arXiv subjects

Yangyang Zhang

Publications and source records attributed to Yangyang Zhang.

At least 37 records · Page 2Linked to original sources

arXiv2025

Codebook-based Port Selection and Combining for CSI-Free Uplink Fluid Antenna Multiple Access

Fluid antenna multiple access (FAMA) has recently emerged as a simple, promising scheme for large-scale multiuser connectivity, offering strong scalability with low implementation complexity. Nevertheless, most existing FAMA studies focus on downlink transmission under perfect channel state information (CSI) at the receiver side, while the uplink counterpart remains largely unexplored. This paper proposes a novel codebook-based port selection and combining (CPSC) FAMA framework for the uplink communications without CSI at the base station (BS). In the proposed scheme, a predefined codebook is designed and broadcast by the BS. Each user equipment (UE) employs a fluid antenna, acquires its local CSI and independently chooses the most suitable codeword, activates the corresponding fluid antenna ports, and determines the combining weights to achieve a two-way match between the selected codeword and the instantaneous effective channel. The BS then separates the superimposed user signals through codebook-guided projection operations without requiring global CSI or multiuser joint optimization. To handle potential codeword collisions, three lightweight scheduling strategies are introduced, offering flexible trade-offs between signaling overhead and collision avoidance. Simulation results demonstrate that the proposed CPSC-FAMA approach achieves substantially higher rates than fixed-antenna systems while maintaining low complexity. Moreover, the results confirm that amortizing the optimization cost over the UEs effectively reduces the BS processing burden and enhances scalability, making the proposed scheme a strong candidate for future sixth-generation (6G) networks.

eess.SP↗

arXiv2025

Fluid Antenna System-Enabled UAV-to-Ground Communications

Fluid antenna systems (FAS) have emerged as a revolutionary technology offering enhanced spatial diversity within a compact form factor. Concurrently, unmanned aerial vehicles (UAVs) are integral to future networks, necessitating channel models that capture both multipath fading and shadowing. This letter presents a novel performance analysis of a UAV-to-ground link, where the receiver is equipped with an $N$-port FAS operating over the challenging double-shadowing fading channel. By adapting a tractable eigenvalue-based approximation for the correlated FAS ports, we derive new analytical expressions for the end-to-end signal-to-noise ratio statistics, namely the cumulative distribution function and the probability density function. Based on these statistics, we present exact integral expressions for the outage probability, average bit error rate, and average channel capacity. We further derive new, tractable closed-form solutions for the average bit error rate and capacity for the practical dual-rank, independent but non-identically distributed case. Finally, a key asymptotic analysis reveals that the system achieves a multiplicative diversity order of $G_d = M \times d$, which is precisely the product of the FAS spatial rank $M$ and the intrinsic channel diversity order $d$. Simulation results are provided to validate the high accuracy of our entire theoretical framework.

cs.IT↗

arXiv2025

Formation of Extremely Low-Mass White Dwarfs in Wide Orbits

Helium white dwarfs (WDs) with masses less than 0.3 $\rm M_{\sun}$ are known as extremely low-mass WDs (ELM WDs), which cannot be produced by single stellar evolution in theory. Generally, these stars are believed to form through binary interactions. Recently, two ELM WDs in unusually wide orbits were reported, i.e., KIC 8145411 and HE 0430-2457. Their orbital separations are too wide to be produced by the binary evolution scenario. In this work, we study the formation of wide-orbit ELM WD binaries from hierarchical triple systems. In this scenario, an ELM WD is formed from the inner binary and subsequently forms a wide binary system with the third object. We find that the merger of an evolved star with a brown dwarf in the inner binary fails to produce single ELM WDs, but Type Ia supernovae (SNe Ia) explosions can successfully do so. Furthermore, we investigate the impact of the supernova explosion on the orbital distribution of the surviving binary and find that this channel may have a probability of reproducing the orbital parameters of HE 0430-2457, but fails to reproduce the observed features of KIC 8145411. This supports recent observational recalibrations suggesting that KIC 8145411 resides in a triple system rather than a binary.

