arXiv subjects

Quanzhong Li

Publications and source records attributed to Quanzhong Li.

9 recordsLinked to original sources

arXiv2026

Real Interference Alignment for Active IRS-Aided Systems: A Rate-Profile Learning-Based Approach

With additional spatial degrees of freedom provided by the active intelligent reflecting surface (IRS), interference alignment (IA) can be achieved at low cost. In this letter, we propose a real IA scheme for an active IRS-aided system. The proposed scheme only requires the IRS to know the instantaneous channel coefficients under the assumption of blocked direct links. To maximize the achievable sum rate subject to individual minimum rate requirements and transmission power constraints, we propose a rate-profile learning-based algorithm. The algorithm uses offline-trained achievable rate profiles to decouple the original problem into multiple feasibility subproblems, which are then solved by generalized eigenvalue decomposition. Simulation results demonstrate that our proposed algorithm outperforms the conventional weighted minimum mean square error algorithm, while requiring significantly less program execution time.

cs.IT↗

arXiv2026

Fluid Antenna System-Enabled Interference Alignment

Interference alignment is an efficient spectrum reuse scheme for multiuser wireless networks. In this letter, assuming no channel state information at the transmitters, we investigate a fluid antenna system (FAS)-enabled interference alignment scheme over a multiuser interference channel. In the proposed system, the additional spatial degrees of freedom provided by the FAS are exploited to nullify the real components of the effective combined interference such that those are reserved for interference-free desired signal detection. The interference alignment conditions and corresponding outage probabilities are theoretically derived. Simulations verify that the theoretically derived outage probabilities agree well with the numerical results. Furthermore, the proposed system is able to achieve a higher average sum rate than conventional single-user transmission schemes over non-interfering channels.

cs.IT↗

arXiv2026

OFDM Enabled Over-the-Air Computation Systems with Two-Dimensional Fluid Antennas

Fluid antenna system (FAS) is able to exploit spatial degrees of freedom (DoFs) in wireless channels. In this letter, to exploit spatial DoFs in frequency-selective environments, we investigate an orthogonal frequency division multiplexing enabled over-the-air computation system, where the access point is equipped with a two-dimensional FAS to enhance performance. We solve the computation mean square error (MSE) minimization problem by transforming the original problem into transmit precoders optimization problem and antenna positions optimization along with receive combiners optimization problem. The latter is solved via a majorization-minimization approach combined with sequential optimization. Numerical results confirm that the proposed scheme achieves MSE reduction over the scheme with fixed position antennas.

cs.IT↗

arXiv2025

Average Secrecy Capacity Maximization of Rotatable Antenna-Assisted Secure Communications

A rotatable antenna, which is able to dynamically adjust its deflection angle, is promising to achieve better physical layer security performance for wireless communications. In this paper, considering practical scenarios with non-real-time rotatable antenna adjustment, we investigate the average secrecy rate maximization problem of a rotatable antenna-assisted secure communication system. We theoretically prove that the objective function of the average secrecy rate maximization problem is quasi-concave with respect to an adjustment factor of the rotatable antenna. Under this condition, the optimal solution can be found by the bisection search. Furthermore, we derive the closed-form optimal deflection angle for the secrecy capacity maximization problem, considering the existence of only line-of-sight components of wireless channels. This solution serves as a near optimal solution to the average secrecy rate maximization problem. Based on the closed-form near optimal solution, we obtain the system secrecy outage probability at high signal-to-noise ratio (SNR). It is shown through simulation results that the near optimal solution achieves almost the same average secrecy capacity as the optimal solution. It is also found that at high SNR, the theoretical secrecy outage probabilities match the simulation ones.

cs.IT↗

arXiv2024

XSema: A Novel Framework for Semantic Extraction of Cross-chain Transactions

As the number of blockchain platforms continues to grow, the independence of these networks poses challenges for transferring assets and information across chains. Cross-chain bridge technology has emerged to address this issue, establishing communication protocols to facilitate cross-chain interaction of assets and information, thereby enhancing user experience. However, the complexity of cross-chain transactions increases the difficulty of security regulation, rendering traditional single-chain detection methods inadequate for cross-chain scenarios. Therefore, understanding cross-chain transaction semantics is crucial, as it forms the foundation for cross-chain security detection tasks. Although there are existing methods for extracting transaction semantics specifically for single chains, these approaches often overlook the unique characteristics of cross-chain scenarios, limiting their applicability. This paper introduces XSema, a novel cross-chain semantic extraction framework grounded in asset transfer and message-passing, designed specifically for cross-chain contexts. Experimental results demonstrate that XSema effectively distinguishes between cross-chain and non-cross-chain transactions, surpassing existing methods by over 9% for the generality metric and over 10% for the generalization metric. Furthermore, we analyze the underlying asset transfer patterns and message-passing event logs associated with cross-chain transactions. We offer new insights into the coexistence of multiple blockchains and the cross-chain ecosystem.

