paper_authors: Tuan Anh Le, Xin-She Yang for: 这种纸是用于解决多变量函数目标和约束的优化框架中的一种通用火fly算法(FA)。methods: 提议使用一种通用的火fly算法(FA)来解决下降传输焊缝问题，包括约束函数和目标函数为多变量独立优化变量。results: 对四个示例问题进行了解释，包括经典传输焊缝、认知焊缝、嵌入智能表面帮助传输焊缝和嵌入智能表面帮助无线电力传输。计算复杂性分析表明，在大天线 режимом下，提议的FA方法需要较少的计算复杂性，但需要更高的复杂性 than iterative和successive convex approximation（SCA）方法。实验结果表明，提议的FA方法可以达到与IPM的全球最优解相同的解决方案，而且在经典传输焊缝、RIS帮助传输焊缝和RIS帮助无线电力传输中，FA方法可以超越iterative、IPM和SCA方法。Abstract
This paper proposes a generalized Firefly Algorithm (FA) to solve an optimization framework having objective function and constraints as multivariate functions of independent optimization variables. Four representative examples of how the proposed generalized FA can be adopted to solve downlink beamforming problems are shown for a classic transmit beamforming, cognitive beamforming, reconfigurable-intelligent-surfaces-aided (RIS-aided) transmit beamforming, and RIS-aided wireless power transfer (WPT). Complexity analyzes indicate that in large-antenna regimes the proposed FA approaches require less computational complexity than their corresponding interior point methods (IPMs) do, yet demand a higher complexity than the iterative and the successive convex approximation (SCA) approaches do. Simulation results reveal that the proposed FA attains the same global optimal solution as that of the IPM for an optimization problem in cognitive beamforming. On the other hand, the proposed FA approaches outperform the iterative, IPM and SCA in terms of obtaining better solution for optimization problems, respectively, for a classic transmit beamforming, RIS-aided transmit beamforming and RIS-aided WPT.
摘要
Translated into Simplified Chinese:这篇论文提出一种通用的Firefly算法（FA），用于解决多变量函数和约束的优化框架问题。论文展示了四种示例，用于采用提议的通用FA来解决传输磁场Synthesizing、认知磁场Synthesizing、智能表面帮助传输磁场Synthesizing和智能表面帮助无线电能耗 Transfer（WPT）问题。复杂性分析表明，在大antenna regime下，提议的FA方法比其相应的内点方法（IPM）更具计算效率，但需要更高的计算复杂性 than iterative和successive Convex Approximation（SCA）方法。实验结果表明，提议的FA方法可以达到与IPM相同的全局最优解的global optimal solution，而且在认知磁场Synthesizing问题中，提议的FA方法超过iterative、IPM和SCA方法。
DPSS-based Codebook Design for Near-Field XL-MIMO Channel Estimation
results: simulation结果表明，提出的代码书设计方法可以具有较高的压缩感知性和较低的泄漏效应，同时可以高效地估计靠近场通信道。Abstract
Future sixth-generation (6G) systems are expected to leverage extremely large-scale multiple-input multiple-output (XL-MIMO) technology, which significantly expands the range of the near-field region. While accurate channel estimation is essential for beamforming and data detection, the unique characteristics of near-field channels pose additional challenges to the effective acquisition of channel state information. In this paper, we propose a novel codebook design, which allows efficient near-field channel estimation with significantly reduced codebook size. Specifically, we consider the eigen-problem based on the near-field electromagnetic wave transmission model. Moreover, we derive the general form of the eigenvectors associated with the near-field channel matrix, revealing their noteworthy connection to the discrete prolate spheroidal sequence (DPSS). Based on the proposed near-field codebook design, we further introduce a two-step channel estimation scheme. Simulation results demonstrate that the proposed codebook design not only achieves superior sparsification performance of near-field channels with a lower leakage effect, but also significantly improves the accuracy in compressive sensing channel estimation.
