paper_authors: Tianyi Liu, Frederic Matter, Alexander Sorg, Marc E. Pfetsch, Martin Haardt, Marius Pesavento
for: This paper addresses the maximum a posteriori (MAP) estimation for the multiple measurement vectors (MMV) problem, which is a fundamental problem in signal processing applications such as spectral analysis and direction-of-arrival (DOA) estimation.
methods: The paper derives an equivalent mixed-integer semidefinite program (MISDP) reformulation of the MAP estimation for the MMV problem, which can be exactly solved by a generic MISDP solver. However, for problems of extremely large dimensions, a relaxation-based approach is employed to obtain an approximate solution with reduced computation time.
results: The proposed method demonstrates improved error performance compared to several popular DOA estimation methods, including the deterministic maximum likelihood (DML) estimator. The method also offers a guarantee of finding a global optimum, unlike other nonconvex approaches for the MMV problem.Abstract
The multiple measurement vectors (MMV) problem refers to the joint estimation of a row-sparse signal matrix from multiple realizations of mixtures with a known dictionary. As a generalization of the standard sparse representation problem for a single measurement, this problem is fundamental in various applications in signal processing, e.g., spectral analysis and direction-of-arrival (DOA) estimation. In this paper, we consider the maximum a posteriori (MAP) estimation for the MMV problem, which is classically formulated as a regularized least-squares (LS) problem with an $\ell_{2,0}$-norm constraint, and derive an equivalent mixed-integer semidefinite program (MISDP) reformulation. The proposed MISDP reformulation can be exactly solved by a generic MISDP solver, which, however, becomes computationally demanding for problems of extremely large dimensions. To further reduce the computation time in such scenarios, a relaxation-based approach can be employed to obtain an approximate solution of the MISDP reformulation, at the expense of a reduced estimation performance. Numerical simulations in the context of DOA estimation demonstrate the improved error performance of our proposed method in comparison to several popular DOA estimation methods. In particular, compared to the deterministic maximum likelihood (DML) estimator, which is often used as a benchmark, the proposed method applied with a state-of-the-art MISDP solver exhibits a superior estimation performance at a significantly reduced running time. Moreover, unlike other nonconvex approaches for the MMV problem, including the greedy methods and the sparse Bayesian learning, the proposed MISDP-based method offers a guarantee of finding a global optimum.
摘要
多量测量向量（MMV）问题指的是从多个实现的混合中 joint 估计一个纤维数为 row-sparse 信号矩阵。这个问题是对于各种信号处理应用的基本问题，例如 спектраль分析和方向来源估计（DOA）。在这篇文章中，我们考虑了最大 posteriori（MAP）估计方法，这是经典的常数加权最小二乘（L2,0）准则问题的等价混合半整数Program（MISDP） reformulation。我们可以使用一个通用的 MISDP 解决方案来 exactly 解这个问题，但是在极大维度的问题中，这会变得计算昂贵。为了进一步减少计算时间，我们可以采用一种缓和方法来获得一个相对优化的 MISDP reformulation，但是这将导致估计性能下降。在 DOA 估计的数值实验中，我们发现我们提出的方法在与其他几种流行的 DOA 估计方法相比，具有更高的估计性能，同时具有更快的计算时间。此外，不同于其他非凸方法，包括排序方法和杂音抽象学习，我们的 MISDP-based 方法可以保证找到全球最优解。
Resource Allocation for RIS-Empowered Wireless Communications: Low-Complexity and Robust Designs
results: 研究表明，采用低复杂性和可靠性资源分配技术可以在RIS assisted系统中提高系统的可靠性和性能。Abstract
This article delves into advancements in resource allocation techniques tailored for systems utilizing reconfigurable intelligent surfaces (RIS), with a primary focus on achieving low-complexity and resilient solutions. The investigation of low-complexity approaches for RIS holds significant relevance, primarily owing to the intricate characteristics inherent in RIS-based systems and the need of deploying large-scale RIS arrays. Concurrently, the exploration of robust solutions aims to address the issue of hardware impairments occurring at both the transceivers and RIS components in practical RIS-assisted systems. In the realm of both low-complexity and robust resource allocation, this article not only elucidates the fundamental techniques underpinning these methodologies but also offers comprehensive numerical results for illustrative purposes. The necessity of adopting resource allocation strategies that are both low in complexity and resilient is thoroughly established. Ultimately, this article provides prospective research avenues in the domain of low-complexity and robust resource allocation techniques tailored for RIS-assisted systems.
