arXiv subjects

Guangyue Lu

Publications and source records attributed to Guangyue Lu.

17 recordsLinked to original sources

arXiv2026

Do Ambient Backscatter Communication Receivers Require Low-Noise Amplifiers?

In ambient backscatter communication (AmBC), strong direct interference from the ambient source poses a major challenge to reliable symbol detection. Although previous studies have shown that employing a low-noise amplifier (LNA) in conventional point-to-point communication improves symbol detection performance at low-to-moderate transmission power, it remains unclear whether this improvement also holds for AmBC. To respond it, in this work, we investigate the symbol detection performance of an AmBC receiver that is equipped with an LNA and adopts the energy detection (ED) to recover tag's information. Particularly, we first propose a new AmBC symbol detection framework that incorporates LNA parameters. On this basis, we derive the bit error rate (BER) of the ED and employ the deflection coefficient (DC) to demonstrate that the detection performance can be enhanced by the LNA at low-to-moderate ambient source transmission power. Then, we derive the near-optimal detection threshold to minimize the BER and propose a method to estimate the required parameters for this threshold by leveraging the tag's pilot symbols.

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arXiv2025

Symbol Detection in Multi-channel Multi-tag Ambient Backscatter Communication Under IQ Imbalance

Ambient backscatter communication (AmBC) offers low-cost and low-power connectivity for Internet of Things (IoT), where a backscatter tag (BT) modulates incident signals transmitted by an ambient radio frequency (RF) source and reflects them to its associated AmBC receiver. In multi-channel multi-tag AmBC, one of major challenges from the aspect of symbol detection is the image channel crosstalk, which is induced by the inevitable in-phase/quadrature (IQ) imbalance. To address this issue, in this paper, we study symbol detection in multi-channel multi-tag AmBC under IQ imbalance. Considering the differential encoding scheme at the BTs, we propose a novel symbol detection model that incorporates IQ imbalance parameters, the presence or absence of both the incident signal and the backscattered signal of the image channel. On this basis, considering an energy difference detector at the AmBC receiver, we derive the closed-form expressions for the bit error rate (BER) as well as the near-optimal detection threshold to minimize BER. However, calculating the near-optimal detection threshold requires prior information, such as the IQ imbalance parameters, the presence probability of the incident signal of the image channel and the backscattered signal of the image channel, the signal power of the ambient RF source, and the noise power, which are typically unknown to the AmBC receiver in practice. To eliminate the need for the prior information, we propose a threshold estimation method using the received samples. Numerical results indicate that under IQ imbalance, directly using the existing method leads to a significant degradation in BER performance. However, this degradation can be effectively mitigated by our derived detection threshold.

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arXiv2025

Gaussian Copula-Based Outage Performance Analysis of Fluid Antenna Systems: Channel Coefficient- or Envelope-Level Correlation Matrix?

Gaussian copula has been employed to evaluate the outage performance of Fluid Antenna Systems (FAS), with the covariance matrix reflecting the dependence among multivariate normal random variables (RVs). While prior studies approximate this matrix using the channel coefficient correlation matrix from Jake's model, this work instead employs the channel envelope correlation matrix, motivated by the fact that the multivariate normal RVs are generated by transforming correlated channel envelopes. This raises an open question of whether using the coefficient- or envelope-level correlation matrix yields better accuracy in accessing FAS performance. Toward this end, this paper explores the benefits of using the envelope-level correlation matrix under fully correlated Nakagami-m fading, and develops a method for generating such fading channels for Monte Carlo simulations, which serve as a benchmark for validating the theoretical results. Simulation results confirm the effectiveness of the proposed channel modeling approach and demonstrate the superior accuracy of using the envelope-level correlation matrix, particularly in sparse port deployment and low-outage regime.

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arXiv2025

Performance Analysis of Single-Antenna Fluid Antenna Systems via Extreme Value Theory

In single-antenna fluid antenna systems (FASs), the transceiver dynamically selects the antenna port with the strongest instantaneous channel to enhance link reliability. However, deriving accurate yet tractable performance expressions under fully correlated fading remains challenging, primarily due to the absence of a closed-form distribution for the FAS channel. To address this gap, this paper develops a novel performance evaluation framework for FAS operating under fully correlated Rayleigh fading, by modeling the FAS channel through extreme value distributions (EVDs). We first justify the suitability of EVD modeling and approximate the FAS channel through the Gumbel distribution, with parameters expressed as functions of the number of ports and the antenna aperture size via the maximum likelihood (ML) criterion. Closed-form expressions for the outage probability (OP) and ergodic capacity (EC) are then derived. While the Gumbel model provides an excellent fit, minor deviations arise in the extreme-probability regions. To further improve accuracy, we extend the framework using the generalized extreme value (GEV) distribution and obtain closed-form OP and EC approximations based on ML-derived parameters. Simulation results confirm that the proposed GEV-based framework achieves superior accuracy over the Gumbel-based model, while both EVD-based approaches offer computationally efficient and analytically tractable tools for evaluating the performance of FAS under realistic correlated fading conditions.