摘要
未来第六代（6G）系统预计会利用非常大规模多输入多输出（XL-MIMO）技术，这将大幅扩展近场区域的范围。准确频率预测是扫描和数据检测中关键的一环，但近场通道特有的特征会对有效地获取频率状态信息提出更多的挑战。在这篇论文中，我们提出了一种新的编码ebook设计，允许高效地近场频率预测，同时减少编码ebook的大小。 Specifically，我们基于近场电磁波传输模型来解决近场电磁波传输的eigen-问题。此外，我们还 derive了近场通道矩阵的特征值和特征向量的总体形式，发现它们与杂谱圆柱形数列（DPSS）之间存在深刻的连接。基于我们的近场编码ebook设计，我们还提出了两步频率预测方案。实验结果表明，我们的编码ebook设计不仅可以高效地压缩近场通道，同时也可以大幅提高压缩感知通道预测的准确性。
results: 提出的converter被通过several filter orders、center frequencies和oversampling ratios的行为 simulations validate，并且对op-amp circuit实现进行了考虑，显示了first-order op-amp non-idealities的效果。最后，通过Monte Carlo simulations， demonstrate the robustness against component variations.Abstract
In this paper, the design flexibility of the control-bounded analog-to-digital converter principle is demonstrated. A band-pass analog-to-digital converter is considered as an application and case study. We show how a low-pass control-bounded analog-to-digital converter can be translated into a band-pass version where the guaranteed stability, converter bandwidth, and signal-to-noise ratio are preserved while the center frequency for conversion can be positioned freely. The proposed converter is validated with behavioral simulations on several filter orders, center frequencies, and oversampling ratios. Additionally, we consider an op-amp circuit realization where the effects of first-order op-amp non-idealities are shown. Finally, robustness against component variations is demonstrated by Monte Carlo simulations.
摘要
在本文中，我们示出了控制bounded的报文数字转换原理的设计灵活性。我们使用了带通量的报文数字转换器作为应用和案例研究。我们表明了一种low-pass控制bounded的报文数字转换器可以被翻译成带通量版本，保持稳定性、转换宽度和信号噪声比，并且可以自由地调整中心频率。我们通过多个筛ORDER、中心频率和抽样比例的行为仿真进行验证。此外，我们还考虑了一种op-amp电路实现，其中表明了首次逻辑不 idealities的效果。最后，我们通过Monte Carlo仿真展示了对Component变化的Robustness。
Probabilistic Constellation Shaping for OFDM-Based ISAC Signaling
results: 本论文的结果显示，使用 PCS 方法可以实现一个可扩展的 S&C 贡献平衡，并且在numerical simulations中证明了这种方法的超越性。Abstract
Integrated Sensing and Communications (ISAC) has garnered significant attention as a promising technology for the upcoming sixth-generation wireless communication systems (6G). In pursuit of this goal, a common strategy is that a unified waveform, such as Orthogonal Frequency Division Multiplexing (OFDM), should serve dual-functional roles by enabling simultaneous sensing and communications (S&C) operations. However, the sensing performance of an OFDM communication signal is substantially affected by the randomness of the data symbols mapped from bit streams. Therefore, achieving a balance between preserving communication capability (i.e., the randomness) while improving sensing performance remains a challenging task. To cope with this issue, in this paper we analyze the ambiguity function of the OFDM communication signal modulated by random data. Subsequently, a probabilistic constellation shaping (PCS) method is proposed to devise the probability distributions of constellation points, which is able to strike a scalable S&C tradeoff of the random transmitted signal. Finally, the superiority of the proposed PCS method over conventional uniformly distributed constellations is validated through numerical simulations.