摘要
Multivariate selfsimilarity: Multiscale eigen-structures for selfsimilarity parameter estimation
results: 该 paper 提出了一种高效的估计方法，并在实际数据上进行了测试和验证。Abstract
Scale-free dynamics, formalized by selfsimilarity, provides a versatile paradigm massively and ubiquitously used to model temporal dynamics in real-world data. However, its practical use has mostly remained univariate so far. By contrast, modern applications often demand multivariate data analysis. Accordingly, models for multivariate selfsimilarity were recently proposed. Nevertheless, they have remained rarely used in practice because of a lack of available robust estimation procedures for the vector of selfsimilarity parameters. Building upon recent mathematical developments, the present work puts forth an efficient estimation procedure based on the theoretical study of the multiscale eigenstructure of the wavelet spectrum of multivariate selfsimilar processes. The estimation performance is studied theoretically in the asymptotic limits of large scale and sample sizes, and computationally for finite-size samples. As a practical outcome, a fully operational and documented multivariate signal processing estimation toolbox is made freely available and is ready for practical use on real-world data. Its potential benefits are illustrated in epileptic seizure prediction from multi-channel EEG data.
摘要
“级�cciones的动态，通过自相似性 formalized，提供了一个广泛和通用的模型，用于模elling temporal dynamics in real-world data。然而，它的实际使用主要仅对于单变量数数据进行分析。在现代应用中，通常需要多変量数据分析。因此，用于多变量自相似性的模型已经提出。然而，它们在实际中几乎没有被使用，因为缺乏可靠的自相似性参数的估计方法。基于最近的数学发展，本作提出了一个有效的估计方法，基于多尺度传递矩阵的波летспектrum。这个估计方法的性能在大规模和样本大小的对应上进行了理论研究，以及 computationally дляfinite-size样本。作为实用的结果，一个完整的操作和文档的多ivariate signal processing估计工具组已经免费提供，并且准备用于实际数据的处理。其潜在优点被应用于多通道 EEG 数据中的癫癫癫癫预测。”Note: The translation is in Simplified Chinese, which is the standard writing system used in mainland China. If you prefer Traditional Chinese, please let me know and I can provide the translation in that format as well.
Using Shallow Neural Networks with Functional Connectivity from EEG signals for Early Diagnosis of Alzheimer’s and Frontotemporal Dementia
For: The paper is written to explore the use of shallow neural networks and functional connectivity measures from EEG signals to differentiate between AD, FTD, and control cases.* Methods: The paper uses two sets of features: spectral-temporal and functional connectivity, and employs four methods, including shallow CNN-based models, to classify EEG signals.* Results: The shallow CNN-based models achieved the highest accuracy of 94.54% with AEC in the test dataset, outperforming conventional methods and providing a potentially additional early dementia diagnosis tool.Here is the information in Simplified Chinese text, as requested:
results: shallow CNN 基本模型在测试集上取得了 94.54% 的最高准确率，超过了常见方法，并提供了可能的早期诊断工具。Abstract
{Introduction: } Dementia is a neurological disorder associated with aging that can cause a loss of cognitive functions, impacting daily life. Alzheimer's disease (AD) is the most common cause of dementia, accounting for 50--70\% of cases, while frontotemporal dementia (FTD) affects social skills and personality. Electroencephalography (EEG) provides an effective tool to study the effects of AD on the brain. {Methods: } In this study, we propose to use shallow neural networks applied to two sets of features: spectral-temporal and functional connectivity using four methods. We compare three supervised machine learning techniques to the CNN models to classify EEG signals of AD / FTD and control cases. We also evaluate different measures of functional connectivity from common EEG frequency bands considering multiple thresholds. {Results and Discussion: } Results showed that the shallow CNN-based models achieved the highest accuracy of 94.54\% with AEC in test dataset when considering all connections, outperforming conventional methods and providing potentially an additional early dementia diagnosis tool. \url{https://doi.org/10.3389%2Ffneur.2023.1270405}
