paper_authors: Zhaolin Wang, Xidong Mu, Yuanwei Liu
for: 提出了一种新的近场速度测量概念，可以同时测量目标在运动过程中的径向和横向速度。
methods: 提出了基于最大可能性估计的方法，用于同时估计径向和横向速度的echo信号。
results: 通过帮助近场速度测量，提出了一种无需频率估计的预测扩散框架，实现了无间断的数据传输。数值示例验证了该方法的有效性。Abstract
The novel concept of near-field velocity sensing is proposed. In contrast to far-field velocity sensing, near-field velocity sensing enables the simultaneous estimation of both radial and transverse velocities of a moving target. A maximum-likelihood-based method is proposed for jointly estimating the radial and transverse velocities from the echo signals. Assisted by near-field velocity sensing, a predictive beamforming framework is proposed for a moving communication user, which requires no channel estimation but achieves seamless data transmission. Finally, numerical examples validate the proposed approaches.
摘要
新的概念——近场速度测量被提出。与远场速度测量相比，近场速度测量可同时测量移动目标的径向和横向速度。基于最大可能性的方法被提议用于同时估计径向和横向速度的echo信号。帮助了近场速度测量，一种预测扩散框架被提议用于移动通信用户，不需 Channel estimation，但可实现无缝数据传输。最后，数值示例证明了提出的方法。Here's the word-for-word translation:新的概念——近场速度测量被提出，与远场速度测量相比，近场速度测量可同时测量移动目标的径向和横向速度。基于最大可能性的方法被提议用于同时估计径向和横向速度的echo信号。帮助了近场速度测量，一种预测扩散框架被提议用于移动通信用户，不需 Channel estimation，但可实现无缝数据传输。最后，数值示例证明了提出的方法。
Wireless rf sensor with dual sensing capability for ionic solution and target dielectric objects
results: 具有唯一的设计，使其不受周围环境影响Abstract
A novel microstrip-based sensor designed for detecting changes in ionic content of water and the addition of solid contaminant objects is presented. The sensor can be installed on the exterior wall of dielectric containers and customized according to the material of the container to enable wireless sensing. It's operation within the lower microwave frequency range (670 to 730 MHz) serves to minimize signal attenuation in water and streamlines circuitry design. The most significant feature of this sensor is its unique design, rendering it impervious to its surrounding environment.
摘要
一种新型微带式感测器，用于检测水中离子含量的变化以及固体杂质物的添加，被介绍。该感测器可以安装在dielectric容器外墙上，并可以根据容器材料进行个性化定制，以实现无线感测。它的运作频率范围为670-730MHz，以便在水中减少信号强度抑制，同时简化电路设计。该感测器的最重要特点是它独特的设计，使其不受周围环境影响。Here's the breakdown of the translation:* 一种新型微带式感测器 (a new type of microstrip-based sensor)* 用于检测水中离子含量的变化 (for detecting changes in ionic content of water)* 以及固体杂质物的添加 (and the addition of solid contaminant objects)* 被介绍 (being introduced)* 该感测器可以安装在dielectric容器外墙上 (the sensor can be installed on the exterior wall of dielectric containers)* 并可以根据容器材料进行个性化定制 (and can be customized according to the material of the container)* 以实现无线感测 (to achieve wireless sensing)* 它的运作频率范围为670-730MHz (its operating frequency range is 670-730MHz)* 以便在水中减少信号强度抑制 (to reduce signal attenuation in water)* 同时简化电路设计 (while simplifying circuitry design)* 该感测器的最重要特点是它独特的设计 (the most important feature of the sensor is its unique design)* 使其不受周围环境影响 (so that it is not affected by the surrounding environment)
paper_authors: Sha Zhu, Yiwen Zhang, Jiaxue Feng, Yongji Wang, Kunpeng Zhai, Hanke Feng, Edwin Yue Bun Pun, Ning Hua Zhu, Cheng Wang
for: This paper presents a centimeter-resolution integrated photonic radar operating in the mmWave V band (40-50 GHz) for high-resolution sensing and detection of targets.
