results giving the foundation of our method and extended numerical examples.
Complex Number Assignment in the Topology Method for Heartbeat Interval Estimation Using Millimeter-Wave Radar
results: 验证了使用简化的波峰值特征点预测优化复杂数字分配方法的有效性，并使用公共数据集进行了验证。Abstract
The topology method is an algorithm for accurate estimation of instantaneous heartbeat intervals using millimeter-wave radar signals. In this model, feature points are extracted from the skin displacement waveforms generated by heartbeats and a complex number is assigned to each feature point. However, these numbers have been assigned empirically and without solid justification. This study used a simplified model of displacement waveforms to predict the optimal choice of the complex number assignments to feature points corresponding to inflection points, and the validity of these numbers was confirmed using analysis of a publicly available dataset.
摘要
“扁平方法”是一种用于精确计算心跳间隔的毫米波激光信号中的算法。在这个模型中，从心跳所导致皮肤变形波形中提取特征点，然后将每个特征点分配到复数中。但是这些复数的分配是基于实践和无对Solid的说明。这个研究使用简化的变形波形来预测最佳的复数分配，并使用公共可用数据集进行验证。
Intelligent Resource Allocation for UAV-Based Cognitive NOMA Networks: An Active Inference Approach
paper_authors: Felix Obite, Ali Krayani, Atm S. Alam, Lucio Marcenaro, Arumugam Nallanathan, Carlo Regazzoni for:This paper aims to improve the adaptive resource allocation and decision-making of future wireless networks, specifically in the context of uplink UAV-based cognitive NOMA networks.methods:The proposed approach uses an active inference-based learning framework, rooted in cognitive neuroscience, to solve the complex problem of joint subchannel and power allocation. This involves creating a training dataset using random or iterative methods, training a mobile UAV offline to learn a generative model of discrete subchannels and continuous power allocation, and using this model for online inference.results:The proposed approach is validated through numerical simulations, which show efficient performance compared to suboptimal baseline schemes. The approach is able to adapt to non-stationary environments and improve the cumulative sum rate by jointly optimizing the subchannel and power allocation based on the UAV’s mobility at each time step.Abstract
Future wireless networks will need to improve adaptive resource allocation and decision-making to handle the increasing number of intelligent devices. Unmanned aerial vehicles (UAVs) are being explored for their potential in real-time decision-making. Moreover, cognitive non-orthogonal multiple access (Cognitive-NOMA) is envisioned as a remedy to address spectrum scarcity and enable massive connectivity. This paper investigates the design of joint subchannel and power allocation in an uplink UAV-based cognitive NOMA network. We aim to maximize the cumulative sum rate by jointly optimizing the subchannel and power allocation based on the UAV's mobility at each time step. This is often formulated as an optimization problem with random variables. However, conventional optimization algorithms normally introduce significant complexity, and machine learning methods often rely on large but partially representative datasets to build solution models, assuming stationary testing data. Consequently, inference strategies for non stationary events are often overlooked. In this study, we introduce a novel active inference-based learning approach, rooted in cognitive neuroscience, to solve this complex problem. The framework involves creating a training dataset using random or iterative methods to find suboptimal resource allocations. This dataset trains a mobile UAV offline, enabling it to learn a generative model of discrete subchannels and continuous power allocation. The UAV then uses this model for online inference. The method incrementally derives new generative models from training data by identifying dynamic equilibrium conditions between required actions and variables, represented within a unique dynamic Bayesian network. The proposed approach is validated through numerical simulations, showing efficient performance compared to suboptimal baseline schemes.
