arXiv subjects

Yijin Zhang

Publications and source records attributed to Yijin Zhang.

At least 19 recordsLinked to original sources

arXiv2026

One-Dimensional Electronic States in a Moiré Superlattice of Twisted Bilayer WTe2

One-dimensional (1D) moiré superlattices provide a new route to engineering reduced-dimensional electronic states in van der Waals materials, yet their electronic structure and microscopic origin remain largely unexplored. Here, we investigate the structural relaxation and electronic properties of a 1D moiré superlattice formed in twisted bilayer 1T$'$-WTe$_2$ using density functional theory calculations, complemented by high-angle annular dark-field scanning transmission electron microscopy. We show that lattice relaxation strongly reconstructs the moiré stripes, leading to stacking-dependent stripe widths that are in excellent agreement with experimental observations. The relaxed structure hosts quasi-one-dimensional electronic bands near the Fermi level, characterized by strong dispersion along the stripe direction and nearly flat dispersion in the perpendicular direction. By comparing the full bilayer with isolated relaxed layers, we establish that these 1D electronic states are governed predominantly by an intralayer moiré potential induced by in-plane lattice relaxation, rather than by interlayer hybridization. We extract this position-dependent moiré potential directly from DFT calculations and construct an effective tight-binding model that reproduces both the band dispersion and the real-space localization of the electronic wave functions. Our results identify lattice relaxation as the key mechanism underlying 1D electronic states in 1D moiré superlattices. %and establish twisted bilayer WTe$_2$ as a promising platform for exploring emergent one-dimensional moiré physics. The framework developed here provides a unified theoretical basis for realizing and exploring one-dimensional moiré physics in a broad class of anisotropic two-dimensional materials.

cond-mat.mes-hall↗

arXiv2026

Raman spectroscopy of van der Waals topological magnet GdGaI

We report polarization-resolved Raman spectroscopy of a van der Waals compound GdGaI that is a candidate for excitonic insulators. By combining the symmetry analysis with density functional theory calculations, we identify six Raman-active phonons. The spectra exhibit only the expected anharmonic hardening down to 4 K: no additional peaks, no soft modes, and no signatures of zone folding are observed. This result indicates that any lattice distortion is below our experimental sensitivity, supporting an electronically driven origin for the band reconstruction reported by angle-resolved photoemission spectroscopy rather than an electron-phonon-driven mechanism. Moreover, we observe a pronounced circular dichroism of the $A_{1g}$ modes under an out-of-plane magnetic field. Based on symmetry considerations, we attribute this dichroic response to chiral $A_{1g}$ phonons with opposite angular momenta generated by spin-phonon coupling in the time-reversal-broken state. The temperature evolution of the degree of circular polarization further suggests that circularly polarized Raman spectroscopy detects the emergence of short-range antiferromagnetic correlations. Our results highlight GdGaI as a promising platform in which excitonic order, magnetism, and circularly polarized phonons can be intertwined, and demonstrate that circular-polarization Raman provides a sensitive probe of spin-phonon coupling in excitonic systems.

cond-mat.mtrl-sci↗

arXiv2026

Multichannel Conflict-Avoiding Codes for Expanded Scenarios

A conflict-avoiding code (CAC) of length L and weight w is used for deterministic multiple-access without feedback. When the number of simultaneous active users is less than or equal to w, such a code is able to provide a hard guarantee that each active user has a successful transmission within every consecutive L time slots. Recently, CACs were extended to multichannel CAcs (MC-CACs) over M orthogonal channels with the aim of increasing the number of potential users that can be supported. While most existing results on MC-CAC are derived under the assumption that M is not less than w, this paper focuses on the case that M is less than w, which is more relevant to practical application scenarios. In this paper, we first introduce the concept of exceptional codewords in MC-CACs. By employing some techniques from additive combinatorics, we derive a series of optimal MC-CACs. Along the way, several previously known optimal CAC results are generalized. Finally, our results extend naturally to AM-OPPTS MC-CACs and mixed-weight MC-CACs, two classes of relevant codes.

cs.IT↗

arXiv2026

Emergent Cooperative Superstructures via Order-Disorder Kinetics in Molecule-Intercalated NbSe2

