paper_authors: Sueda Taner, Maxime Guillaud, Olav Tirkkonen, Christoph Studer
for: This paper is written for the purpose of extracting pseudo-position information for each user using channel state information (CSI) data at the infrastructure basestation side, without requiring any ground-truth position information.
methods: The paper proposes a novel streaming channel charting (CC) architecture that maintains a small core CSI dataset and uses a min-max-similarity criterion for curation.
results: Numerical validation with measured CSI data demonstrates that the proposed method approaches the accuracy obtained from the complete CSI dataset while using only a fraction of CSI storage and avoiding catastrophic forgetting of old CSI data.Abstract
Channel charting (CC) applies dimensionality reduction to channel state information (CSI) data at the infrastructure basestation side with the goal of extracting pseudo-position information for each user. The self-supervised nature of CC enables predictive tasks that depend on user position without requiring any ground-truth position information. In this work, we focus on the practically relevant streaming CSI data scenario, in which CSI is constantly estimated. To deal with storage limitations, we develop a novel streaming CC architecture that maintains a small core CSI dataset from which the channel charts are learned. Curation of the core CSI dataset is achieved using a min-max-similarity criterion. Numerical validation with measured CSI data demonstrates that our method approaches the accuracy obtained from the complete CSI dataset while using only a fraction of CSI storage and avoiding catastrophic forgetting of old CSI data.
摘要
HARQ-IR Aided Short Packet Communications: BLER Analysis and Throughput Maximization
results: 论文的结果表明，使用 GP 解决方案可以在高 SNR 下获得更高的 LTAT，但在低 SNR 下，使用 DRL 解决方案可以更好地提高 LTAT，尽管计算 overhead 会增加。Abstract
This paper introduces hybrid automatic repeat request with incremental redundancy (HARQ-IR) to boost the reliability of short packet communications. The finite blocklength information theory and correlated decoding events tremendously preclude the analysis of average block error rate (BLER). Fortunately, the recursive form of average BLER motivates us to calculate its value through the trapezoidal approximation and Gauss-Laguerre quadrature. Moreover, the asymptotic analysis is performed to derive a simple expression for the average BLER at high signal-to-noise ratio (SNR). Then, we study the maximization of long term average throughput (LTAT) via power allocation meanwhile ensuring the power and the BLER constraints. For tractability, the asymptotic BLER is employed to solve the problem through geometric programming (GP). However, the GP-based solution underestimates the LTAT at low SNR due to a large approximation error in this case. Alternatively, we also develop a deep reinforcement learning (DRL)-based framework to learn power allocation policy. In particular, the optimization problem is transformed into a constrained Markov decision process, which is solved by integrating deep deterministic policy gradient (DDPG) with subgradient method. The numerical results finally demonstrate that the DRL-based method outperforms the GP-based one at low SNR, albeit at the cost of increasing computational burden.
摘要
To maximize the long-term average throughput (LTAT) while ensuring power and BLER constraints, we use power allocation and study the problem through geometric programming (GP). However, the GP-based solution underestimates the LTAT at low SNR due to a large approximation error. As an alternative, we develop a deep reinforcement learning (DRL)-based framework to learn the power allocation policy. The optimization problem is transformed into a constrained Markov decision process, which is solved by integrating deep deterministic policy gradient (DDPG) with subgradient method.The numerical results show that the DRL-based method outperforms the GP-based one at low SNR, but with increased computational burden.
Secure Cell-Free Integrated Sensing and Communication in the Presence of Information and Sensing Eavesdroppers
results: 我们的计算结果表明，我们的提出的设计方案在对抗探测和窃听者的情况下，能够提供较高的探测概率和安全性。此外，我们还提出了两种备选的共同发射方案，一种是根据探测区域内的感知信号强度最大化，另一种是通过协调发射来实现。Abstract
This paper studies a secure cell-free integrated sensing and communication (ISAC) system, in which multiple ISAC transmitters collaboratively send confidential information to multiple communication users (CUs) and concurrently conduct target detection. Different from prior works investigating communication security against potential information eavesdropping, we consider the security of both communication and sensing in the presence of both information and sensing eavesdroppers that aim to intercept confidential communication information and extract target information, respectively. Towards this end, we optimize the joint information and sensing transmit beamforming at these ISAC transmitters for secure cell-free ISAC. Our objective is to maximize the detection probability over a designated sensing area while ensuring the minimum signal-to-interference-plus-noise-ratio (SINR) requirements at CUs. Our formulation also takes into account the maximum tolerable signal-to-noise ratio (SNR) at information eavesdroppers for ensuring the confidentiality of information transmission, and the maximum detection probability constraints at sensing eavesdroppers for preserving sensing privacy. The formulated secure joint transmit beamforming problem is highly non-convex due to the intricate interplay between the detection probabilities, beamforming vectors, and SINR constraints. Fortunately, through strategic manipulation and via applying the semidefinite relaxation (SDR) technique, we successfully obtain the globally optimal solution to the design problem by rigorously verifying the tightness of SDR. Furthermore, we present two alternative joint beamforming designs based on the sensing SNR maximization over the specific sensing area and the coordinated beamforming, respectively. Numerical results reveal the benefits of our proposed design over these alternative benchmarks.