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arXiv2025

UniGTE: Unified Graph-Text Encoding for Zero-Shot Generalization across Graph Tasks and Domains

Generalizing to unseen graph tasks without task-specific supervision is challenging: conventional graph neural networks are typically tied to a fixed label space, while large language models (LLMs) struggle to capture graph structure. We introduce UniGTE, an instruction-tuned encoder-decoder framework that unifies structural and semantic reasoning. The encoder augments a pretrained autoregressive LLM with learnable alignment tokens and a structure-aware graph-text attention mechanism, enabling it to attend jointly to a tokenized graph and a natural-language task prompt while remaining permutation-invariant to node order. This yields compact, task-aware graph representations. Conditioned solely on these representations, a frozen LLM decoder predicts and reconstructs: it outputs the task answer and simultaneously paraphrases the input graph in natural language. The reconstruction objective regularizes the encoder to preserve structural cues. UniGTE is instruction-tuned on five datasets spanning node-level, edge-level, and graph-level tasks across diverse domains, yet requires no fine-tuning at inference. It achieves new state-of-the-art zero-shot results on node classification, link prediction, graph classification, and graph regression under cross-task and cross-domain settings, demonstrating that tight integration of graph structure with LLM semantics enables robust, transferable graph reasoning.

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arXiv2025

Symbol Timing Synchronization and Signal Detection for Ambient Backscatter Communication

Ambient backscatter communication (AmBC) enables ambient Internet of Things (AIoT) devices to achieve ultra-low-power, low-cost, and massive connectivity. Most existing AmBC studies assume ideal synchronization between the backscatter device (BD) and the backscatter receiver (BR). However, in practice, symbol timing offset (STO) occurs due to both the propagation delay and the BR activation latency, which leads to unreliable symbol recovery at the BR. Moreover, the uncontrollable nature of the ambient radio frequency source renders conventional correlation-based synchronization methods infeasible in AmBC. To address this challenge, we investigate STO estimation and symbol detection in AmBC without requiring coordination from the ambient radio frequency source. Firstly, we design a specialized pilot sequence at the BD to induce sampling errors in the pilot signal. Furthermore, we propose a pilot-based STO estimator using the framework of maximum likelihood estimation (MLE), which can exploit the statistical variations in the received pilot signal. Finally, we integrate STO compensation into an energy detector and evaluate the bit error rate (BER) performance. Simulation results show that the proposed estimator achieves accurate STO estimation and effectively mitigates the BER performance degradation caused by STO.

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arXiv2025

Graph-R1: Incentivizing the Zero-Shot Graph Learning Capability in LLMs via Explicit Reasoning

Generalizing to unseen graph tasks without task-pecific supervision remains challenging. Graph Neural Networks (GNNs) are limited by fixed label spaces, while Large Language Models (LLMs) lack structural inductive biases. Recent advances in Large Reasoning Models (LRMs) provide a zero-shot alternative via explicit, long chain-of-thought reasoning. Inspired by this, we propose a GNN-free approach that reformulates graph tasks--node classification, link prediction, and graph classification--as textual reasoning problems solved by LRMs. We introduce the first datasets with detailed reasoning traces for these tasks and develop Graph-R1, a reinforcement learning framework that leverages task-specific rethink templates to guide reasoning over linearized graphs. Experiments demonstrate that Graph-R1 outperforms state-of-the-art baselines in zero-shot settings, producing interpretable and effective predictions. Our work highlights the promise of explicit reasoning for graph learning and provides new resources for future research.

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arXiv2025

Revolutionizing Symbiotic Radio: Exploiting Tradeoffs in Hybrid Active-Passive Communications

Symbiotic radio (SR), a novel energy- and spectrum-sharing paradigm of backscatter communications (BC), has been deemed a promising solution for ambient Internet of Things (A-IoT), enabling ultra-low power consumption and massive connectivity. However, A-IoT nodes utilizing BC suffer from low transmission rates, which may limit the applications of SR in A-IoT scenarios with data transmission requirements. To address this issue, in this article, we introduce hybrid active-passive communications (HAPC) into SR by exploiting tradeoffs between transmission rate and power consumption. We first present an overview of novel BC paradigms including ambient BC and SR. Then, a novel HAPC-enabled SR is proposed to enhance the transmission rate of A-IoT nodes. Furthermore, within this paradigm, we investigate the resource allocation scheme and present preliminary research results. Simulation results show that the transmission rate of A-IoT nodes in the proposed HAPC-enabled SR surpasses that in traditional SR. Finally, we discuss open issues related to HAPC-enabled SR.