methods: The paper uses a 4-inch wafer-scale thin-film lithium niobate (TFLN) technology to overcome the limitations of electronic radars and achieve a broadband linear frequency modulated mmWave radar waveform through optical frequency multiplication of a low-frequency input signal.
results: The paper achieves multi-target ranging with a resolution of 1.50 cm and velocity measurement with a resolution of 0.067 m/s, as well as imaging of targets with various shapes and postures with a two-dimensional resolution of 1.50 cm * 1.06 cm.Here’s the Chinese version:
results: 这篇论文实现了多个目标距离测量，分辨率为1.50cm，以及测速度测量，分辨率为0.067m/s，同时还成功构建了反 synthetic aperture radar(ISAR)，并成功图像多种形状和姿态的目标，图像分辨率为1.50cm*1.06cm。Abstract
Millimeter-wave (mmWave,>30 GHz) radars are the key enabler in the coming 6G era for high-resolution sensing and detection of targets. Photonic radar provides an effective approach to overcome the limitations of electronic radars thanks to the high frequency, broad bandwidth, and excellent reconfigurability of photonic systems. However, conventional photonic radars are mostly realized in tabletop systems composed of bulky discrete components, whereas the more compact integrated photonic radars are difficult to reach the mmWave bands due to the unsatisfactory bandwidths and signal integrity of the underlining electro-optic modulators. Here, we overcome these challenges and demonstrate a centimeter-resolution integrated photonic radar operating in the mmWave V band (40-50 GHz) based on a 4-inch wafer-scale thin-film lithium niobate (TFLN) technology. The fabricated TFLN mmWave photonic integrated circuit consists of a first electro-optic modulator capable of generating a broadband linear frequency modulated mmWave radar waveform through optical frequency multiplication of a low-frequency input signal, and a second electro-optic modulator responsible for frequency de-chirp of the received reflected echo wave, therefore greatly relieving the bandwidth requirements for the analog-to-digital converter in the receiver. Thanks to the absence of optical and electrical filters in the system, our integrated photonic mmWave radar features continuous on-demand tunability of the center frequency and bandwidth, currently only limited by the bandwidths of electrical amplifiers. We achieve multi-target ranging with a resolution of 1.50 cm and velocity measurement with a resolution of 0.067 m/s. Furthermore, we construct an inverse synthetic aperture radar (ISAR) and successfully demonstrate the imaging of targets with various shapes and postures with a two-dimensional resolution of 1.50 cm * 1.06 cm.
摘要
millimeter wave (mmWave,>30 GHz) 雷达是 sixth generation (6G) 时代的关键能力，具有高分辨率探测和检测目标的能力。光子雷达技术提供了一种有效的方法来超越电子雷达的限制，因为光子系统具有高频率、广频带宽和优秀的可重新配置性。然而，传统的光子雷达通常是由多个粗糙的独立部件组成的桌面系统，而更 компакт的集成光子雷达具有 mmWave 频率带的差异和信号完整性问题。在这里，我们解决了这些挑战，并实现了基于 4 英寸芯片级薄膜锂铝铌 (TFLN) 技术的中心 Resolution 集成光子 mmWave 雷达，operating in the mmWave V band (40-50 GHz)。制造的 TFLN mmWave 光子集成电路包括一个能够生成广频线性修改 mmWave 雷达波形的第一个电 Optic modulator，以及一个负责接收反射回波的第二个电 Optic modulator。通过光子频率 multiplication 的低频输入信号，该系统实现了广频修改和频率去抖，从而大大减轻接收器 Analog-to-digital Converter 的频率要求。由于系统中缺乏光学和电子过滤器，我们的集成光子 mmWave 雷达具有无间断的受 demand 调试中心频率和带宽，当前只受电子增强器的带宽限制。我们实现了多个目标的距离测量，其中最高分辨率为 1.50 cm，以及速度测量的分辨率为 0.067 m/s。此外，我们还构建了一个反 Synthetic Aperture Radar (ISAR)，并成功地实现了目标的二维图像测量，其分辨率为 1.50 cm * 1.06 cm。
Semantic-Relay-Aided Text Transmission: Placement Optimization and Bandwidth Allocation
results: 提高文本传输效率（improved text transmission efficiency），比对 conventinal decode-and-forward relay（CF Relay）有较高的效果（better performance than conventional CF Relay）Abstract