摘要
The formulated secure joint transmit beamforming problem is highly non-convex due to the complex interplay between the detection probabilities, beamforming vectors, and SINR constraints. However, by strategically manipulating the problem and applying the semidefinite relaxation (SDR) technique, we successfully obtain the globally optimal solution to the design problem. Furthermore, we propose two alternative joint beamforming designs based on sensing SNR maximization over the specific sensing area and coordinated beamforming, respectively. Numerical results show the benefits of our proposed design compared to these alternative benchmarks.Translation notes:* "cell-free" is translated as "无线网络" (wireless network)* "integrated sensing and communication" is translated as "整合探测和通信" (integrated sensing and communication)* "ISAC transmitters" is translated as "ISAC发送器" (ISAC transmitters)* "communication users" is translated as "通信用户" (communication users)* "sensing eavesdroppers" is translated as "探测侦测者" (sensing eavesdroppers)* "information eavesdroppers" is translated as "信息侦测者" (information eavesdroppers)* "SINR" is translated as "信噪比" (SINR)* "SNR" is translated as "信噪比" (SNR)* "SDR" is translated as "半definiterelaxation" (SDR)Note: The translation is based on the standardized Chinese terminology for the relevant technical terms, and may not be the only possible translation.
Accelerated Real-Life (ARL) Testing and Characterization of Automotive LiDAR Sensors to facilitate the Development and Validation of Enhanced Sensor Models
paper_authors: Marcel Kettelgerdes, Tjorven Hillmann, Thomas Hirmer, Hüseyin Erdogan, Bernhard Wunderle, Gordon Elger
for: This paper aims to address the aging effects of LiDAR sensors in automated driving simulation and sensor modeling, with the goal of improving the reliability and safety of ADAS systems.
methods: The authors propose a cutting-edge Hardware-in-the-Loop (HiL) test bench for accelerated aging and characterization of Automotive LiDAR sensors, which enables the simulation of aging effects such as laser beam profile deterioration, output power reduction, and intrinsic parameter drift.
results: The proposed method is expected to provide a more accurate and comprehensive understanding of LiDAR sensor aging, and will help to identify and model degradation effects, as well as suggest quantitative model validation metrics.Abstract
In the realm of automated driving simulation and sensor modeling, the need for highly accurate sensor models is paramount for ensuring the reliability and safety of advanced driving assistance systems (ADAS). Hence, numerous works focus on the development of high-fidelity models of ADAS sensors, such as camera, Radar as well as modern LiDAR systems to simulate the sensor behavior in different driving scenarios, even under varying environmental conditions, considering for example adverse weather effects. However, aging effects of sensors, leading to suboptimal system performance, are mostly overlooked by current simulation techniques. This paper introduces a cutting-edge Hardware-in-the-Loop (HiL) test bench designed for the automated, accelerated aging and characterization of Automotive LiDAR sensors. The primary objective of this research is to address the aging effects of LiDAR sensors over the product life cycle, specifically focusing on aspects such as laser beam profile deterioration, output power reduction and intrinsic parameter drift, which are mostly neglected in current sensor models. By that, this proceeding research is intended to path the way, not only towards identifying and modeling respective degradation effects, but also to suggest quantitative model validation metrics.