astro-ph.SR↗

arXiv2025

Secure ISAC with Fluid Antenna Systems: Joint Precoding and Port Selection

This paper presents a novel framework for enhancing physical-layer security in integrated sensing and communication (ISAC) systems by leveraging the reconfigurability of fluid antenna systems (FAS). We propose a joint precoding and port selection (JPPS) strategy that maximizes the sum secrecy rate while simultaneously ensuring reliable radar sensing. The problem is formulated using fractional programming (FP) and solved through an iterative algorithm that integrates FP transformations with successive convex approximation (SCA). To reduce computational complexity, we further develop low-complexity schemes based on zero-forcing (ZF) precoding, combined with greedy port selection and trace-inverse minimization. Simulation results demonstrate substantial improvements in both secrecy performance and sensing accuracy compared to conventional baselines, across a wide range of FAS ports, user loads, and sensing targets. These findings highlight the critical importance of FAS geometry optimization in enabling secure and efficient joint communication-sensing for next-generation wireless networks.

eess.SP↗

arXiv2025

Geometric Port Selection in CUMA Systems

Compact ultra-massive antenna-array (CUMA) is a novel multiple access technology built on the fluid antenna system (FAS) concept, offering an improved scheme over fluid antenna multiple access (FAMA) that can support massive connectivity on the same physical channel without the need of precoding and interference cancellation. By employing a simple port-selection mechanism that leverages random channel superposition, CUMA can suppress inter-user interference while keeping hardware costs low. Nevertheless, its ad-hoc port-selection strategy leaves considerable room for optimization. In this work, we revisit CUMA and propose two adaptive single-RF port-selection schemes that retain its simplicity while significantly enhancing performance. The first one, referred to as exact optimal half-space (EOHS), dynamically selects the projection direction that maximizes the instantaneous signal build-up across active ports. To reduce complexity while preserving most of the gains, we furthermore introduce a principal component analysis (PCA)-based scheme, which aligns port partitioning with the dominant statistical direction of per-port channel vectors. This method yields a closed-form low-complexity solution, complemented by a tractable analytical framework that provides a closed-form expression for the signal-to-interference ratio (SIR) probability density function (PDF). Simulation results corroborate the analysis, demonstrating that both EOHS and PCA consistently outperform conventional CUMA across diverse user densities, port counts, and FAS aperture sizes. Notably, PCA achieves performance close to EOHS at a fraction of the computational cost. The proposed schemes scale effectively to large-user regimes, offering a compelling complexity-performance trade-off for next-generation multiple access systems.

eess.SP↗

arXiv2025

Fluid Antenna Systems: A Geometric Approach to Error Probability and Fundamental Limits

The fluid antenna system (FAS) concept is an emerging paradigm that promotes the utilization of the feature of shape and position reconfigurability in antennas to broaden the design of wireless communication systems. This also means that spatial diversity can be exploited in an unconventional way. However, a rigorous framework for error probability analysis of FAS under realistic spatially correlated channels has been lacking. In this paper, we fill this gap by deriving a tight, closed-form asymptotic expression for the symbol error rate (SER) that establishes the fundamental scaling law linking the system's SER to the channel's spatial correlation structure. A key insight of our analysis is that the achievable diversity gain is governed not by the number of antenna ports, but by the channel's effective rank. To find this critical parameter, we propose a novel dual-pronged approach. First of all, we develop a geometry-based algorithm that extracts distinct performance thresholds from the channel's eigenvalue spectrum. Second, we theoretically prove that the effective rank converges to a fundamental limit dictated solely by the antenna's normalized aperture width. We further establish the equivalence between the threshold identified by the geometric algorithm and the derived theoretical limit, providing rigorous validation for the proposed method. Our effective rank model achieves higher accuracy than existing approaches in the literature. Building on this framework, we offer a complete characterization of diversity and coding gains. The analysis leads to a definitive design insight: FAS performance improvements are fundamentally driven by enlarging the antenna's explorable aperture, which increases the effective channel rank, whereas increasing port density within a fixed aperture yields diminishing returns.

cs.IT↗

arXiv2025

A Contemporary Survey on Fluid Antenna Systems: Fundamentals and Networking Perspectives