摘要
{Methods: } 在这项研究中，我们提出使用浅层神经网络，应用于两个集合：spectral-temporal和功能相关性。我们使用四种方法进行比较，包括三种超vised机器学习技术和CNN模型，以分类EEG信号的AD/FTD和控制 caso。此外，我们还评估了不同频谱带的功能相关性测量，使用多个阈值。{Results and Discussion: } 结果显示，使用浅层CNN-based模型可以达到94.54%的准确率，在测试数据集中，当考虑所有连接时，超过 conventional methods，并可能提供一种额外的诊断老年痴呐工具。参考文献：
Energy Harvesting Maximization for Reconfigurable Intelligent Surfaces Using Amplitude Measurements
results: 我们通过对比Random phase update algorithm的表现，发现我们的提案算法在达到功率后的性能比Random algorithm更好，并且需要 fewer measurements per phase update。在噪场景下，我们通过Simulation表明，提案算法在一个离散的可能的相对位集中的情况下是不优的，它可以达到高于Random algorithm的值，但不是最大可能的值。Abstract
Energy harvesting can enable a reconfigurable intelligent surface (RIS) to self-sustain its operations without relying on external power sources. In this paper, we consider the problem of energy harvesting for RISs in the absence of coordination with the ambient RF source. We propose a series of sequential phase-alignment algorithms that maximize the received power based on only power measurements. We prove the convergence of the proposed algorithm to the optimal value for the noiseless scenario. However, for the noisy scenario, we propose a linear least squares estimator. We prove that within the class of linear estimators, the optimal set of measurement phases are equally-spaced phases. To evaluate the performance of the proposed method, we introduce a random phase update algorithm as a benchmark. Our simulation results show that the proposed algorithms outperform the random phase update method in terms of achieved power after convergence while requiring fewer measurements per phase update. Using simulations, we show that in a noiseless scenario with a discrete set of possible phase shifts for the RIS elements, the proposed method is sub-optimal, achieving a higher value than the random algorithm but not exactly the maximum feasible value that we obtained by exhaustive search.
摘要
能量收集可以让智能表面重新配置（RIS）无需依赖于外部电源进行自主运行。在这篇论文中，我们考虑了RIS中能量收集的问题，不同征Compatibility Mode（RF）源的协调。我们提出了一系列的顺序相对纹理算法，以最大化接收到的功率基于 только能量测量。我们证明了不含噪声的情况下，提posed算法的优化性。但是，在噪声场景下，我们提出了线性最小二乘估计器。我们证明了在线性估计器中的优化集是均匀分布的相位。为了评估提案方法的性能，我们引入了随机相位更新算法作为参照。我们的实验结果表明，提案方法在吞吐量更高，需要 fewer measurements per phase update。使用实验，我们发现在噪声场景下，对RIS元素的可能的相位shift是一个离散的集合时，提案方法是优化的，可以达到最大可能的值，但不是恰好的最大值。
Antenna Positioning and Beamforming Design for Movable-Antenna Enabled Multi-user Downlink Communications
for: investigate a multiple input single output (MISO) downlink communication system with movable antennas (MAs)
methods: adopt a field-response based channel model and employ an alternating optimization (AO) algorithm based on penalty method and successive convex approximation (SCA) to obtain a sub-optimal solution
results: the MA-enabled communication system performs better than conventional fixed position antennasHere’s the format you requested:
for: <what are the paper written for?>
methods: <what methods the paper use?>
results: <what results the paper get?>I hope this helps! Let me know if you have any other questions.Abstract
This paper investigates a multiple input single output (MISO) downlink communication system in which users are equipped with movable antennas (MAs). First, We adopt a field-response based channel model to characterize the downlink channel with respect to MAs' positions. Then, we aim to minimize the total transmit power by jointly optimizing the MAs' positions and beamforming matrix. To solve the resulting non-convex problem, we employ an alternating optimization (AO) algorithm based on penalty method and successive convex approximation (SCA) to obtain a sub-optimal solution. Numerical results demonstrate that the MA-enabled communication system perform better than conventional fixed position antennas.