摘要
未来无线网络将需要改进适应性资源分配和决策，以满足智能设备的增加。无人机（UAV）正被研究，以其实时决策的潜在优势。此外，认知非对称多接入（Cognitive-NOMA）被视为spectrum scarcity和大规模连接问题的解决方案。本文研究了基于无人机的上行UAV认知多接入网络的共同子频率和功率分配的设计。我们希望通过在每个时间步骤中并行优化子频率和功率分配，以最大化总带宽率。这经常被формализова为随机变量的优化问题。然而，常见的优化算法通常会引入显著的复杂性，而机器学习方法通常需要大量但部分代表性的数据来建立解决方案模型，假设测试数据是静止的。因此，对非静态事件的推理策略通常被忽略。在本研究中，我们提出了一种新的活动推理学习方法，基于认知神经科学，解决这个复杂的问题。该框架包括使用随机或迭代方法创建训练数据集，该数据集用于在线推理。无人机使用该模型在线进行推理，并在训练数据中逐渐 derivation of new generative models from training data by identifying dynamic equilibrium conditions between required actions and variables, represented within a unique dynamic Bayesian network. The proposed approach is validated through numerical simulations, showing efficient performance compared to suboptimal baseline schemes.
Aerial-Aided mmWave VANETs Using NOMA: Performance Analysis, Comparison, and Insights
paper_authors: Abdullah Abu Zaid, Baha Eddine Youcef Belmekki, Mohamed-Slim Alouini
for: 这 paper 的目的是研究在协同交通网络 (VANET) 中使用缔结的飞行平台 (NTFP) 来解决城市化导致的问题。
methods: 这 paper 使用 Stochastic Geometry 工具来 derive 缔结平台的停机概率和可以达到的速率表达。
results: 研究结果显示，当 NTFP 作为中继器时，它们在较大的传输距离上表现更好于 traditional roadside units (RSUs)，但是在短距离上，RSUs 表现更好。此外，使用非对称访问 (NOMA) 可以提高spectrum 效率，并且在 millimeter-wave (mmWave) 频率上使用 сектор化扫描模型可以提高数据速率。Abstract
In this paper, we propose the integration of tethered flying platforms in cooperative vehicular ad hoc networks (VANETs) to alleviate the problems of rapid urbanization. In this context, we study the performance of VANETs by deriving approximate outage probability and average achievable rate expressions using tools from stochastic geometry. We compare between the usage of networked tethered flying platforms (NTFPs) and traditional roadside units (RSUs). On the other hand, the rapid increase of smart devices in vehicles and the upcoming urban air mobility (UAM) vision will congest the spectrum and require increased data rates. Hence, we use non-orthogonal multiple access (NOMA) to improve spectral efficiency and compare its performance to orthogonal access schemes. Furthermore, we utilize millimeter-wave (mmWave) frequencies for high data rates and implement a sectored beamforming model. We extensively study the system using three transmission schemes: direct, relay, and hybrid transmission. The results show that when acting as relays, NTFPs outperform RSUs for larger distances between the transmitting and the receiving vehicles, while RSUs outperform NTFPs for short distances. However, NTFPs are the best solution when acting as a source. Moreover, we find that, in most cases, direct transmission is preferred to achieve a high rate compared to other schemes. Finally, the results are summarized in two tables that provide insights into connecting VANETs by selecting the most suitable platform and type of communication for a given set of parameters, configurations, and requirements.
摘要
在这篇论文中，我们提出了在合作式自适应网络（VANET）中 integrate 固定飞行平台（NTFP）以解决城市化导致的问题。在这个上下文中，我们研究了VANET的性能，通过Stochastic Geometry工具 derive approximate outage probability 和 average achievable rate 表达。我们比较了使用网络化固定飞行平台（NTFP）和传统路边单元（RSU）。而随着智能设备的增加和未来城市空中交通（UAM）的出现，将导致频率受到压力，需要增加数据速率。因此，我们使用非对称多接入（NOMA）提高频率效率，并与对称访问方案进行比较。此外，我们使用毫米波频率（mmWave）频率获得高数据速率，并实施 сектор化扫描模型。我们广泛研究了系统，使用三种传输方案：直接传输、重复传输和混合传输。结果表明，当NTFP作为中继器时，NTFP在较远的传输和接收车辆之间表现更好，而RSU在短距离之间表现更好。然而，NTFP在源位置时是最佳解决方案。此外，我们发现，在大多数情况下，直接传输是以高速度相比其他方案更好。最后，结果分表两个表格，提供了关于连接VANET的最佳平台和通信方式的准确信息，以便根据不同的参数、配置和需求选择最适合的方案。
A Tutorial on Near-Field XL-MIMO Communications Towards 6G