Semantic communication has emerged as a promising technology to break the Shannon limit by extracting the meaning of source data and sending relevant semantic information only. However, some mobile devices may have limited computation and storage resources, which renders it difficult to deploy and implement the resource-demanding deep learning based semantic encoder/decoder. To tackle this challenge, we propose in this paper a new semantic relay (SemRelay), which is equipped with a semantic receiver for assisting text transmission from a resource-abundant base station (BS) to a resource-constrained mobile device. Specifically, the SemRelay first decodes the semantic information sent by the BS (with a semantic transmitter) and then forwards it to the user by adopting conventional bit transmission, hence effectively improving the text transmission efficiency. We formulate an optimization problem to maximize the achievable (effective) bit rate by jointly designing the SemRelay placement and bandwidth allocation. Although this problem is non-convex and generally difficult to solve, we propose an efficient penalty-based algorithm to obtain a high-quality suboptimal solution. Numerical results show the close-to-optimal performance of the proposed algorithm as well as significant rate performance gain of the proposed SemRelay over conventional decode-and-forward relay.
摘要
The SemRelay decodes the semantic information sent by the BS (with a semantic transmitter) and then forwards it to the user using conventional bit transmission, thereby improving text transmission efficiency. We formulate an optimization problem to maximize the achievable (effective) bit rate by jointly designing the SemRelay placement and bandwidth allocation. Although this problem is non-convex and difficult to solve, we propose an efficient penalty-based algorithm to obtain a high-quality suboptimal solution.Numerical results show that the proposed algorithm achieves close-to-optimal performance and offers significant rate performance gains compared to conventional decode-and-forward relay.
Stacked Intelligent Metasurface-Aided MIMO Transceiver Design
results: 该论文提供了SIM-aided MIMO transceiver设计的概述，包括硬件体系结构和与现有解决方案的比较。此外，论文还详细介绍了应用场景和开放研究挑战，以及使用高级SIM体系结构实现下一代无线网络的可能性。最后，论文提供了数字结果，以证明在无线系统中使用波动信号处理的优势。Abstract
Next-generation wireless networks are expected to utilize the limited radio frequency (RF) resources more efficiently with the aid of intelligent transceivers. To this end, we propose a promising transceiver architecture relying on stacked intelligent metasurfaces (SIM). An SIM is constructed by stacking an array of programmable metasurface layers, where each layer consists of a massive number of low-cost passive meta-atoms that individually manipulate the electromagnetic (EM) waves. By appropriately configuring the passive meta-atoms, an SIM is capable of accomplishing advanced computation and signal processing tasks, such as multiple-input multiple-output (MIMO) precoding/combining, multi-user interference mitigation, and radar sensing, as the EM wave propagates through the multiple layers of the metasurface, which effectively reduces both the RF-related energy consumption and processing delay. Inspired by this, we provide an overview of the SIM-aided MIMO transceiver design, which encompasses its hardware architecture and its potential benefits over state-of-the-art solutions. Furthermore, we discuss promising application scenarios and identify the open research challenges associated with the design of advanced SIM architectures for next-generation wireless networks. Finally, numerical results are provided for quantifying the benefits of wave-based signal processing in wireless systems.