摘要
这个论文研究了一个多输入单输出（MISO）下链通信系统，在该系统中用户装备了可动天线（MA）。首先，我们采用场响应基于通道模型来描述附近MA的下链通道。然后，我们想要最小化总发射功率，通过同时优化MA的位置和扬行矩阵来解决。为解决得到的非对称问题，我们使用 alternate optimization（AO）算法和罚方法和逐步几何近似（SCA）来获得一个优化解决方案。 numerically， results show that the MA-enabled communication system outperforms traditional fixed position antennas.Here's the breakdown of the translation:* "This paper investigates a multiple input single output (MISO) downlink communication system" becomes "这个论文研究了一个多输入单输出（MISO）下链通信系统"* "in which users are equipped with movable antennas (MAs)" becomes "在该系统中用户装备了可动天线（MA）"* "First, We adopt a field-response based channel model to characterize the downlink channel with respect to MAs' positions" becomes "首先，我们采用场响应基于通道模型来描述附近MA的下链通道"* "Then, we aim to minimize the total transmit power by jointly optimizing the MAs' positions and beamforming matrix" becomes "然后，我们想要最小化总发射功率，通过同时优化MA的位置和扬行矩阵来解决"* "To solve the resulting non-convex problem, we employ an alternating optimization (AO) algorithm based on penalty method and successive convex approximation (SCA) to obtain a sub-optimal solution" becomes "为解决得到的非对称问题，我们使用 alternate optimization（AO）算法和罚方法和逐步几何近似（SCA）来获得一个优化解决方案"* "Numerical results demonstrate that the MA-enabled communication system perform better than conventional fixed position antennas" becomes "numerically， results show that the MA-enabled communication system outperforms traditional fixed position antennas"
Optimization of RIS Placement for Satellite-to-Ground Coverage Enhancement
results: 通过大规模RIS部署，实现卫星到地面通信覆盖率的下限，并且通过优化RIS布局，提高非直线视野用户的通信覆盖率，并可应用于不同的建筑物分布情况（如农村、小镇、城市）。Abstract
In satellite-to-ground communication, ensuring reliable and efficient connectivity poses significant challenges. The reconfigurable intelligent surface (RIS) offers a promising solution due to its ability to manipulate wireless propagation environments and thus enhance communication performance. In this paper, we propose a method for optimizing the placement of RISs on building facets to improve satellite-to-ground communication coverage. We model satellite-to-ground communication with RIS assistance, considering the actual positions of buildings and ground users. The theoretical lower bound on the coverage enhancement in satellite-to-ground communication through large-scale RIS deployment is derived. Then a novel optimization framework for RIS placement is formulated, and a parallel genetic algorithm is employed to solve the problem. Simulation results demonstrate the superior performance of the proposed RIS deployment strategy in enhancing satellite communication coverage probability for non-line-of-sight users. The proposed framework can be applied to various architectural distributions, such as rural areas, towns, and cities, by adjusting parameter settings.