results: 本论文通过对XL-MIMO技术的近场模型和性能分析，提出了新的信号噪响比例法则、焊焊范围模式、可达性和度量（DoF）等。此外，论文还详细介绍了各种XL-MIMO设计问题，如近场ibeam代码库、焊焊训练、通道估计和延迟对齐变换（DAM）传输。Abstract
Extremely large-scale multiple-input multiple-output (XL-MIMO) is a promising technology for the sixth-generation (6G) mobile communication networks. By significantly boosting the antenna number or size to at least an order of magnitude beyond current massive MIMO systems, XL-MIMO is expected to unprecedentedly enhance the spectral efficiency and spatial resolution for wireless communication. The evolution from massive MIMO to XL-MIMO is not simply an increase in the array size, but faces new design challenges, in terms of near-field channel modelling, performance analysis, channel estimation, and practical implementation. In this article, we give a comprehensive tutorial overview on near-field XL-MIMO communications, aiming to provide useful guidance for tackling the above challenges. First, the basic near-field modelling for XL-MIMO is established, by considering the new characteristics of non-uniform spherical wave (NUSW) and spatial non-stationarity. Next, based on the near-field modelling, the performance analysis of XL-MIMO is presented, including the near-field signal-to-noise ratio (SNR) scaling laws, beam focusing pattern, achievable rate, and degrees-of-freedom (DoF). Furthermore, various XL-MIMO design issues such as near-field beam codebook, beam training, channel estimation, and delay alignment modulation (DAM) transmission are elaborated. Finally, we point out promising directions to inspire future research on near-field XL-MIMO communications.
摘要
“极大规模多输入多输出（XL-MIMO）技术是6G移动通信网络的未来技术之一。它通过增加天线数或大小，至少一个量级超过当前庞大MIMO系统，可以无 precedent 地提高spectral efficiency和空间分辨率，以提高无线通信的性能。从庞大MIMO到XL-MIMO的演化不仅是天线数或大小的增加，而且面临新的设计挑战，包括近场通道模型、性能分析、通道估计和实践实现。本文提供了XL-MIMO近场通信的完整教程详细介绍，以便对这些挑战进行有用的指导。首先，我们建立了XL-MIMO近场模型，考虑了新的非均匀球波（NUSW）和空间非站点性。然后，基于近场模型，我们提供了XL-MIMO性能分析，包括近场信噪比（SNR）扩展律、扫描 Pattern、可达率和度量（DoF）。此外，我们还详细介绍了XL-MIMO设计问题，如近场天线代码库、天线训练、通道估计和延迟对齐模ulation（DAM）传输。最后，我们指出了未来研究XL-MIMO近场通信的可能的方向。”
Channel Autocorrelation Estimation for IRS-Aided Wireless Communications Based on Power Measurements
results: 验证了新的通道估计算法的有效性，以及基于估计的IRS投射设计。Abstract
Intelligent reflecting surface (IRS) can bring significant performance enhancement for wireless communication systems by reconfiguring wireless channels via passive signal reflection. However, such performance improvement generally relies on the knowledge of channel state information (CSI) for IRS-associated links. Prior IRS channel estimation strategies mainly estimate IRS-cascaded channels based on the excessive pilot signals received at the users/base station (BS) with time-varying IRS reflections, which, however, are not compatible with the existing channel training/estimation protocol for cellular networks. To address this issue, we propose in this paper a new channel estimation scheme for IRS-assisted communication systems based on the received signal power measured at the user, which is practically attainable without the need of changing the current protocol. Specifically, due to the lack of signal phase information in power measurements, the autocorrelation matrix of the BS-IRS-user cascaded channel is estimated by solving equivalent matrix-rank-minimization problems. Simulation results are provided to verify the effectiveness of the proposed channel estimation algorithm as well as the IRS passive reflection design based on the estimated channel autocorrelation matrix.