The design of quantum states at heterointerfaces has enabled a variety of emergent phenomena. Among them, molecular intercalation superlattices have attracted attention as tunable hybrid materials, formed by inserting organic molecules into van der Waals crystals, where molecular structure and chemistry provide new degrees of freedom. Traditionally, the intercalated molecules have been regarded as inactive spacers, while possible molecular ordering and its impact on the host lattice have remained largely unexplored. Here, we report the discovery of a cooperative superstructure (CSS) phase in molecule intercalated NbSe2, where ordering of the guest molecules induce a concomitant superstructure in the NbSe2 host lattice, characterized by a moiré structure due to incommensurability between the molecular layer and the inorganic lattice. Synchrotron X-ray diffraction reveals the emergence of CSS phase, accompanied by crystal symmetry lowering. Complementary resistivity and thermal-quench measurements show that the transition is governed by unusually slow order-disorder kinetics, so that the CSS phase can be selectively accessed under standard laboratory cooling rates. This kinetic behavior arises from slow molecular dynamics coupled to the host lattice, contrasting with fast charge or magnetic ordering in inorganic solids. Our findings establish molecular ordering as a route for engineering heterointerfaces, enabling thermally programmable superstructures.

cond-mat.mtrl-sci↗

arXiv2025

Age of Information for Constrained Scheduling with Imperfect Feedback

This paper considers a downlink system where an access point sends the monitored status of multiple sources to multiple users. By jointly accounting for imperfect feedback and constrained transmission rate, which are key limited factors in practical systems, we aim to design scheduling algorithms to optimize the age of information (AoI) over the infinite time horizon. For zero feedback under the generate-at-will traffic, we derive a closed-form lower bound of achievable AoI, which, to the best of our knowledge, reflects the impact of zero feedback for the first time, and propose a policy that achieves this bound in many cases by jointly applying rate splitting and modular arithmetic. For zero feedback under the Bernoulli traffic, we develop a drift-plus-penalty (DPP) policy with a threshold structure based on the theory of Lyapunov optimization and provide a closed-form performance guarantee. Furthermore, we extend the design of this DPP policy to support general imperfect feedback without increasing the online computational complexity. Numerical results verify our theoretical analysis and the AoI advantage of the proposed policies over state-of-the-art policies.

cs.IT↗

arXiv2024

The Undirected Optical Indices of Trees

For a connected graph $G$, an instance $I$ is a set of pairs of vertices and a corresponding routing $R$ is a set of paths specified for all vertex-pairs in $I$. Let $\mathfrak{R}_I$ be the collection of all routings with respect to $I$. The undirected optical index of $G$ with respect to $I$ refers to the minimum integer $k$ to guarantee the existence of a mapping $ϕ:R\to\{1,2,\ldots,k\}$, such that $ϕ(P)\neqϕ(P')$ if $P$ and $P'$ have common edge(s), over all routings $R\in\mathfrak{R}_I$. A natural lower bound of the undirected optical index is the edge-forwarding index, which is defined to be the minimum of the maximum edge-load over all possible routings. Let $w(G,I)$ and $π(G,I)$ denote the undirected optical index and edge-forwarding index with respect to $I$, respectively. In this paper, we derive the inequality $w(T,I_A)<\frac{3}{2}π(T,I_A)$ for any tree $T$, where $I_A:=\{\{x,y\}:\,x,y\in V(T)\}$ is the all-to-all instance.

math.CO↗

arXiv2024

Optimal Constant-Weight and Mixed-Weight Conflict-Avoiding Codes

A conflict-avoiding code (CAC) is a deterministic transmission scheme for asynchronous multiple access without feedback. When the number of simultaneously active users is less than or equal to $w$, a CAC of length $L$ with weight $w$ can provide a hard guarantee that each active user has at least one successful transmission within every consecutive $L$ slots. In this paper, we generalize some previously known constructions of constant-weight CACs, and then derive several classes of optimal CACs by the help of Kneser's Theorem and some techniques in Additive Combinatorics. Another spotlight of this paper is to relax the identical-weight constraint in prior studies to study mixed-weight CACs for the first time, for the purpose of increasing the throughput and reducing the access delay of some potential users with higher priority. As applications of those obtained optimal CACs, we derive some classes of optimal mixed-weight CACs.