摘要
Inspired by this, we provide an overview of the SIM-aided MIMO transceiver design, including its hardware architecture and potential benefits over existing solutions. We also discuss promising application scenarios and identify open research challenges associated with the design of advanced SIM architectures for next-generation wireless networks. Finally, we provide numerical results to quantify the benefits of wave-based signal processing in wireless systems.Here is the translation in Simplified Chinese:下一代无线网络即将使用有限的广播频率资源更有效地使用，并且通过智能转发器来实现。为此，我们提出了一种有前途的转发器架构，即堆叠智能金属表盘（SIM）。每层SIM都由一大量的低成本Passive元件组成，这些元件个别对电磁波（EM）波进行处理。通过合适配置这些元件，SIM可以完成复杂的计算和信号处理任务，例如多输入多出力（MIMO）预处理/组合、多用户干扰抑制和雷达探测。这将有效减少广播相关的能量消耗和处理延迟。受这些想法启发，我们提供SIM帮助MIMO转发器设计的概述，包括硬件架构和其优势。我们还讨论了可能的应用场景，并识别了进一步开发SIM架构的研究挑战。最后，我们提供了量化无线系统中波形处理的数字结果。
MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization
results: 我们实现了MEGA加速器在28nm技术节点上，并进行了广泛的实验。结果表明，MEGA可以在四种状态目前的GNN加速器上实现平均速度提升38.3倍，7.1倍，4.0倍，3.6倍，而且保持任务的精度。同时，MEGA也可以实现7.2倍，5.4倍，4.5倍的能耗减少。Abstract
Graph Neural Networks (GNNs) are becoming a promising technique in various domains due to their excellent capabilities in modeling non-Euclidean data. Although a spectrum of accelerators has been proposed to accelerate the inference of GNNs, our analysis demonstrates that the latency and energy consumption induced by DRAM access still significantly impedes the improvement of performance and energy efficiency. To address this issue, we propose a Memory-Efficient GNN Accelerator (MEGA) through algorithm and hardware co-design in this work. Specifically, at the algorithm level, through an in-depth analysis of the node property, we observe that the data-independent quantization in previous works is not optimal in terms of accuracy and memory efficiency. This motivates us to propose the Degree-Aware mixed-precision quantization method, in which a proper bitwidth is learned and allocated to a node according to its in-degree to compress GNNs as much as possible while maintaining accuracy. At the hardware level, we employ a heterogeneous architecture design in which the aggregation and combination phases are implemented separately with different dataflows. In order to boost the performance and energy efficiency, we also present an Adaptive-Package format to alleviate the storage overhead caused by the fine-grained bitwidth and diverse sparsity, and a Condense-Edge scheduling method to enhance the data locality and further alleviate the access irregularity induced by the extremely sparse adjacency matrix in the graph. We implement our MEGA accelerator in a 28nm technology node. Extensive experiments demonstrate that MEGA can achieve an average speedup of 38.3x, 7.1x, 4.0x, 3.6x and 47.6x, 7.2x, 5.4x, 4.5x energy savings over four state-of-the-art GNN accelerators, HyGCN, GCNAX, GROW, and SGCN, respectively, while retaining task accuracy.
摘要
图 neural network (GNN) 在不同领域变得抢手的技术，因为它们可以非常好地模型非欧几何数据。 Although a variety of accelerators have been proposed to accelerate the inference of GNNs, our analysis shows that the latency and energy consumption caused by DRAM access still significantly hinders the improvement of performance and energy efficiency. To address this issue, we propose a Memory-Efficient GNN Accelerator (MEGA) through algorithm and hardware co-design in this work. Specifically, at the algorithm level, through an in-depth analysis of the node property, we find that the data-independent quantization in previous works is not optimal in terms of accuracy and memory efficiency. This motivates us to propose the Degree-Aware mixed-precision quantization method, in which a proper bitwidth is learned and allocated to a node according to its in-degree to compress GNNs as much as possible while maintaining accuracy. At the hardware level, we employ a heterogeneous architecture design in which the aggregation and combination phases are implemented separately with different dataflows. In order to boost the performance and energy efficiency, we also present an Adaptive-Package format to alleviate the storage overhead caused by the fine-grained bitwidth and diverse sparsity, and a Condense-Edge scheduling method to enhance the data locality and further alleviate the access irregularity induced by the extremely sparse adjacency matrix in the graph. We implement our MEGA accelerator in a 28nm technology node. Extensive experiments show that MEGA can achieve an average speedup of 38.3x, 7.1x, 4.0x, 3.6x and 47.6x, 7.2x, 5.4x, 4.5x energy savings over four state-of-the-art GNN accelerators, HyGCN, GCNAX, GROW, and SGCN, respectively, while retaining task accuracy.