The explosive growth of teletraffic, fueled by the convergence of cyber-physical systems and data-intensive applications, such as the Internet of Things (IoT), autonomous systems, and immersive communications, demands a multidisciplinary suite of innovative solutions across the physical and network layers. Fluid antenna systems (FAS) represent a transformative advancement in antenna design, offering enhanced spatial degrees of freedom through dynamic reconfigurability. By exploiting spatial flexibility, FAS can adapt to varying channel conditions and optimize wireless performance, making it a highly promising candidate for next-generation communication networks. This paper provides a comprehensive survey of the state of the art in FAS research. We begin by examining key application scenarios in which FAS offers significant advantages. We then present the fundamental principles of FAS, covering channel measurement and modeling, single-user configurations, and the multi-user fluid antenna multiple access (FAMA) framework. Following this, we delve into key network-layer techniques such as quality-of-service (QoS) provisioning, power allocation, and content placement strategies. We conclude by identifying prevailing challenges and outlining future research directions to support the continued development of FAS in next-generation wireless networks.

cs.IT↗

arXiv2025

Fractional Heat Semigroup Characterization of Distances from Functions in Lipschitz Spaces to Their Subspaces

Let $Λ_s$ denote the inhomogeneous Lipschitz space of order $s\in(0,\infty)$ on $\mathbb{R}^n$. This article characterizes the distance $d(f, V)_{Λ_s}: = \inf_{g\in V} \|f-g\|_{Λ_s}$ from a function $f\in Λ_s$ to a non-dense subspace $V\subset Λ_s$ via the fractional semigroup $\{T_{α, t}: =e^{-t (-Δ)^{α/2}}: t\in (0, \infty)\}$ for any $α\in(0,\infty)$. Given an integer $ r >s/α$, a uniformly bounded continuous function $f$ on $\mathbb{R}^n$ belongs to the space $Λ_s$ if and only if there exists a constant $λ\in(0,\infty)$ such that \begin{align*} \left|(-Δ)^{\frac {αr}2} (T_{α, t^α} f)(x) \right|\leq λt^{s -rα}\ \ \text{for any $x\in\mathbb{R}^n$ and $t\in (0, 1]$}.\end{align*} The least such constant is denoted by $λ_{ α, r, s}(f)$. For each $f\in Λ_s$ and $0<\varepsilon< λ_{α,r, s}(f)$, let $$ D_{α, r}(s,f,\varepsilon):=\left\{ (x,t)\in \mathbb{R}^n\times (0,1]:\ \left| (-Δ)^{\frac {αr}2} (T_{α, t^α} f)(x) \right|> \varepsilon t^{s -r α}\right\}$$ be the set of ``bad'' points. To quantify its size, we introduce a class of extended nonnegative \emph{admissible set functions} $ν$ on the Borel $σ$-algebra $\mathcal{B}(\mathbb{R}^n\times [0, 1])$ and define, for any admissible function $ν$, the \emph{critical index} $ \varepsilon_{α, r, s,ν}(f):=\inf\{\varepsilon\in(0,\infty):\ ν(D_{α, r}(s,f,\varepsilon))<\infty\}.$ Our result shows that, for a broad class of subspaces $V\subset Λ_s$, including intersections of $Λ_s$ with Sobolev, Besov, Triebel--Lizorkin, and Besov-type spaces, there exists an admissible function $ν$ depending on $V$ such that $\varepsilon_{α, r, s,ν}(f)\sim \mathrm{dist}(f, V)_{Λ_s}.$

math.FA↗

arXiv2025

Sharp Weighted Cohen--Dahmen--Daubechies--DeVore Inequality with Applications to (Weighted) Critical Sobolev Spaces, Gagliardo--Nirenberg Inequalities, and Muckenhoupt Weights

In this article, we establish a quantitative weighted variant of a far-reaching inequality obtained by A. Cohen, W. Dahmen, I. Daubechies, and R. DeVore in 2003, whose dependence on the $A_p$-weight constant for any $p\in[1,\infty)$ is sharp. As applications, we obtain the almost characterization of the critical weighted Sobolev space in terms of wavelets, a sharp real interpolation between this weighted Sobolev space and weighted Besov spaces, and three new Gagliardo--Nirenberg type inequalities in the framework of ball Banach function spaces. Moreover, we apply this sharp weighted inequality to extend the famous Brezis--Seeger--Van Schaftingen--Yung formula in ball Banach function spaces, which gives an affirmative answer to the question in page 29 of [Calc. Var. Partial Differential Equations 62 (2023), Paper No. 234]. Notably, we further establish two new characterizations of Muckenhoupt weights related to the inequality of Cohen et al.\ and the formula of Brezis et al. The most novelty of this article exists in applying and further developing the good cube method introduced by Cohen et al.\ to trace the sharp dependences on weight constants.