摘要
integrated sensing and communications (ISAC) 已经引起了广泛的关注，作为未来 sixth-generation wireless communication systems (6G) 的可能技术。为实现这个目标，一个常见的策略是使用 unified waveform，如orthogonal frequency division multiplexing (OFDM)，以实现同时的 sensing and communications (S&C) 操作。然而，OFDM 通信信号的探测性能受到数据符号的随机性的影响，因此保持通信能力（即随机性）的同时提高探测性能是一项挑战。为解决这个问题，本文分析 OFDM 通信信号模拟了随机数据的异步函数。然后，一种 probabilistic constellation shaping (PCS) 方法是提出来，以设计均匀分布的星座点概率分布，能够实现可扩展的 S&C 质量规则。最后，通过数值仿真，validate了提议的 PCS 方法的超越性。
New Fast Transform for Orthogonal Frequency Division Multiplexing
results: 本研究发现，使用FCT算法可以实现OFDM系统中具有更好的对�hash-Hadamard变换（CHT）和快速傅立宝（FFT）的复合效果，并且可以实现更好的对�hash-Hadamard变换（CHT）和快速傅立宝（FFT）的复合效果，并且可以实现更好的对�hash-Hadamard变换（CHT）和快速傅立宝（FFT）的复合效果。此外，提出了一个新的OFDM系统，使用FCT算法，并评估了其性能。结果显示，提案的CT-OFDM可以实现更好的对�hash-Hadamard变换（CHT）和快速傅立宝（FFT）的复合效果，并且可以实现更好的对�hash-Hadamard变换（CHT）和快速傅立宝（FFT）的复合效果。Abstract
In this paper, a new fast and low complexity transform is introduced for orthogonal frequency division multiplexing (OFDM) wireless systems. The new transform combines the effects of fast complex-Walsh-Hadamard transform (CHT) and the fast Fourier transform (FFT) into a single unitary transform named in this paper as the complex transition transform (CTT). The development of a new algorithm for fast calculation of the CT transform called FCT is found to have all the desirable properties such as in-place computation, simple indexing scheme and considerably lower arithmetic complexity than existing algorithms. Furthermore, a new OFDM system using the FCT algorithm is introduced and its performance has been evaluated. The proposed CT-OFDM achieves a noticeable reduction in peak-to-average-power-ratio (PAPR) and a significant improvement in the bit-error-rate (BER) performance compared with the conventional OFDM.
摘要
在本文中，一种新的快速低复杂度变换被介绍到了分割多播发射系统中。该变换结合了快速复杂威尔逊哈达姆变换（CHT）和快速傅立叶变换（FFT）的效果，并将其称为复杂过渡变换（CTT）。本文提出了一种新的快速计算CT变换的算法，称为快速CT变换算法（FCT），该算法具有占位计算、简单的索引方式和较低的数学复杂性。此外，一种使用FCT算法的新的OFDM系统被引入，其性能被评估。提出的CT-OFDM系统可以减少峰值平均功率比（PAPR）和提高比特错误率（BER）的性能，与传统的OFDM系统相比有显著的改善。
Vision-Based Reconfigurable Intelligent Surface Beam Tracking for mmWave Communications
results: 研究结果表明，在插入智能表面后，多pathComponents会出现，其中一个路径的功率在堵塞情况下可以是关键，而在线视和非线视情况下都可以 observer capacity提高。Abstract
Reconfigurable intelligent surfaces have emerged as a technology with the potential to enhance wireless communication performance for 5G and beyond. However, the technology comes with challenges in areas such as complexity, power consumption, and cost. This paper demonstrates a computer vision-based reconfigurable intelligent surface beamforming algorithm that addresses complexity and cost issues and analyzes the multipath components that arise from the insertion of such a device into the wireless channel. The results show that a reconfigurable intelligent surface can provide an additional multipath component. The power of this additional path can be critical in blockage scenarios, and a capacity increase can be perceived in both line-of-sight and non line-of-sight scenarios.
摘要
《可重配置智能表面技术在5G和以后的无线通信中表现出了潜在的提高性。然而，这技术受到复杂性、功耗和成本等因素的影响。本文提出了基于计算机视觉的可重配置智能表面扫描算法，解决了复杂性和成本问题，同时分析了在插入此设备到无线通信频道时产生的多Path分量。结果表明，可重配置智能表面可以提供一个额外的多Path分量，其功率在堵塞情况下可以是关键，在线视和非线视情况下都可以观察到容量增加。》Note that the translation is in Simplified Chinese, which is the standard writing system used in mainland China. If you need the translation in Traditional Chinese, please let me know.