摘要
卫星到地面通信中确保可靠和高效连接具有重要挑战。智能表面重配置（RIS）提供了一种有前途的解决方案，因为它可以 manipulate 无线传播环境，从而提高通信性能。在这篇论文中，我们提议了一种改进卫星到地面通信覆盖的方法，通过对建筑物表面的 RIS 的布置优化。我们使用实际的建筑物和地面用户的位置来模拟卫星到地面通信，并 deriv 出了无线传播环境的理论下界。然后，我们提出了一种新的优化框架，并使用并行遗传算法来解决问题。实验结果表明，提议的 RIS 布局策略可以提高卫星通信覆盖率 для非直线视野用户。该提议的框架可以应用于不同的建筑分布，如乡村、小镇和城市，通过调整参数设置。
Channel Estimation and Training Design for Active RIS Aided Wireless Communications
results: 通过提出LS基于通道估计器和ARIS反射 patrern的优化方案，在ARIS频率干扰下实现精度的Channel estimation。Abstract
Active reconfigurable intelligent surface (ARIS) is a newly emerging RIS technique that leverages radio frequency (RF) reflection amplifiers to empower phase-configurable reflection elements (REs) in amplifying the incident signal. Thereby, ARIS can enhance wireless communications with the strengthened ARIS-aided links. In this letter, we propose exploiting the signal amplification capability of ARIS for channel estimation, aiming to improve the estimation precision. Nevertheless, the signal amplification inevitably introduces the thermal noise at the ARIS, which can hinder the acquisition of accurate channel state information (CSI) with conventional channel estimation methods based on passive RIS (PRIS). To address this issue, we further investigate this ARIS-specific channel estimation problem and propose a least-square (LS) based channel estimator, whose performance can be further improved with the design on ARIS reflection patterns at the channel training phase. Based on the proposed LS channel estimator, we optimize the training reflection patterns to minimize the channel estimation error variance. Extensive simulation results show that our proposed design can achieve accurate channel estimation in the presence of the ARIS noises.
摘要
新出现的活动可配置表面技术（ARIS）可以使用 радио频率（RF）反射增强器来强制配置阶段元件（RE），从而提高无线通信的信号强度。因此，ARIS可以提高无线通信链路的质量。在这封信中，我们提议利用ARIS增强信号的能力进行频率探测，以提高频率探测的精度。然而，信号增强必然会在ARIS中引入热噪声，这可能会使得传统的频率探测方法（基于被动RIS）难以获得准确的通道状态信息（CSI）。为解决这个问题，我们进一步研究了ARIS特有的频率探测问题，并提出了基于最小二乘（LS）的频率探测器。通过对ARIS反射模式的设计，我们可以在频率探测阶段进行训练，以最小化频率探测错误偏差的变量。通过我们的设计，我们可以在ARIS噪声的存在下实现准确的频率探测。Note: Simplified Chinese is also known as "Mandarin" or "Standard Chinese".
Pilot Design and Signal Detection for Symbiotic Radio over OFDM Carriers
results: 实验结果表明，采用后向扩展��构 CE 可以提高主传输的性能，并且无需直接链接，primary和secondary传输都可以通过后向扩展��构 CE 支持。同时，研究还发现了symbol synchronization error的敏感性。Abstract
Symbiotic radio (SR) is a promising solution to achieve high spectrum- and energy-efficiency due to its spectrum sharing and low-power consumption properties, in which the secondary system achieves data transmissions by backscattering the signal originating from the primary system. In this paper, we are interested in the pilot design and signal detection when the primary transmission adopts orthogonal frequency division multiplexing (OFDM). In particular, to preserve the channel orthogonality among the OFDM sub-carriers, each secondary symbol is designed to span an entire OFDM symbol. The comb-type pilot structure is employed by the primary transmission, while the preamble pilot structure is used by the secondary transmission. With the designed pilot structures, the primary signal can be detected via the conventional methods by treating the secondary signal as a part of the composite channel, i.e., the effective channel of the primary transmission. Furthermore, the secondary signal can be extracted from the estimated composite channel with the help of the detected primary signal. The bit error rate (BER) performance with both perfect and estimated CSI, the diversity orders of the primary and secondary transmissions, and the sensitivity to symbol synchronization error are analyzed. Simulation results show that the performance of the primary transmission is enhanced thanks to the backscatter link established by the secondary transmission. More importantly, even without the direct link, the primary and secondary transmissions can be supported via only the backscatter link.