cs.IT↗

arXiv2024

Analysis Methodology for Age of Information under Sequence Based Scheduling

We focus on the Age of Information (AoI) performance in a system where each user generates packets periodically to send to a common access point (AP) for status updating. To avoid heavy overhead, we assume that channel sensing, feedback information from the AP, and time synchronization are not available in the system. We adopt a multi-access scheme called the sequence scheme, where each user is assigned a periodic binary sequence to schedule their transmissions. In our previous work [18], we have thoroughly studied the AoI performance under sequence scheme when the period of schedule sequences, $L$, is equal to the status generating period, $T$. The results can be extended to the case where $T>L$. However, the case of $T<L$ is not covered by [18]. Therefore, in this paper, we concentrate on analyzing the AoI performance in the case of $T<L$, which is more challenging and requires different approaches. We conduct in-depth analysis on this case and develop a mathematical tool based on integer partitions to facilitate the analysis. We derive low-complexity closed-form expressions for two scenarios under $T<L$. Based on the obtained analytical results, we propose an algorithm to optimize the construction parameters of the sequence scheme. Finally, we compare our proposed sequence scheme with two commonly used baselines, and show that our proposed scheme outperforms the baselines in terms of AoI performance while consuming less energy.

cs.IT↗

arXiv2024

Content Caching-Assisted Vehicular Edge Computing Using Multi-Agent Graph Attention Reinforcement Learning

In order to avoid repeated task offloading and realize the reuse of popular task computing results, we construct a novel content caching-assisted vehicular edge computing (VEC) framework. In the face of irregular network topology and unknown environmental dynamics, we further propose a multi-agent graph attention reinforcement learning (MGARL) based edge caching scheme, which utilizes the graph attention convolution kernel to integrate the neighboring nodes' features of each agent and further enhance the cooperation among agents. Our simulation results show that our proposed scheme is capable of improving the utilization of caching resources while reducing the long-term task computing latency compared to the baselines.

cs.MA↗

arXiv2024

Tunneling photo-thermoelectric effect in monolayer graphene/bilayer hexagonal boron nitride/bilayer graphene asymmetric van der Waals tunnel junctions

Graphene is known to exhibit a pronounced photo-thermoelectric effect (PTE) in its in-plane carrier transport and attracting attention toward various optoelectronic applications. In this study, we demonstrate an out-of-plane PTE by utilizing electron tunneling across a barrier, namely, the tunneling photo-thermoelectric effect (TPTE). This was achieved in a monolayer graphene (MLG)/bilayer hexagonal boron nitride (h-BN)/bilayer graphene (BLG) asymmetric tunnel junction. MLG and BLG exhibit different cyclotron resonance (CR) optical absorption energies when their energies are Landau quantized under an out-of-plane magnetic field. We tuned the magnetic field under mid-infrared (MIR) irradiation to bring MLG into CR conditions, whereas BLG was not in CR. The CR absorption in the MLG generates an electron temperature difference between the MLG and BLG, and induces an out-of-plane TPTE voltage across the h-BN tunnel barrier. The TPTE exhibited a unique dependence on the Fermi energy of the MLG, which differed from that of the in-plane PTE of the MLG. The TPTE signal was large when the Fermi energy of the MLG was tuned near the phase transition between the quantum Hall state (QHS) and non-QHS, that is, the transition between carrier localization and delocalization. The TPTE provides another degree of freedom for probing the electronic and optoelectronic properties of two-dimensional material heterostructures.