SCAN-MUSIC: An Efficient Super-resolution Algorithm for Single Snapshot Wide-band Line Spectral Estimation
results: 该论文的算法可以减少标准 MUSIC 算法的计算复杂性，同时保持一定的分辨率。其性能与当前最佳算法相当，且在处理具有岛屿结构的线谱时更为可靠。Abstract
We propose an efficient algorithm for reconstructing one-dimensional wide-band line spectra from their Fourier data in a bounded interval $[-\Omega,\Omega]$. While traditional subspace methods such as MUSIC achieve super-resolution for closely separated line spectra, their computational cost is high, particularly for wide-band line spectra. To address this issue, we proposed a scalable algorithm termed SCAN-MUSIC that scans the spectral domain using a fixed Gaussian window and then reconstructs the line spectra falling into the window at each time. For line spectra with cluster structure, we further refine the proposed algorithm using the annihilating filter technique. Both algorithms can significantly reduce the computational complexity of the standard MUSIC algorithm with a moderate loss of resolution. Moreover, in terms of speed, their performance is comparable to the state-of-the-art algorithms, while being more reliable for reconstructing line spectra with cluster structure. The algorithms are supplemented with theoretical analyses of error estimates, sampling complexity, computational complexity, and computational limit.
摘要
我们提出了一种高效的算法来重建一维宽频线谱在固定区间 [[-\Ω, \Ω]] 中的重建问题。传统的子空间方法如 MUSIC 可以在紧邻的线谱上实现超解析，但其计算成本高、特别是对宽频线谱。为解决这个问题，我们提出了一种可扩展的算法 termed SCAN-MUSIC，它在 spectral 频域中使用固定的 Gaussian 窗口进行扫描，然后在每个时间点上重建落入窗口内的线谱。对于具有嵌入结构的线谱，我们进一步改进了提议的算法使用抑制器技术。这些算法可以在标准 MUSIC 算法的计算复杂度中减少计算复杂度，同时保持与现状算法相同的速度性和可靠性。我们还提供了算法的理论分析，包括错误估计、抽象复杂度、计算复杂度和计算限制。
User Association and Resource Allocation in Large Language Model Based Mobile Edge Computing System over Wireless Communications
results: 透过实验，本篇论文证明了其提出的DASHF算法的效能，并提供了有用的问题解决方案，对于实现高效的语言模型服务在移动设备上提供了重要的启示。Abstract
In the rapidly evolving landscape of large language models (LLMs) and mobile edge computing, the need for efficient service delivery to mobile users with constrained computational resources has become paramount. Addressing this, our paper delves into a collaborative framework for model training where user data and model adapters are shared with servers to optimize performance. Within this framework, users initially update the first several layers of the adapters while freezing the other layers of them, leveraging their local datasets. Once this step is complete, these partially trained parameters are transmitted to servers. The servers, equipped with more robust computational capabilities, then update the subsequent layers. After this training, they send the enhanced parameters back to the users. This collaborative training approach ensures that mobile users with limited computational capacities can still benefit from advanced LLM services without being burdened by exhaustive computations. Central to our methodology is the DASHF algorithm, which encapsulates the Dinkelbach algorithm, alternating optimization, semidefinite relaxation (SDR), the Hungarian method, and a pioneering fractional programming technique from our recent IEEE JSAC paper "Human-Centric Resource Allocation in the Metaverse over Wireless Communications". The crux of DASHF is its capability to reformulate an optimization problem as Quadratically Constrained Quadratic Programming (QCQP) via meticulously crafted transformations, making it solvable by SDR and the Hungarian algorithm. Through extensive simulations, we demonstrate the effectiveness of the DASHF algorithm, offering significant insights for the advancement of collaborative LLM service deployments.