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arXiv2023

Is the Performance of NOMA-aided Integrated Sensing and Multicast-Unicast Communications Improved by IRS?

In this paper, we consider intelligent reflecting surface (IRS) in a non-orthogonal multiple access (NOMA)-aided Integrated Sensing and Multicast-Unicast Communication (ISMUC) system, where the multicast signal is used for sensing and communications while the unicast signal is used only for communications. Our goal is to depict whether the IRS improves the performance of NOMA-ISMUC system or not under the imperfect/perfect successive interference cancellation (SIC) scenario. Towards this end, we formulate a non-convex problem to maximize the unicast rate while ensuring the minimum target illumination power and multicast rate. To settle this problem, we employ the Dinkelbach method to transform this original problem into an equivalent one, which is then solved via alternating optimization algorithm and semidefinite relaxation (SDR) with Sequential Rank-One Constraint Relaxation (SROCR). Based on this, an iterative algorithm is devised to obtain a near-optimal solution. Computer simulations verify the quick convergence of the devised iterative algorithm, and provide insightful results. Compared to NOMA-ISMUC without IRS, IRS-aided NOMA-ISMUC achieves a higher rate with perfect SIC but keeps the almost same rate in the case of imperfect SIC.

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arXiv2022

Impacts of Hardware Impairments on Mutualistic Cooperative Ambient Backscatter Communications

In mutualistic cooperative ambient backscatter communications (AmBC), Internet-of-Things (IoT) device sends its information to a desired receiver by modulating and backscattering the primary signal, while providing beneficial multipath diversity to the primary receiver in return, thus forming a mutualism relationship between the AmBC and primary links. We note that the hardware impairments (HIs), which are unavoidable in practical systems and may significantly affect the transmission rates of the primary and AmBC links and their mutualism relationships, have been largely ignored in the study of mutualistic cooperative AmBC networks. In this paper, we consider a mutualistic cooperative AmBC network under HIs, and study the impacts of HIs on the achievable rates of the primary link and the AmBC link. In particular, we theoretically prove that although HIs degrades the rate of each link, the mutualism relationship between the AmBC and primary links is maintained, i.e., the rate of the primary link in the mutualistic cooperative AmBC network is still higher than that without the AmBC link. The closed-form rate expressions of both the AmBC and primary links are derived. Computer simulations are provided to validate our theoretical analysis.

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arXiv2021

System Outage Probability and Diversity Analysis of SWIPT Enabled Two-Way DF Relaying under Hardware Impairments

This paper investigates the system outage performance of a simultaneous wireless information and power transfer (SWIPT) based two-way decode-and-forward (DF) relay network, where potential hardware impairments (HIs) in all transceivers are considered. After harvesting energy and decoding messages simultaneously via a power splitting scheme, the energy-limited relay node forwards the decoded information to both terminals. Each terminal combines the signals from the direct and relaying links via selection combining. We derive the system outage probability under independent but non-identically distributed Nakagami-m fading channels. It reveals an overall system ceiling (OSC) effect, i.e., the system falls in outage if the target rate exceeds an OSC threshold that is determined by the levels of HIs. Furthermore, we derive the diversity gain of the considered network. The result reveals that when the transmission rate is below the OSC threshold, the achieved diversity gain equals the sum of the shape parameter of the direct link and the smaller shape parameter of the terminal-to-relay links; otherwise, the diversity gain is zero. This is different from the amplify-and-forward (AF) strategy, under which the relaying links have no contribution to the diversity gain. Simulation results validate the analytical results and reveal that compared with the AF strategy, the SWIPT based two-way relaying links under the DF strategy are more robust to HIs and achieve a lower system outage probability.

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arXiv2020

System Outage Probability of PS-SWIPT Enabled Two-Way AF Relaying with Hardware Impairments

In this paper, we investigate the system outage probability of a simultaneous wireless information and power transfer (SWIPT) based two-way amplify-and-forward (AF) relay network considering transceiver hardware impairments (HIs), where the energy-constrained relay node processes the received signals based on a power splitting protocol and the two terminals employ a selection combining (SC) scheme to exploit the signals from the direct and relaying links. Assuming independent but non-identically distributed Nakagami-m fading channels, we derive the system outage probability in a closed-form, which enables us to identify two crucial ceiling effects on the system outage probability caused by HIs in the high data rate regions, i.e., relay cooperation ceiling (RCC) and overall system ceiling (OSC). Specifically, the RCC prevents the relaying link from participating in cooperative communications, while the OSC leaves the overall system in outage. Furthermore, we derive the achievable diversity gain of the considered network, which shows that the diversity gain equals either the shape parameter of the direct link or zero. Computer simulations are provided to validate the correctness of our analytical results, and study the effects of various system parameters on the system outage performance and the optimal power splitting ratio, as well as the energy efficiency.