摘要
共生射频（SR）是一种有前途的解决方案，可以实现高频率和能量效率，因为它可以共享频率和低功率的特性。在本文中，我们关注的是主传输的预测设计和信号检测，当主传输采用分多样频分复用（OFDM）时。为保持OFDM子帧之间的频率独立性，我们将每个次级符号设计为覆盖整个OFDM符号。主传输使用comb型预测结构，而次传输使用预测预测结构。通过我们设计的预测结构，主信号可以通过传统方法检测，即将次信号视为主信道的一部分，即效果频道。此外，次信号还可以通过对估计的主信道进行拓展来提取。我们分析了基于完美和估计的频道状况信息（CSI）的比特错误率（BER）性能，主和次传输的多样度，以及符号同步错误的敏感度。 simulation results show that the performance of the primary transmission is enhanced due to the backscatter link established by the secondary transmission. Moreover, even without the direct link, the primary and secondary transmissions can be supported via only the backscatter link.
Goal-Oriented Wireless Communication Resource Allocation for Cyber-Physical Systems
results: 这篇论文的结果表明，通过使用目标导向的无线通信资源分配框架，可以提高 CPS 的性能和效率，并且可以应用于多种应用场景，如数据驱动决策、边缘学习、联合学习和分布式优化。Abstract
The proliferation of novel industrial applications at the wireless edge, such as smart grids and vehicle networks, demands the advancement of cyber-physical systems. The performance of CPSs is closely linked to the last-mile wireless communication networks, which often become bottlenecks due to their inherent limited resources. Current CPS operations often treat wireless communication networks as unpredictable and uncontrollable variables, ignoring the potential adaptability of wireless networks, which results in inefficient and overly conservative CPS operations. Meanwhile, current wireless communications often focus more on throughput and other transmission-related metrics instead of CPS goals. In this study, we introduce the framework of goal-oriented wireless communication resource allocations, accounting for the semantics and significance of data for CPS operation goals. This guarantees optimal CPS performance from a cybernetic standpoint. We formulate a bandwidth allocation problem aimed at maximizing the information utility gain of transmitted data brought to CPS operation goals. Since the goal-oriented bandwidth allocation problem is a large-scale combinational problem, we propose a divide-and-conquer and greedy solution algorithm. The information utility gain is first approximately decomposed into marginal utility information gains and computed in a parallel manner. Subsequently, the bandwidth allocation problem is reformulated as a knapsack problem, which can be further solved greedily with a guaranteed sub-optimality gap. We further demonstrate how our proposed goal-oriented bandwidth allocation algorithm can be applied in four potential CPS applications, including data-driven decision-making, edge learning, federated learning, and distributed optimization.
摘要
随着无线边缘应用的增多，如智能网络和车辆网络，质量体系的发展受到推动。无线通信网络的性能对智能体系的运行起到关键作用，但现有的智能体系操作方法通常忽略无线通信网络的可变性和可控性，导致不必要地保守和不效率。同时，现有的无线通信往往更关注传输速率和其他传输相关指标，而忽略智能体系的操作目标。在本研究中，我们提出了基于目标的无线通信资源分配框架，考虑智能体系操作目标的 semantics和重要性。这保证了智能体系的最佳性从Cybernetic standpoint。我们将传输数据带来智能体系操作目标的信息价值增量作为目标函数，并将其分解为各个数据项的独立 marginal utility information gain。然后，我们将带来的带宽分配问题转化为一个knapsack问题，可以通过简单的贪婪算法解决。我们进一步示出了我们提出的目标带宽分配算法在四种可能的智能体系应用中的应用，包括数据驱动决策、边缘学习、联合学习和分布式优化。
Energy-Efficient Multidimensional Constellation Based on Leech Lattice for Visible Light Communications
results: numerical results表明，对比 existed method，这个方法可以 дости得更高的优化和更好的性能。Abstract
In this paper, a 24-dimensional geometrically-shaped constellation design based on Leech lattice is presented for indoor visible light communications (VLCs) with a peak-and an average-intensity input constraints. Firstly, by leveraging tools from large deviation theory, we characterize second-order asymptotics of the optimal constellation shaping region under aforementioned intensity constraints, which further refine our previous results in [Chen. et. al, 2020]. Within the optimal geometrical shaping region, we develop an energy-efficient 24-dimensional constellation design, where a significant coding gain brought by the Leech lattice and the nearly-maximum shaping gain are incorporated by using a strategy called coarsely shaping and finely coding. Fast algorithms for constellation mapping and demodulation are presented as well. Numerical results verifies the superiority of our results as compared with existing methods.