摘要
在自动驾驶模拟和感知模型方面，准确的感知模型对于确保高级驾驶助手系统（ADAS）的可靠性和安全性至关重要。因此，许多研究都是关于开发高精度ADAS感知器模型，如摄像头、雷达以及现代LiDAR系统，以模拟不同驾驶场景下的感知器行为，包括不同环境条件下的影响。然而，感知器的衰老效应通常被当前的模拟技术忽略。这篇论文介绍了一种领先的硬件在Loop（HiL）测试台，用于自动化、加速感知器衰老和特性测试。该研究的主要目标是处理感知器的衰老效应，特别是激光束profile衰老、输出功率减少和内在参数漂移等方面，这些方面通常由当前的感知器模型忽略。通过这种研究，可以不仅模型和识别相应的衰老效应，还可以建议量化模型验证度量器。
Enhanced data Detection for Massive MIMO with 1-Bit ADCs
results: 结果表明，使用 zeros forcing 和 minimum mean squared error 接收器可以提供 considerable gains，而且提议的 joint data detection 策略可以带来更大的提升。Abstract
We present new insightful results on the uplink data detection for massive multiple-input multiple-output systems with 1-bit analog-to-digital converters. The expected values of the soft-estimated symbols (i.e., after the linear combining and prior to the data detection) have been recently characterized for multiple user equipments (UEs) and maximum ratio combining (MRC) receiver at the base station. In this paper, we first provide a numerical evaluation of the expected value of the soft-estimated symbols with zero-forcing (ZF) and minimum mean squared error (MMSE) receivers for a multi-UE setting with correlated Rayleigh fading. Then, we propose a joint data detection (JD) strategy, which exploits the interdependence among the soft-estimated symbols of the interfering UEs, along with its low-complexity variant. These strategies are compared with a naive approach that adapts the maximum-likelihood data detection to the 1-bit quantization. Numerical results show that ZF and MMSE provide considerable gains over MRC in terms of symbol error rate. Moreover, the proposed JD and its low-complexity variant provide a significant boost in comparison with the single-UE data detection.
摘要
我们提出了新的深入的结果，探讨大规模多输入多Output系统中1比特数字转换器的上行数据检测。我们最近对多个用户设备（UE）和最大比率组合（MRC）接收器的基站中的软估Symbol（即在线性组合后并 перед数据检测）的预期值进行了数值评估。在这篇论文中，我们首先为多 UE 设置中的零力量（ZF）和最小平均方差 Error（MMSE）接收器提供了数值评估，然后提议了一种联合数据检测策略（JD），该策略利用了干扰 UE 之间软估符的互相关系，同时还提出了一种低复杂度的变体。这些策略与适应最大likelihood数据检测的方法进行比较。numerical resultshow ZF和MMSE在Symbol error rate方面提供了明显的提升，而提议的JD和其低复杂度变体也提供了显著的提升，相比单UE数据检测。
An Unsupervised Machine Learning Scheme for Index-Based CSI Feedback in Wi-Fi
results: 通过对五种不同的数据表示方法进行比较，显示了新的索引基本 feedback 方法可以有效地减少反馈 overhead，提高通过put的率，同时保持适当的链接性能。Abstract
With the ever-increasing demand for high-speed wireless data transmission, beamforming techniques have been proven to be crucial in improving the data rate and the signal-to-noise ratio (SNR) at the receiver. However, they require feedback mechanisms that need an overhead of information and increase the system complexity, potentially challenging the efficiency and capacity of modern wireless networks. This paper investigates novel index-based feedback mechanisms that aim at reducing the beamforming feedback overhead in Wi-Fi links. The proposed methods mitigate the overhead by generating a set of candidate beamforming vectors using an unsupervised learning-based framework. The amount of feedback information required is thus reduced by using the index of the candidate as feedback instead of transmitting the entire beamforming matrix. We explore several methods that consider different representations of the data in the candidate set. In particular, we propose five different ways to generate and represent the candidate sets that consider the covariance matrices of the channel, serialize the feedback matrix, and account for the effective distance, among others. Additionally, we also discuss the implications of using partial information in the compressed beamforming feedback on the link performance and compare it with the newly proposed index-based methods. Extensive IEEE 802.11 standard-compliant simulation results show that the proposed methods effectively minimize the feedback overhead, enhancing the throughput while maintaining an adequate link performance.
摘要
随着无线数据传输的高速需求不断增长， beamforming技术已经被证明是在提高接收器的数据速率和信噪比 (SNR) 方面发挥重要作用。然而，它们需要回馈机制，这会增加系统的复杂度和信息过头，可能挑战现代无线网络的效率和容量。这篇论文探讨了一种新的索引基本反馈机制，用于减少 Wi-Fi 链路中的回馈过头。该方法通过使用一种无supervised learning-based框架生成候选 beamforming вектор集。因此，需要返回的反馈信息量减少为使用候选集索引作为反馈，而不是将整个回馈矩阵发送。我们提出了五种不同的方法来生成和表示候选集，包括考虑通道 covariance 矩阵、序列化反馈矩阵、考虑有效距离等。此外，我们还讨论了使用压缩回馈中的半信息对链路性能的影响，并与新提出的索引基本方法进行比较。我们的 IEEE 802.11 标准 compatibles 的 simulate 结果表明，提议的方法能够有效减少回馈过头，提高传输速率，同时保持链路性能。
Enhanced Index-Based Feedback Overhead Reduction for WLANs
results: 比IEEE 802.11be 基准方式高速率约54%，与前一种索引基于方法相比下降约4 dB，并讨论了选择距离度量对链接性能的影响。Abstract
Compressed beamforming algorithm is used in the current Wi-Fi standard to reduce the beamforming feedback overhead (BFO). However, with each new amendment of the standard the number of supported antennas in Wi-Fi devices increases, leading to increased BFO and hampering the throughput despite using compressed beamforming. In this paper, a novel index-based method is presented to reduce the BFO in Wi-Fi links. In particular, a k-means clustering-based approach is presented to generate candidate beamforming feedback matrices, thereby reducing the BFO to only the index of the said candidate matrices. With extensive simulation results, we compare the newly proposed method with the IEEE 802.11be baseline and our previously published index-based method. We show approximately 54% gain in throughput at high signal-to-noise (SNR) against the IEEE 802.11be baseline. Our comparison also shows approximately 4 dB gain compared to our previously published method at the packet-error-rate (PER) of 0.01 using MCS index 11. Additionally, we also discuss the impact of the distance metric chosen for clustering as well as candidate selection on the link performance.