cond-mat.mes-hall↗

arXiv2024

Age-Gain-Dependent Random Access for Event-Driven Periodic Updating

This paper considers utilizing the knowledge of age gains to reduce the network average age of information (AoI) in random access with event-driven periodic updating for the first time. Built on the form of slotted ALOHA, we require each device to determine its age gain threshold and transmission probability in an easily implementable decentralized manner, so that the unavoided contention can be limited to devices with age gains as high as possible. For the basic case that each device utilizes its knowledge of age gain of only itself, we provide an analytical modeling approach by a multi-layer discrete-time Markov chains (DTMCs), where an external infinite-horizon DTMC manages the jumps between the beginnings of frames and an internal finite-horizon DTMC manages the evolution during an arbitrary frame. Such modelling enables that optimal access parameters can be obtained offline. For the enhanced case that each device utilizes its knowledge of age gains of all the devices, we require each device to adjust its access parameters for maximizing the estimated network \textit{expected AoI reduction} (EAR) per slot, which captures the essential for improving the contribution of the throughput to the AoI performance. To estimate the network EAR, we require each device to use Bayes' rule to keep a posteriori joint probability distribution of local age and age gain of an arbitrary device based on the channel observations. Numerical results validate our theoretical analysis and demonstrate the advantage of the proposed schemes over the existing schemes in a wide range of network configurations.

cs.IT↗

arXiv2023

DOA Estimation Using Massive Receive MIMO: Basic Principle and Key Techniques

As massive multiple-input multiple-output (MIMO) becomes popular, direction of arrival (DOA) measurement has been made a real renaissance due to the high-resolution achieved. Thus, there is no doubt about DOA estimation using massive MIMO. The purpose of this paper is to describe its basic principles and key techniques, to present the performance analysis, and to appreciate its engineering applications. It is anticipated that there are still many challenges in DOA estimation using massive receive MIMO, such as high circuit cost, high energy consumption and high complexity of the algorithm implementation. New researches and breakthroughs are illustrated to deal with those problems. Then, a new architecture, hybrid analog and digital (HAD) massive receive MIMO with low-resolution ADCs, is presented to strike a good balance among circuit cost, complexity and performance. Then, a novel three-dimensional (3D) angle of arrival (AOA) localization method based on geometrical center is proposed to compute the position of a passive emitter using single base station equipped with an ultra-massive MIMO system. And, it can achieve the Cramer-Rao low bound (CRLB). Here, the performance loss is also analyzed to quantify the minimum number of bits. DOA estimation will play a key role in lots of applications, such as directional modulation, beamforming tracking and alignment for 6G.

cs.IT↗

arXiv2023

Age-of-Information Dependent Random Access for Periodic Updating

This paper considers an uplink Internet of Things system with synchronous periodic traffic, where multiple devices generate their status updates at the beginning of each global frame and attempt to send them to a common access point. To achieve a low network-wide age of information (AoI) in an easily implementable manner, we require each device to adopt an age-dependent random access protocol, i.e., to transmit with a certain probability only when its corresponding AoI reaches a certain threshold. We analyze the time-average expected AoI by a multi-layer Markov model where an external infinite-horizon Markov chain manages the jumps between the beginnings of frames, while two internal finite-horizon Markov chains manage the evolution during an arbitrary frame for different cases. Simulation results verify the accuracy of the modeling and the AoI advantage over age-independent schemes.

cs.IT↗

arXiv2023

Deadline-Constrained Opportunistic Spectrum Access With Spectrum Handoff

This paper considers designing an optimal policy for deadline-constrained access in cognitive radio networks, where a secondary user needs to complete a packet transmission over the vacant spectrum within a delivery deadline. To minimize the total access cost, it is desirable to design an optimal opportunistic access policy by utilizing channel dynamics and sensing outcomes. We take non-negligible switching overheads, a state-dependent overtime penalty, and practical switching operations into consideration in the Markov decision process formulation of such an access problem under wide-band sensing. Moreover, we establish the existence of monotone optimal decision rules to reduce the complexity of computing an optimal policy. Simulation results verify our theoretical studies and the cost advantage over other policies.

eess.SY↗

arXiv2023

Privacy-Preserving Joint Edge Association and Power Optimization for the Internet of Vehicles via Federated Multi-Agent Reinforcement Learning