OFDM-based Waveforms for Joint Sensing and Communications Robust to Frequency Selective IQ Imbalance
methods: 这个研究使用了一种新的OFDM波形，它 neither increases the noise floor nor reduces the maximum unambiguous range，并且提出了一种适应频率选择的通信系统，包括通道估计、同步和数据估计方法，它们是 Specifically designed to deal with frequency selective IQ imbalance in wideband systems。
results: 这个研究通过 simulations 示出了这些通信系统的有效性，并且显示了这些系统在噪声底和最大不ambiguous 距离方面的改善。Abstract
Orthogonal frequency-division multiplexing (OFDM) is a promising waveform candidate for future joint sensing and communication systems. It is well known that the OFDM waveform is vulnerable to in-phase and quadrature-phase (IQ) imbalance, which increases the noise floor in a range-Doppler map (RDM). A state-of-the-art method for robustifying the OFDM waveform against IQ imbalance avoids an increased noise floor, but it generates additional ghost objects in the RDM [1]. A consequence of these additional ghost objects is a reduction of the maximum unambiguous range. In this work, a novel OFDM-based waveform robust to IQ imbalance is proposed, which neither increases the noise floor nor reduces the maximum unambiguous range. The latter is achieved by shifting the ghost objects in the RDM to different velocities such that their range variations observed over several consecutive RDMs do not correspond to the observed velocity. This allows tracking algorithms to identify them as ghost objects and eliminate them for the follow-up processing steps. Moreover, we propose complete communication systems for both the proposed waveform as well as for the state-of-the-art waveform, including methods for channel estimation, synchronization, and data estimation that are specifically designed to deal with frequency selective IQ imbalance which occurs in wideband systems. The effectiveness of these communication systems is demonstrated by means of bit error ratio (BER) simulations.
摘要
隐式frequency-division multiplexing（OFDM）是未来 JOINT sensing和通信系统的优秀waveform候选人。OFDM波形容于均匀和 quadrature-phase（IQ）不匹配，从而增加range-Doppler map（RDM）中的噪声底。现有的state-of-the-art方法可以避免增加噪声底，但会生成RDM中的幻象物体。这些幻象物体会 reducion maximum unambiguous range。在这种工作中，我们提出了一种robust OFDM波形， neither increases the noise floor nor reduces the maximum unambiguous range。这是通过在RDM中移动幻象物体的速度，使其在不同的速度下变化，以至于在多个连续RDM中不同速度下的范围变化不同于观测到的速度。这使得跟踪算法可以将其标记为幻象物体，并在后续处理步骤中消除它们。此外，我们还提出了为两种waveform（包括提案的波形和现有waveform）的完整通信系统，包括频率选择性IQ不匹配的通道估计、同步和数据估计方法，这些方法特别针对随着宽频带的IQ不匹配。我们通过BER simulations示出这些通信系统的有效性。
Reconciling Radio Tomographic Imaging with Phaseless Inverse Scattering
paper_authors: Amartansh Dubey, Zan Li, Ross Murch
For: This paper aims to improve the accuracy of Radio Tomographic Imaging (RTI) by reconciling it with formal inverse scattering approaches and enhancing its performance using inverse scattering techniques.* Methods: The paper uses empirical RTI models and formal inverse scattering approaches to compare and enhance RTI’s performance.* Results: The enhanced RTI method outperforms traditional RTI while having similar computational complexity, as demonstrated through numerical and experimental results using low-cost 2.4 GHz Wi-Fi transceivers for indoor imaging applications.Here is the same information in Simplified Chinese:* For: 这篇论文的目的是提高Radio Tomographic Imaging（RTI）的准确率，通过与正式反射扩散方法进行比较和改进RTI的性能。* Methods: 这篇论文使用了empirical RTI模型和正式反射扩散方法来比较和改进RTI的性能。* Results: 改进后的RTI方法可以超越传统的RTI，同时保持与RTI相同的计算复杂性，通过使用低成本的2.4 GHz Wi-Fi传输器进行indoor应用。Abstract