math.CA↗

arXiv2025

Iterative Sparse Asymptotic Minimum Variance Based Channel Estimation in Fluid Antenna System

With fluid antenna system (FAS) gradually establishing itself as a possible enabling technology for next generation wireless communications, channel estimation for FAS has become a pressing issue. Existing methodologies however face limitations in noise suppression. To overcome this, in this paper, we propose a maximum likelihood (ML)-based channel estimation approach tailored for FAS systems, designed to mitigate noise interference and enhance estimation accuracy. By capitalizing on the inherent sparsity of wireless channels, we integrate an ML-based iterative tomographic algorithm to systematically reduce noise perturbations during the channel estimation process. Furthermore, the proposed approach leverages spatial correlation within the FAS channel to optimize estimation accuracy and spectral efficiency. Simulation results confirm the efficacy of the proposed method, demonstrating superior channel estimation accuracy and robustness compared to existing benchmark techniques.

eess.SP↗

arXiv2025

Sharp Brezis--Seeger--Van Schaftingen--Yung Formulae for Higher-Order Gradients in Ball Banach Function Spaces

Let $X$ be a ball Banach function space on $\mathbb{R}^n$, $k\in\mathbb{N}$, $h\in\mathbb{R}^n$, and $Δ^k_h$ denote the $k${\rm th} order difference. In this article, under some mild extra assumptions about $X$, the authors prove that, for both parameters $q$ and $γ$ in \emph{sharp} ranges which are related to $X$ and for any locally integrable function $f$ on ${\mathbb{R}^n}$ satisfying $|\nabla^k f|\in X$, $$ \sup_{λ\in(0,\infty)}λ\left\|\left[\int_{\{h\in\mathbb{R}^n:\ |Δ_h^k f(\cdot)|>λ|h|^{k+\fracγ{q}}\}} \left|h\right|^{γ-n}\,dh\right]^\frac{1}{q}\right\|_X \sim \left\|\,\left|\nabla^k f\right|\,\right\|_{X} $$ with the positive equivalence constants independent of $f$. As applications, the authors establish the Brezis--Seeger--Van Schaftingen--Yung (for short, BSVY) characterization of higher-order homogeneous ball Banach Sobolev spaces and higher-order fractional Gagliardo--Nirenberg and Sobolev type inequalities in critical cases. All these results are of quite wide generality and can be applied to various specific function spaces; moreover, even when $X:= L^{q}$, these results when $k=1$ coincide with the best known results and when $k\ge 2$ are completely new. The first novelty is to establish a sparse characterization of dyadic cubes in level sets related to the higher-order local approximation, which, together with the well-known Whitney inequality in approximation theory, further induces a higher-order weighted variant of the remarkable inequality obtained by A. Cohen, W. Dahmen, I. Daubechies, and R. DeVore; the second novelty is to combine this weighted inequality neatly with a variant higher-order Poincaré inequality to establish the desired upper estimate of BSVY formulae in weighted Lebesgue spaces.

math.FA↗

arXiv2025

Difference and Wavelet Characterizations of Distances from Functions in Lipschitz Spaces to Their Subspaces