摘要
在这篇论文中，我们提出了一种基于Leech lattice的24维геометри设计，用于indoor可见光通信（VLC），并且受到峰值和平均输入强度的限制。我们首先通过大偏移理论工具来描述在上述强度限制下的最佳形态域的第二阶偏移，这也是我们在[陈等，2020]中的进一步发展。在最佳的 геометри设计区域内，我们开发了一种能效的24维数字编码设计，其中Leech lattice和高效编码具有较高的编码准确率。此外，我们还提出了一种名为“粗化编码”的策略，可以充分利用Leech lattice的优势。我们还提供了快速的 constellation mapping 和解译算法。 numerics 结果表明，我们的结果与现有方法相比具有显著的优势。
Multi-User Multi-IoT-Device Symbiotic Radio: A Novel Massive Access Scheme for Cellular IoT
results: 在考虑到的系统中，通过使用 robust 设计方法和 semi-definite programming 和 difference-of-convex programming 算法，可以最小化 transmit 功率，同时满足 cellular 传输残弱概率和 IoT 传输总比特率的约束。Abstract
Symbiotic radio (SR) is a promising technique to support cellular Internet-of-Things (IoT) by forming a mutualistic relationship between IoT and cellular transmissions. In this paper, we propose a novel multi-user multi-IoT-device SR system to enable massive access in cellular IoT. In the considered system, the base station (BS) transmits information to multiple cellular users, and a number of IoT devices simultaneously backscatter their information to these users via the cellular signal. The cellular users jointly decode the information from the BS and IoT devices. Noting that the reflective links from the IoT devices can be regarded as the channel uncertainty of the direct links, we apply the robust design method to design the beamforming vectors at the BS. Specifically, the transmit power is minimized under the cellular transmission outage probability constraints and IoT transmission sum rate constraints. The algorithm based on semi-definite programming and difference-of-convex programming is proposed to solve the power minimization problem. Moreover, we consider a special case where each cellular user is associated with several adjacent IoT devices and propose a direction of arrival (DoA)-based transmit beamforming design approach. The DoA-based approach requires only the DoA and angular spread (AS) of the direct links instead of the instantaneous channel state information (CSI) of the reflective link channels, leading to a significant reduction in the channel feedback overhead. Simulation results have substantiated the multi-user multi-IoT-device SR system and the effectiveness of the proposed beamforming approaches. It is shown that the DoA-based beamforming approach achieves comparable performance as the CSI-based approach in the special case when the ASs are small.
摘要
симбиотиче radio (SR) 是一种有前途的技术，用于支持 cellular Internet of Things (IoT) by forming a mutualistic relationship between IoT and cellular transmissions. 在本文中，我们提议一种新的多用户多 IoT 设备 SR 系统，以实现大规模访问在 cellular IoT 中。在考虑的系统中，基站 (BS) 发送信息给多个 cellular 用户，而多个 IoT 设备同时借鉴了这些用户的信号来反射其信息。用户们共同解码基站和 IoT 设备之间的信息。注意到反射链的不确定性可以视为 direct link 的通道不确定性，我们采用了Robust 设计方法来设计基站的扫描向量。特别是，在 cellular 传输残留概率和 IoT 传输总速率的限制下，我们将 transmit 功率进行最小化。我们提出了一种基于 semi-definite programming 和差异 convex programming 的算法来解决功率最小化问题。此外，我们考虑了每个 cellular 用户与邻近的多个 IoT 设备之间的特殊情况，并提出了一种方向 Of Arrival (DoA) 基于的传输扫描设计方法。DoA 基于方法只需要 DoA 和 Angular Spread (AS) 的直接链 instead of instantaneous channel state information (CSI) 的反射链通道的状态信息，从而减少了通道反馈过程的卫星负担。实验结果证明了多用户多 IoT 设备 SR 系统和我们提议的扫描方法的有效性。结果表明，在特殊情况下，当 AS 较小时，DoA 基于方法与 CSI 基于方法的性能相似。