摘要
智能反射表面（IRS）可以带来无线通信系统的性能提升，通过通过pasive signal reflection重新配置无线通道。然而，这种性能提升通常需要IRS相关链路的通道状态信息（CSI）的知识。先前的IRS通道估计策略主要基于用户/基站（BS）接收到的过剩的射频信号来估计IRS-堆叠的通道，这些信号在时间变化IRS反射后是不可靠的。为解决这个问题，我们在这篇论文中提出了一种新的通道估计方案 дляIRS协助通信系统，基于用户接收到的信号功率。具体来说，由于射频信号的相位信息不可获得，我们通过解决相当于矩阵约等减少问题来估计BS-IRS-用户堆叠通道的自相关矩阵。我们提供了估计算法的实验结果，以证明提案的有效性以及基于估计的IRS pasive反射设计。
Spectral-Efficiency and Energy-Efficiency of Variable-Length XP-HARQ
paper_authors: Jiahui Feng, Zheng Shi, Yaru Fu, Hong Wang, Guanghua Yang, Shaodan Ma for:* 提高通信的spectral efficiency (SE)和能效率 (EE)methods:* 提出变量长度跨包 hybrid automatic repeat request (VL-XP-HARQ) 技术* 使用 Dinkelbach 变换和successive convex approximation (SCA) 等方法进行优化results:* 提高 SE 和 EE 的Upper bound* 可以通过power allocation来最大化 EE 并保证出错率的要求Abstract
A variable-length cross-packet hybrid automatic repeat request (VL-XP-HARQ) is proposed to boost the spectral efficiency (SE) and the energy efficiency (EE) of communications. The SE is firstly derived in terms of the outage probabilities, with which the SE is proved to be upper bounded by the ergodic capacity (EC). Moreover, to facilitate the maximization of the SE, the asymptotic outage probability is obtained at high signal-to-noise ratio (SNR), with which the SE is maximized by properly choosing the number of new information bits while guaranteeing outage requirement. By applying Dinkelbach's transform, the fractional objective function is transformed into a subtraction form, which can be decomposed into multiple sub-problems through alternating optimization. By noticing that the asymptotic outage probability is a convex function, each sub-problem can be easily relaxed to a convex problem by adopting successive convex approximation (SCA). Besides, the EE of VL-XP-HARQ is also investigated. An upper bound of the EE is found and proved to be attainable. Furthermore, by aiming at maximizing the EE via power allocation while confining outage within a certain constraint, the methods to the maximization of SE are invoked to solve the similar fractional problem. Finally, numerical results are presented for verification.
摘要
一种变长跨包自动重复请求（VL-XP-HARQ）被提议，以提高通信的spectral efficiency（SE）和能效率（EE）。首先，SE是通过出现概率来 derivation，并证明其Upper bounded by ergodic capacity（EC）。此外，为了最大化SE，高信号噪声比（SNR）下的 asymptotic outage probability 被获得，并通过选择合适的新信息位数来 garantuee outage requirement。通过应用Dinkelbach的变换，目标函数被转换成一个减法表示，可以通过 alternate optimization 分解成多个子问题。由于 asymptotic outage probability 是一个 convex function，每个子问题可以通过Successive convex approximation（SCA）的方式放松到一个convex problem。此外，EE 的Upper bound 也被查找并证明可达。进一步，通过对力分配来最大化EE，并将出现约束在一定范围内，使用SE 的最大化方法来解决相似的分数问题。最后，通过numerical results 进行验证。
paper_authors: Boqun Zhao, Chongjun Ouyang, Xingqi Zhang, Yuanwei Liu for:* 这个论文是为了研究Integrated Sensing and Communications（ISAC）在靠近场区域中的性能，并提出了一个更加准确的通道模型。methods:* 该论文使用了一种基于效果天线的评估模型，并分析了下降和上升方向的感知和通信性能。results:* 论文显示，随着天线数量的增加，提出的模型的感知率和通信率都会 converges to常数，而传统的TCMs则会无限增长；* ISAC在靠近场区域中可以 achieve 更广泛的速率区域，比传统的频分S&C更好。Abstract
The technical trends for the next-generation wireless network significantly extend the near-field region, necessitating a reevaluation for the performance of integrated sensing and communications (ISAC) to account for the effects introduced by the near field. In this paper, a near-field ISAC framework is proposed with a more accurate channel model than the three conventional models (TCMs): uniform plane wave, uniform spherical wave, and non-uniform spherical wave, in which the effective aperture of the antenna is considered. Based on the proposed model, sensing and communication (S&C) performance in both downlink and uplink scenarios are analyzed. For the downlink case, three distinct designs are studied: the communications-centric (C-C) design, the sensing-centric (S-C) design, and the Pareto optimal design. Regarding the uplink case, the C-C design, the S-C design and the time-sharing strategy are considered. Within each design, sensing rates (SRs) and communication rates (CRs) are derived. To gain further insights, high signal-to-noise ratio slopes and rate scaling laws concerning the number of antennas are also examined. Finally, the attainable SR-CR regions of the near-field ISAC are characterized. Numerical results reveal that 1) as the number of antennas grows, the SRs and CRs of the proposed model converges to constants, while those of the TCMs increase unboundedly; 2) ISAC achieves a more extensive rate region than the conventional frequency-division S&C in both downlink and uplink cases.