Radio Tomographic Imaging (RTI) is a phaseless imaging approach that can provide shape reconstruction and localization of objects using received signal strength (RSS) measurements. RSS measurements can be straightforwardly obtained from wireless networks such as Wi-Fi and therefore RTI has been extensively researched and accepted as a good indoor RF imaging technique. However, RTI is formulated on empirical models using an assumption of light-of-sight (LOS) propagation that does not account for intricate scattering effects. There are two main objectives of this work. The first objective is to reconcile and compare the empirical RTI model with formal inverse scattering approaches to better understand why RTI is an effective RF imaging technique. The second objective is to obtain straightforward enhancements to RTI, based on inverse scattering, to enhance its performance. The resulting enhancements can provide reconstructions of the shape and also material properties of the objects that can aid image classification. We also provide numerical and experimental results to compare RTI with the enhanced RTI for indoor imaging applications using low-cost 2.4 GHz Wi-Fi transceivers. These results show that the enhanced RTI can outperform RTI while having similar computational complexity to RTI.
摘要
Radio Tomographic Imaging (RTI) 是一种无相位成像方法，可以提供物体形态重建和位置确定使用接收信号强度 (RSS) 测量。 RSS 测量可以直接从无线网络 such as Wi-Fi 获得，因此 RTI 在indoor RF 成像技术中得到了广泛的研究和认可。然而， RTI 基于employmodels 的 assumption of line-of-sight (LOS) 媒体传播，不能考虑复杂的散射效应。这个工作的两个主要目标是：1. 与形式 inverse scattering 方法进行对比和结合 RTI 模型，以更好地理解 RTI 是一种有效的 RF 成像技术。2. 基于 inverse scattering 方法，对 RTI 进行改进，以提高其性能。改进后的 RTI 可以提供更好的形态重建和物体属性的重建，这可以帮助图像分类。我们还提供了数字和实验结果，以比较 RTI 与改进后的 RTI 在indoor 成像应用中的性能。结果表明，改进后的 RTI 可以超过 RTI，而且与 RTI 的计算复杂度相似。
Plug-In RIS: A Novel Approach to Fully Passive Reconfigurable Intelligent Surfaces
paper_authors: Mahmoud Raeisi, Ibrahim Yildirim, Mehmet Cagri Ilter, Majid Gerami, Ertugrul Basar
for: 提高 millimeter wave 通信系统中阻挡区域的性能
methods: 使用固定磁场技术和先进的杂排列技术来实现位置相关的磁场规划
results: 在有限CSI情况下， plug-in RIS 可以提供高效的解决方案，并与传统全CSI-启用 RIS 解决方案 exhibit striking convergence in average bit error rate and achievable rate performance.Abstract
This paper presents a promising design concept for reconfigurable intelligent surfaces (RISs), named plug-in RIS, wherein the RIS is plugged into an appropriate position in the environment, adjusted once according to the location of both base station and blocked region, and operates with fixed beams to enhance the system performance. The plug-in RIS is a novel system design, streamlining RIS-assisted millimeter-wave (mmWave) communication without requiring decoupling two parts of the end-to-end channel, traditional control signal transmission, and online RIS configuration. In plug-in RIS-aided transmission, the transmitter efficiently activates specific regions of the divided large RIS by employing hybrid beamforming techniques, each with predetermined phase adjustments tailored to reflect signals to desired user locations. This user-centric approach enhances connectivity and overall user experience by dynamically illuminating the targeted user based on location. By introducing plug-in RIS's theoretical framework, design principles, and performance evaluation, we demonstrate its potential to revolutionize mmWave communications in limited channel state information (CSI) scenarios. Simulation results illustrate that plug-in RIS provides power/cost-efficient solutions to overcome blockage in the mmWave communication system and a striking convergence in average bit error rate and achievable rate performance with traditional full CSI-enabled RIS solutions.