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arXiv2020

Computation Bits Maximization in a Backscatter Assisted Wirelessly Powered MEC Network

In this paper, we introduce a backscatter assisted wirelessly powered mobile edge computing (MEC) network, where each edge user (EU) can offload task bits to the MEC server via hybrid harvest-then-transmit (HTT) and backscatter communications. In particular, considering a practical non-linear energy harvesting (EH) model and a partial offloading scheme at each EU, we propose a scheme to maximize the weighted sum computation bits of all the EUs by jointly optimizing the backscatter reflection coefficient and time, active transmission power and time, local computing frequency and execution time of each EU. By introducing a series of auxiliary variables and using the properties of the non-linear EH model, we transform the original non-convex problem into a convex one and derive closedform expressions for parts of the optimal solutions. Simulation results demonstrate the advantage of the proposed scheme over benchmark schemes in terms of weighted sum computation bits.

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arXiv2020

On the Outage Performance of Ambient Backscatter Communications

Ambient backscatter communications (AmBackComs) have been recognized as a spectrum- and energy-efficient technology for Internet of Things, as it allows passive backscatter devices (BDs) to modulate their information into the legacy signals, e.g., cellular signals, and reflect them to their associated receivers while harvesting energy from the legacy signals to power their circuit operation. {\color{black} However, the co-channel interference between the backscatter link and the legacy link and the non-linear behavior of energy harvesters at the BDs have largely been ignored in the performance analysis of AmBackComs. Taking these two aspects, this paper provides a comprehensive outage performance analysis for an AmBackCom system with multiple backscatter links}, where one of the backscatter links is opportunistically selected to leverage the legacy signals transmitted in a given resource block. For any selected backscatter link, we propose an adaptive reflection coefficient (RC), which is adapted to the non-linear energy harvesting (EH) model and the location of the selected backscatter link, to minimize the outage probability of the backscatter link. In order to study the impact of co-channel interference on both backscatter and legacy links, for a selected backscatter link, we derive the outage probabilities for the legacy link and the backscatter link. Furthermore, we study the best and worst outage performances for the backscatter system where the selected backscatter link maximizes or minimizes the signal-to-interference-plus noise ratio (SINR) at the backscatter receiver. We also study the best and worst outage performances for the legacy link where the selected backscatter link results in the lowest and highest co-channel interference to the legacy receiver, respectively.

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arXiv2019

Energy-efficient Resource Allocation for Wirelessly Powered Backscatter Communications

In this letter, we consider a wireless-powered backscatter communication (WP-BackCom) network, where the transmitter first harvests energy from a dedicated energy RF source in the sleep state, and then backscatters information and harvests energy simultaneously through a reflection coefficient. Our goal is to maximize the achievable energy efficiency of the WP-BackCom network via jointly optimizing time allocation, reflection coefficient and transmit power of the dedicated energy RF source. The optimization problem is non-convex and challenging to solve. We develop an efficient Dinkelbach-based iterative algorithm to obtain the optimal resource allocation scheme. The study shows that for each iteration, the energy-efficient WP-BackCom network is equivalent to either the network in which the transmitter always operates in the active state, or the network in which the dedicated energy RF source adopts the maximum allowed power.

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arXiv2019

On the Performance and Optimization for MEC Networks Using Uplink NOMA

In this paper, we investigate a non-orthogonal multiple access (NOMA) based mobile edge computing (MEC) network, in which two users may partially offload their respective tasks to a single MEC server through uplink NOMA. We propose a new offloading scheme that can operate in three different modes, namely the partial computation offloading, the complete local computation, and the complete offloading. We further derive a closed-form expression of the successful computation probability for the proposed scheme. As part of the proposed offloading scheme, we formulate a problem to maximize the successful computation probability by jointly optimizing the time for offloading, the power allocation of the two users and the offloading ratios which decide how many tasks should be offloaded to the MEC server. We obtain the optimal solutions in the closed forms. Simulation results show that our proposed scheme can achieve the highest successful computation probability than the existing schemes.

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arXiv2019

On the Outage Performance of SWIPT Based Three-step Two-way DF Relay Networks

In this paper, we study the outage performance of simultaneous wireless information and power transfer (SWIP- T) based three-step two-way decode-and-forward (DF) relay networks, where both power-splitting (PS) and harvest-then-forward are employed. In particular, we derive the expressions of terminal-to-terminal (T2T) and system outage probabilities based on a Gaussian-Chebyshev quadrature approximation, and obtain the T2T and system outage capacities. The effects of various system parameters, e.g., the static power allocation ratio at the relay, symmetric PS, as well as asymmetric PS, on the outage performance of the investigated network are examined. It is shown that our derived expression for T2T outage capacity is more accurate than existing analytical results, and that the asymmetric PS achieves a higher system outage capacity than the symmetric one when the channels between the relay node and the terminal nodes have different statistic gains.

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