cs.DC↗

arXiv2024

Joint Optimization for Achieving Covertness in MIMO Over-the-Air Computation Networks

This paper investigates covert data transmission within a multiple-input multiple-output (MIMO) over-the-air computation (AirComp) network, where sensors transmit data to the access point (AP) while guaranteeing covertness to the warden (Willie). Simultaneously, the AP introduces artificial noise (AN) to confuse Willie, meeting the covert requirement. We address the challenge of minimizing mean-square-error (MSE) of the AP, while considering transmit power constraints at both the AP and the sensors, as well as ensuring the covert transmission to Willie with a low detection error probability (DEP). However, obtaining globally optimal solutions for the investigated non-convex problem is challenging due to the interdependence of optimization variables. To tackle this problem, we introduce an exact penalty algorithm and transform the optimization problem into a difference-of-convex (DC) form problem to find a locally optimal solution. Simulation results showcase the superior performance in terms of our proposed scheme in comparison to the benchmark schemes.

eess.SP↗

arXiv2022

Temporal Analysis of Transaction Ego Networks with Different Labels on Ethereum

Due to the widespread use of smart contracts, Ethereum has become the second-largest blockchain platform after Bitcoin. Many different types of Ethereum accounts (ICO, Mining, Gambling, etc.) also have quite active trading activities on Ethereum. Studying the transaction records of these specific Ethereum accounts is very important for understanding their particular transaction characteristics, and further labeling the pseudonymous accounts. However, traditional methods are generally based on static and global transaction networks to conduct research, ignoring useful information about dynamic changes. Our work chooses six kinds of important account labels, and builds ego networks for each kind of Ethereum account. We focus on the interaction between the target node and neighbor nodes with temporal analysis. Experiments show that there is a significant difference between various types of accounts in terms of several network features, helping us better understand their transaction patterns. To the best of our knowledge, this is the first work to analyze the dynamic characteristics of Ethereum labeled accounts from the perspective of transaction ego networks.

cs.CR↗

arXiv2019

Beamforming Design in Multiple-Input-Multiple-Output Symbiotic Radio Backscatter Systems

Symbiotic radio (SR) backscatter systems are possible techniques for the future low-power wireless communications for Internet of Things devices. In this paper, we propose a multiple-input-multiple-output (MIMO) SR backscatter system, where the secondary multi-antenna transmission from the backscatter device (BD) to the receiver is riding on the primary multi-antenna transmission from the transmitter to the receiver. We investigate the beamforming design optimization problem which maximizes the achievable rate of secondary transmission under the achievable rate constraint of primary transmission. In the MIMO SR backscatter system, each antenna of the SR BD reflects its received ambient radio frequency signals from all the transmitting antennas of the transmitter, which causes the globally optimal solution is difficult to obtain. In this paper, we propose a method to obtain the achievable rate upper bound. Furthermore, considering both primary and secondary transmissions, we propose an exact penalty method based locally optimal solution. Simulation results illustrate that our proposed exact penalty method based locally optimal solution performs close to the upper bound.

cs.IT↗

arXiv2009

Search Driven Analysis of Heterogenous XML Data

Analytical processing on XML repositories is usually enabled by designing complex data transformations that shred the documents into a common data warehousing schema. This can be very time-consuming and costly, especially if the underlying XML data has a lot of variety in structure, and only a subset of attributes constitutes meaningful dimensions and facts. Today, there is no tool to explore an XML data set, discover interesting attributes, dimensions and facts, and rapidly prototype an OLAP solution. In this paper, we propose a system, called SEDA that enables users to start with simple keyword-style querying, and interactively refine the query based on result summaries. SEDA then maps query results onto a set of known, or newly created, facts and dimensions, and derives a star schema and its instantiation to be fed into an off-the-shelf OLAP tool, for further analysis.

cs.DB↗