Proactive edge association is capable of improving wireless connectivity at the cost of increased handover (HO) frequency and energy consumption, while relying on a large amount of private information sharing required for decision making. In order to improve the connectivity-cost trade-off without privacy leakage, we investigate the privacy-preserving joint edge association and power allocation (JEAPA) problem in the face of the environmental uncertainty and the infeasibility of individual learning. Upon modelling the problem by a decentralized partially observable Markov Decision Process (Dec-POMDP), it is solved by federated multi-agent reinforcement learning (FMARL) through only sharing encrypted training data for federatively learning the policy sought. Our simulation results show that the proposed solution strikes a compelling trade-off, while preserving a higher privacy level than the state-of-the-art solutions.

cs.LG↗

arXiv2022

Reinforcement Learning for Improved Random Access in Delay-Constrained Heterogeneous Wireless Networks

In this paper, we for the first time investigate the random access problem for a delay-constrained heterogeneous wireless network. We begin with a simple two-device problem where two devices deliver delay-constrained traffic to an access point (AP) via a common unreliable collision channel. By assuming that one device (called Device 1) adopts ALOHA, we aim to optimize the random access scheme of the other device (called Device 2). The most intriguing part of this problem is that Device 2 does not know the information of Device 1 but needs to maximize the system timely throughput. We first propose a Markov Decision Process (MDP) formulation to derive a model-based upper bound so as to quantify the performance gap of certain random access schemes. We then utilize reinforcement learning (RL) to design an R-learning-based random access scheme, called tiny state-space R-learning random access (TSRA), which is subsequently extended for the tackling of the general multi-device problem. We carry out extensive simulations to show that the proposed TSRA simultaneously achieves higher timely throughput, lower computation complexity, and lower power consumption than the existing baseline--deep-reinforcement learning multiple access (DLMA). This indicates that our proposed TSRA scheme is a promising means for efficient random access over massive mobile devices with limited computation and battery capabilities.

cs.NI↗

arXiv2022

Collaborative Intelligent Reflecting Surface Networks with Multi-Agent Reinforcement Learning

Intelligent reflecting surface (IRS) is envisioned to be widely applied in future wireless networks. In this paper, we investigate a multi-user communication system assisted by cooperative IRS devices with the capability of energy harvesting. Aiming to maximize the long-term average achievable system rate, an optimization problem is formulated by jointly designing the transmit beamforming at the base station (BS) and discrete phase shift beamforming at the IRSs, with the constraints on transmit power, user data rate requirement and IRS energy buffer size. Considering time-varying channels and stochastic arrivals of energy harvested by the IRSs, we first formulate the problem as a Markov decision process (MDP) and then develop a novel multi-agent Q-mix (MAQ) framework with two layers to decouple the optimization parameters. The higher layer is for optimizing phase shift resolutions, and the lower one is for phase shift beamforming and power allocation. Since the phase shift optimization is an integer programming problem with a large-scale action space, we improve MAQ by incorporating the Wolpertinger method, namely, MAQ-WP algorithm to achieve a sub-optimality with reduced dimensions of action space. In addition, as MAQ-WP is still of high complexity to achieve good performance, we propose a policy gradient-based MAQ algorithm, namely, MAQ-PG, by mapping the discrete phase shift actions into a continuous space at the cost of a slight performance loss. Simulation results demonstrate that the proposed MAQ-WP and MAQ-PG algorithms can converge faster and achieve data rate improvements of 10.7% and 8.8% over the conventional multi-agent DDPG, respectively.

cs.MA↗

arXiv2021

Impact of Low-Resolution ADC on DOA Estimation Performance for Massive MIMO Receive Array

In this paper, we present a new scenario of direction of arrival (DOA) estimation using massive multiple-input multiple-output (MIMO) receive array with low-resolution analog-to-digital convertors (ADCs), which can strike a good balance between performance and circuit cost. Based on the linear additive quantization noise model (AQNM), the effect of low-resolution ADCs on the methods, such as Root-MUSIC method, is analyzed. Also, the closed-form expression of Cramer-Rao lower bound (CRLB) is derived to evaluate the performance loss caused by the low-resolution ADCs. The simulation results show that the Root-MUSIC methods can achieve the corresponding CRLB. Furthermore, 2-3 bits are acceptable for most applications if the 1dB performance loss.

cs.IT↗