Let $Λ_s$ denote the Lipschitz space of order $s\in(0,\infty)$ on $\mathbb{R}^n$, which consists of all $f\in\mathfrak{C}\cap L^\infty$ such that, for some constant $L\in(0,\infty)$ and some integer $r\in(s,\infty)$, \begin{equation*} \label{0-1}Δ_r f(x,y): =\sup_{|h|\leq y} |Δ_h^r f(x)|\leq L y^s, \ x\in\mathbb{R}^n, \ y \in(0, 1]. \end{equation*} Here (and throughout the article) $\mathfrak{C}$ refers to continuous functions, and $Δ_h^r$ is the usual $r$-th order difference operator with step $h\in\mathbb{R}^n$. For each $f\in Λ_s$ and $\varepsilon\in(0,L)$, let $ S(f,\varepsilon):= \{ (x,y)\in\mathbb{R}^n\times [0,1]: \frac {Δ_r f(x,y)}{y^s}>\varepsilon\}$, and let $μ: \mathcal{B}(\mathbb{R}_+^{n+1})\to [0,\infty]$ be a suitably defined nonnegative extended real-valued function on the Borel $σ$-algebra of subsets of $\mathbb{R}_+^{n+1}$. Let $\varepsilon(f)$ be the infimum of all $\varepsilon\in(0,\infty)$ such that $μ(S(f,\varepsilon))<\infty$. The main target of this article is to characterize the distance from $f$ to a subspace $V\cap Λ_s$ of $Λ_s$ for various function spaces $V$ (including Sobolev, Besov--Triebel--Lizorkin, and Besov--Triebel--Lizorkin-type spaces) in terms of $\varepsilon(f)$, showing that \begin{equation*} \varepsilon(f)\sim \mathrm{dist} (f, V\cap Λ_s)_{Λ_s}: = \inf_{g\in Λ_s\cap V} \|f-g\|_{Λ_s}.\end{equation*} Moreover, we present our results in a general framework based on quasi-normed lattices of function sequences $X$ and Daubechies $s$-Lipschitz $X$-based spaces.

math.FA↗

arXiv2025

Fluid Antenna System Empowering 5G NR

Fluid antenna system (FAS) is an emerging technology that uses the new form of shape- and position-reconfigurable antennas to empower the physical layer for wireless communications. Prior studies on FAS were however limited to narrowband channels. Motivated by this, this paper addresses the integration of FAS in the fifth generation (5G) orthogonal frequency division multiplexing (OFDM) framework to address the challenges posed by wideband communications. We propose the framework of the wideband FAS OFDM system that includes a novel port selection matrix. Then we derive the achievable rate expression and design the adaptive modulation and coding (AMC) scheme based on the rate. Extensive link-level simulation results demonstrate striking improvements of FAS in the wideband channels, underscoring the potential of FAS in future wireless communications.

eess.SP↗

arXiv2024

All-in-One: Transferring Vision Foundation Models into Stereo Matching

As a fundamental vision task, stereo matching has made remarkable progress. While recent iterative optimization-based methods have achieved promising performance, their feature extraction capabilities still have room for improvement. Inspired by the ability of vision foundation models (VFMs) to extract general representations, in this work, we propose AIO-Stereo which can flexibly select and transfer knowledge from multiple heterogeneous VFMs to a single stereo matching model. To better reconcile features between heterogeneous VFMs and the stereo matching model and fully exploit prior knowledge from VFMs, we proposed a dual-level feature utilization mechanism that aligns heterogeneous features and transfers multi-level knowledge. Based on the mechanism, a dual-level selective knowledge transfer module is designed to selectively transfer knowledge and integrate the advantages of multiple VFMs. Experimental results show that AIO-Stereo achieves start-of-the-art performance on multiple datasets and ranks $1^{st}$ on the Middlebury dataset and outperforms all the published work on the ETH3D benchmark.

cs.CV↗

arXiv2024

One-Dimensional Ionic-Bonded Structures in NiSe Nanowire

One-dimensional van der Waals (1D vdW) materials, characterized by atomic chains bonded ionically or covalently in one direction and held together by van der Waals interactions in the perpendicular directions, have recently gained intensive attention due to their exceptional functions. In this work, we report the discovery of 1D ionic-bonded structures in NiSe nanowires. Utilizing aberration-corrected scanning transmission electron microscopy, we identified four distinct structural phases composed of two fundamental 1D building blocks: a triangle-shaped unit and a parallelogram-shaped unit. These phases can transform into one another through topotactic combinations of the structural units. Density functional theory calculations reveal that these structural units are bound by ionic bonds, unlike the van der Waals forces typically found in 1D vdW materials. The diverse arrangements of these building blocks may give rise to unique electronic structures and magnetic properties, paving the way for designing advanced materials with novel functionalities.