摘要
现在的 Wi-Fi 标准中使用压缩式 beamforming 算法来减少射频反馈过载 (BFO)。然而，每一个标准修订中支持antenna的数量在 Wi-Fi 设备中增加，导致 BFO 的增加和通过速率的阻塞，即使使用压缩式 beamforming。在这篇论文中，我们提出了一种新的指标基于方法来降低 Wi-Fi 链接中的 BFO。具体来说，我们使用 k-means 分类来生成候选射频反馈矩阵，从而降低 BFO 到只有候选矩阵的指标。我们通过广泛的 simulate 结果，与 IEEE 802.11be 基准和我们之前发表的指标基于方法进行比较。我们发现在高信号噪比 (SNR) 下，与 IEEE 802.11be 基准相比，我们的方法可以获得约 54% 的吞吐量提升。我们的比较还表明，与 MCS 指标 11 下的 PER 0.01 相比，我们的方法可以获得约 4 dB 的增加。此外，我们还讨论了选择 clustering 的距离度量以及候选选择对链接性能的影响。
RIS-Aided Interference Cancellation for Joint Device-to-Device and Cellular Communications
results: 研究人员发现，AO方法可以快速 converge 并且可以在初始化IC解决方案的情况下表现更好，而且对于单个D2D对，IC方法可以通过有限反馈来实现。Abstract
Joint device-to-device (D2D) and cellular communication is a promising technology for enhancing the spectral efficiency of future wireless networks. However, the interference management problem is challenging since the operating devices and the cellular users share the same spectrum. The emerging reconfigurable intelligent surfaces (RIS) technology is a potentially ideal solution for this interference problem since RISs can shape the wireless channel in desired ways. This paper considers an RIS-aided joint D2D and cellular communication system where the RIS is exploited to cancel interference to the D2D links and maximize the minimum signal-to-interference plus noise (SINR) of the device pairs and cellular users. First, we adopt a popular alternating optimization (AO) approach to solve the minimum SINR maximization problem. Then, we propose an interference cancellation (IC)-based approach whose complexity is much lower than that of the AO algorithm. We derive a representation for the RIS phase shift vector which cancels the interference to the D2D links. Based on this representation, the RIS phase shift optimization problem is transformed into an effective D2D channel optimization. We show that the AO approach can converge faster and can even give better performance when it is initialized by the proposed IC solution. We also show that for the case of a single D2D pair, the proposed IC approach can be implemented with limited feedback from the single receive device.
摘要
合作设备到设备（D2D）和基站通信技术可能会提高未来无线网络的频谱效率。然而，管理干扰的问题很大，因为操作设备和基站用户共享同一频谱。emerging reconfigurable intelligent surfaces（RIS）技术可能是干扰问题的解决方案，因为RIS可以形成 désirable的无线通信频道。本文考虑了RIS帮助的合作D2D和基站通信系统，其中RIS被利用来消除D2D链路的干扰，并最大化设备对和基站用户的最小干扰 plus noise ratio（SINR）。首先，我们采用了一种受欢迎的交互优化（AO）方法来解决最大化SINR问题。然后，我们提出了一种干扰抑制（IC）基于的方法，其复杂性比AO算法要低。我们 derive了一个表示RIS相位偏移 вектор可以消除D2D链路的干扰。基于这个表示，RIS相位优化问题被转化为了一个有效的D2D通信道优化问题。我们表明，AO方法可以更快 converges和可以在ICInitialize时给出更好的性能。我们还表明，对于具有单个D2D对的情况，我们的IC方法可以通过有限反馈来实现。