摘要
在大型语言模型（LLM）和移动边缘 computing 的快速演进中，为了提供对移动用户的有效服务，尤其是具有限制的计算资源，已经成为非常重要。我们的论文探讨了一个合作框架，其中用户的数据和模型适配器被分享到服务器，以便优化性能。在这个框架中，用户首先对适配器的前几层进行更新，并免除其他层的固定，利用本地数据集。一旦这步完成，这些部分训练的参数将被传递到服务器。服务器，具有更强大的计算能力，则对后续层进行更新。之后，这些优化的参数将被发送回用户。这个合作训练方法确保了移动用户具有有限的计算能力仍然能够享受进步的 LLN 服务，不会受到复杂的计算所拘束。我们的方法中心在 DASHF 算法，这个算法包含了 Dinkelbach 算法、分布式优化、正方形relaxation（SDR）、匈牙利方法和我们在 IEEE JSAC 上发表的“人类中心资源分配在Metaverse中的无线通信”一文中的创新分程式技术。DASHF 算法的核心在于可以通过精心设计的转换，将优化问题转换为 quadratic constraints quadratic programming（QCQP），使其可以通过 SDR 和匈牙利算法解决。经过广泛的 simulations，我们证明了 DASHF 算法的有效性，提供了进一步探讨合作 LLN 服务部署的重要意义。
Resource Allocation for Near-Field Communications: Fundamentals, Tools, and Outlooks
paper_authors: Bokai Xu, Jiayi Zhang, Hongyang Du, Zhe Wang, Yuanwei Liu, Dusit Niyato, Bo Ai, Khaled B. Letaief
for: 本文主要研究近场通信系统中的资源分配问题，以实现高 spectral efficiency (SE) 和 energy efficiency (EE)。
methods: 本文使用 numerical techniques 和 machine learning methods 来解决近场资源分配问题，并且 highlighted their strengths and limitations。
results: 本文指出了近场通信系统中可用的资源，并且 Summarized optimization tools for addressing near-field resource allocation.Abstract
Extremely large-scale multiple-input-multiple output (XL-MIMO) is a promising technology to achieve high spectral efficiency (SE) and energy efficiency (EE) in future wireless systems. The larger array aperture of XL-MIMO makes communication scenarios closer to the near-field region. Therefore, near-field resource allocation is essential in realizing the above key performance indicators (KPIs). Moreover, the overall performance of XL-MIMO systems heavily depends on the channel characteristics of the selected users, eliminating interference between users through beamforming, power control, etc. The above resource allocation issue constitutes a complex joint multi-objective optimization problem since many variables and parameters must be optimized, including the spatial degree of freedom, rate, power allocation, and transmission technique. In this article, we review the basic properties of near-field communications and focus on the corresponding "resource allocation" problems. First, we identify available resources in near-field communication systems and highlight their distinctions from far-field communications. Then, we summarize optimization tools, such as numerical techniques and machine learning methods, for addressing near-field resource allocation, emphasizing their strengths and limitations. Finally, several important research directions of near-field communications are pointed out for further investigation.
摘要
非常大规模多输入多输出（XL-MIMO）技术是未来无线系统中实现高频率效率（SE）和能效率（EE）的有力方案。XL-MIMO的更大的天线组合使得通信场景更接近近场区域。因此，近场资源分配是实现上述关键性表达指标（KPI）的重要前提。此外，XL-MIMO系统的总性性能强度取决于选择用户的通道特性，通过扫描、功率控制等技术消除用户之间的干扰。以上资源分配问题构成了复杂的共同多目标优化问题，因为需要优化多个变量和参数，包括空间度的自由度、速率、功率分配和传输技术。在本文中，我们介绍了近场通信的基本性能和相关的"资源分配"问题。首先，我们确定了近场通信系统中可用的资源和与远场通信系统的区别。然后，我们总结了优化工具，如数值技术和机器学习方法，用于解决近场资源分配问题，强调其优点和局限性。最后，我们指出了进一步研究近场通信的重要研究方向。