摘要
Next-generation无线网络的技术趋势明显扩展了近场区域，需要重新评估Integrated Sensing and Communications（ISAC）性能，考虑近场效应的影响。本文提出了一种更准确的近场ISAC框架，包括Antenna的有效覆盖面。基于该模型，对下行和上行场景进行了敏感测量和通信性能的分析。在下行场景中，研究了三种设计：通信中心（C-C）设计、探测中心（S-C）设计和Pareto优化设计。在上行场景中，考虑了C-C设计、S-C设计和时间分享策略。对每种设计，计算了探测率（SR）和通信率（CR）。为了更深入地了解，也研究了高信号噪听比斜率和antenna数量下的速率扩展法则。最后，near-field ISAC可达的SR-CR区域的可行性被Characterized。numerical results indicate that: 1) antenna数量增加时，提posed模型中的SR和CR与TCMs相比， converge to constants,而TCMs中的SR和CR无限增长; 2) ISAC在下行和上行场景中都可以获得更广泛的速率区域，比传统频分S&C更好。
Reuse Kernels or Activations? A Flexible Dataflow for Low-latency Spectral CNN Acceleration
results: 在一个现代FPGA平台上，我们的设计可以减少数据传输量42%，使DSP资源利用率达到90%，并实现VGG16模型的推理延迟为9毫秒，比基eline状态则的延迟为68毫秒更快。Abstract
Spectral-domain CNNs have been shown to be more efficient than traditional spatial CNNs in terms of reducing computation complexity. However they come with a `kernel explosion' problem that, even after compression (pruning), imposes a high memory burden and off-chip bandwidth requirement for kernel access. This creates a performance gap between the potential acceleration offered by compression and actual FPGA implementation performance, especially for low-latency CNN inference. In this paper, we develop a principled approach to overcoming this performance gap and designing a low-latency, low-bandwidth, spectral sparse CNN accelerator on FPGAs. First, we analyze the bandwidth-storage tradeoff of sparse convolutional layers and locate communication bottlenecks. We then develop a dataflow for flexibly optimizing data reuse in different layers to minimize off-chip communication. Finally, we propose a novel scheduling algorithm to optimally schedule the on-chip memory access of multiple sparse kernels and minimize read conflicts. On a state-of-the-art FPGA platform, our design reduces data transfers by 42\% with DSP utilization up to 90\% and achieves inference latency of 9 ms for VGG16, compared to the baseline state-of-the-art latency of 68 ms.
摘要
In this paper, we develop a principled approach to overcoming this performance gap and designing a low-latency, low-bandwidth, spectral sparse CNN accelerator on FPGAs. First, we analyze the bandwidth-storage tradeoff of sparse convolutional layers and locate communication bottlenecks. We then develop a dataflow for flexibly optimizing data reuse in different layers to minimize off-chip communication. Finally, we propose a novel scheduling algorithm to optimally schedule the on-chip memory access of multiple sparse kernels and minimize read conflicts.Our design reduces data transfers by 42% with DSP utilization up to 90% and achieves inference latency of 9 ms for VGG16, compared to the baseline state-of-the-art latency of 68 ms.