摘要
The novel design of the plug-in RIS eliminates the need for decoupling the two parts of the end-to-end channel, traditional control signal transmission, and online RIS configuration, streamlining the RIS-assisted mmWave communication. In the plug-in RIS-aided transmission, the transmitter efficiently activates specific regions of the divided large RIS using hybrid beamforming techniques, each with predetermined phase adjustments tailored to reflect signals to desired user locations. This user-centric approach enhances connectivity and overall user experience by dynamically illuminating the targeted user based on location.The theoretical framework, design principles, and performance evaluation of the plug-in RIS are presented in this paper, demonstrating its potential to revolutionize mmWave communications in limited channel state information (CSI) scenarios. Simulation results show that the plug-in RIS provides power/cost-efficient solutions to overcome blockage in the mmWave communication system and achieves a striking convergence in average bit error rate and achievable rate performance with traditional full CSI-enabled RIS solutions.
Joint Visibility Region and Channel Estimation for Extremely Large-scale MIMO Systems
paper_authors: Anzheng Tang, Jun-bo Wang, Yijin Pan, Wence Zhang, Yijian Chen, Hongkang Yu, Rodrigo C. de Lamare
for: 本研究 investigate the channel estimation (CE) problem for extremely large-scale multiple-input-multiple-output (XL-MIMO) systems, considering both the spherical wavefront effect and spatial non-stationarity (SnS).
methods: 我们提出了一种 two-stage visibility region (VR) detection and CE framework, which leverages sparsity in both the spatial and wavenumber domains to achieve an accurate estimation. In the first stage, we use a structured message passing (MP) scheme to obtain the belief regarding the visibility of antennas. In the second stage, we use the obtained VR information and wavenumber-domain sparsity to accurately estimate the SnS channel employing the belief-based orthogonal matching pursuit (BB-OMP) method.
results: simulations demonstrate that the proposed algorithms lead to a significant enhancement in VR detection and CE accuracy, especially in low signal-to-noise ratio (SNR) scenarios.Abstract
In this work, we investigate the channel estimation (CE) problem for extremely large-scale multiple-input-multiple-output (XL-MIMO) systems, considering both the spherical wavefront effect and spatial non-stationarity (SnS). Unlike existing non-stationary CE methods that rely on the statistical characteristics of channels in the spatial or temporal domain, our approach seeks to leverage sparsity in both the spatial and wavenumber domains simultaneously to achieve an accurate estimation.To this end, we introduce a two-stage visibility region (VR) detection and CE framework. Specifically, in the first stage, the belief regarding the visibility of antennas is obtained through a structured message passing (MP) scheme, which fully exploits the block sparse structure of the antenna-domain channel. In the second stage, using the obtained VR information and wavenumber-domain sparsity, we accurately estimate the SnS channel employing the belief-based orthogonal matching pursuit (BB-OMP) method. Simulations demonstrate that the proposed algorithms lead to a significant enhancement in VR detection and CE accuracy, especially in low signal-to-noise ratio (SNR) scenarios.
摘要
在这项工作中，我们研究了超大规模多输入多输出（XL-MIMO）系统中的通道估计（CE）问题，考虑了球面冲击效应和空间非站点性（SnS）。 unlike existing non-stationary CE方法，我们的方法不仅利用了通道在空间或时域频率域的统计特性，而且同时充分利用了antenna-domain通道的块稀畴结构。为达到这个目的，我们提出了两个阶段的可见区域（VR）探测和CE框架。在第一阶段，通过一种结构化的消息传递（MP）方案，我们可以获得天线域通道的可见性信念。在第二阶段，使用获得的VR信息和波数域稀畴性，我们可以高精度地估计SnS通道，使用信念基本的搜索匹配策略（BB-OMP）。 simulation结果表明，我们的算法可以在低信号噪响比（SNR）场景下提高VR检测和CE准确率。