cond-mat.mes-hall↗

arXiv2024

Constraints on Common Envelope Ejection from Double Helium White Dwarfs

Double helium white dwarfs (He WDs) are one type of gravitational wave source and are greatly important in the studies of binary interaction, particularly in the common envelope (CE) ejection physics. Most double He WDs with mass ratios of q~1 are formed through a particular channel. In this channel, one He WD is initially produced from a red giant (RG) with a degenerate core via stable Roche lobe overflow, and another He WD is formed from an RG with a degenerate core via CE ejection. They may have significant implications for the binary evolution processes yet have not received specific studies, especially for the CE phase. This paper adopts a semi-analytic method and a detailed stellar evolution simulation to model the formation of double He WDs. We find that most double He WDs show mass ratios being slightly greater than 1, and their orbital periods and mass ratios relation are broadly consistent with observations. There is also a relation between the mass ratios and the progenitors' masses of the He WDs produced via CE ejection for double He WDs with determined WD masses. Based on this relation, the mass of the He WD progenitor can be inferred from the mass ratio. Then, the CE ejection efficiency can be constrained with the orbital period. In addition, we constrain the CE ejection efficiency for two double He WDs, J1005-2249 and WD0957-666. The results show that the CE ejection efficiencies increase with the WD progenitor masses.

astro-ph.SR↗

arXiv2024

A Gaussian Copula Approach to the Performance Analysis of Fluid Antenna Systems

This paper investigates the performance of a single-user fluid antenna system (FAS), by exploiting a class of elliptical copulas to describe the dependence structure amongst the fluid antenna positions (ports). By expressing the well-known Jakes' model in terms of the Gaussian copula, we consider two cases: (i) the general case, i.e., any arbitrary correlated fading distribution; and (ii) the specific case, i.e., correlated Nakagami-$m$ fading. For both scenarios, we first derive analytical expressions for the cumulative distribution function (CDF) and probability density function (PDF) of the equivalent channel in terms of multivariate normal distribution. Then we obtain the outage probability (OP) and the delay outage rate (DOR) to analyze the performance of FAS. By employing the popular rank correlation coefficients such as Spearman's $ρ$ and Kendall's $τ$ , we measure the degree of dependency in correlated arbitrary fading channels and illustrate how the Gaussian copula can be accurately connected to Jakes' model in FAS. Our numerical results demonstrate that increasing the size of FAS provides lower OP and DOR, but the system performance saturates as the number of antenna ports increases. In addition, our results indicate that FAS provides better performance compared to conventional single-fixed antenna systems even when the size of fluid antenna is small.

cs.IT↗

arXiv2024

Token-Mol 1.0: Tokenized drug design with large language model

Significant interests have recently risen in leveraging sequence-based large language models (LLMs) for drug design. However, most current applications of LLMs in drug discovery lack the ability to comprehend three-dimensional (3D) structures, thereby limiting their effectiveness in tasks that explicitly involve molecular conformations. In this study, we introduced Token-Mol, a token-only 3D drug design model. This model encodes all molecular information, including 2D and 3D structures, as well as molecular property data, into tokens, which transforms classification and regression tasks in drug discovery into probabilistic prediction problems, thereby enabling learning through a unified paradigm. Token-Mol is built on the transformer decoder architecture and trained using random causal masking techniques. Additionally, we proposed the Gaussian cross-entropy (GCE) loss function to overcome the challenges in regression tasks, significantly enhancing the capacity of LLMs to learn continuous numerical values. Through a combination of fine-tuning and reinforcement learning (RL), Token-Mol achieves performance comparable to or surpassing existing task-specific methods across various downstream tasks, including pocket-based molecular generation, conformation generation, and molecular property prediction. Compared to existing molecular pre-trained models, Token-Mol exhibits superior proficiency in handling a wider range of downstream tasks essential for drug design. Notably, our approach improves regression task accuracy by approximately 30% compared to similar token-only methods. Token-Mol overcomes the precision limitations of token-only models and has the potential to integrate seamlessly with general models such as ChatGPT, paving the way for the development of a universal artificial intelligence drug design model that facilitates rapid and high-quality drug design by experts.

q-bio.BM↗