arXiv subjects

Zhendong Li

Publications and source records attributed to Zhendong Li.

At least 91 records · Page 5Linked to original sources

arXiv2024

MindSpore Quantum: A User-Friendly, High-Performance, and AI-Compatible Quantum Computing Framework

We introduce MindSpore Quantum, a pioneering hybrid quantum-classical framework with a primary focus on the design and implementation of noisy intermediate-scale quantum (NISQ) algorithms. Leveraging the robust support of MindSpore, an advanced open-source deep learning training/inference framework, MindSpore Quantum exhibits exceptional efficiency in the design and training of variational quantum algorithms on both CPU and GPU platforms, delivering remarkable performance. Furthermore, this framework places a strong emphasis on enhancing the operational efficiency of quantum algorithms when executed on real quantum hardware. This encompasses the development of algorithms for quantum circuit compilation and qubit mapping, crucial components for achieving optimal performance on quantum processors. In addition to the core framework, we introduce QuPack, a meticulously crafted quantum computing acceleration engine. QuPack significantly accelerates the simulation speed of MindSpore Quantum, particularly in variational quantum eigensolver (VQE), quantum approximate optimization algorithm (QAOA), and tensor network simulations, providing astonishing speed. This combination of cutting-edge technologies empowers researchers and practitioners to explore the frontiers of quantum computing with unprecedented efficiency and performance.

quant-ph↗

arXiv2024

Quantum computation of conical intersections on a programmable superconducting quantum processor

Conical intersections (CIs) are pivotal in many photochemical processes. Traditional quantum chemistry methods, such as the state-average multi-configurational methods, face computational hurdles in solving the electronic Schrödinger equation within the active space on classical computers. While quantum computing offers a potential solution, its feasibility in studying CIs, particularly on real quantum hardware, remains largely unexplored. Here, we present the first successful realization of a hybrid quantum-classical state-average complete active space self-consistent field method based on the variational quantum eigensolver (VQE-SA-CASSCF) on a superconducting quantum processor. This approach is applied to investigate CIs in two prototypical systems - ethylene (C2H4) and triatomic hydrogen (H3). We illustrate that VQE-SA-CASSCF, coupled with ongoing hardware and algorithmic enhancements, can lead to a correct description of CIs on existing quantum devices. These results lay the groundwork for exploring the potential of quantum computing to study CIs in more complex systems in the future.

quant-ph↗

arXiv2024

Multiple Intelligent Reflecting Surfaces Collaborative Wireless Localization System

This paper studies a multiple intelligent reflecting surfaces (IRSs) collaborative localization system where multiple semi-passive IRSs are deployed in the network to locate one or more targets based on time-of-arrival. It is assumed that each semi-passive IRS is equipped with reflective elements and sensors, which are used to establish the line-of-sight links from the base station (BS) to multiple targets and process echo signals, respectively. Based on the above model, we derive the Fisher information matrix of the echo signal with respect to the time delay. By employing the chain rule and exploiting the geometric relationship between time delay and position, the Cramer-Rao bound (CRB) for estimating the target's Cartesian coordinate position is derived. Then, we propose a two-stage algorithmic framework to minimize CRB in single- and multi-target localization systems by joint optimizing active beamforming at BS, passive beamforming at multiple IRSs and IRS selection. For the single-target case, we derive the optimal closed-form solution for multiple IRSs coefficients design and propose a lowcomplexity algorithm based on alternating direction method of multipliers to obtain the optimal solution for active beaming design. For the multi-target case, alternating optimization is used to transform the original problem into two subproblems where semi-definite relaxation and successive convex approximation are applied to tackle the quadraticity and indefiniteness in the CRB expression, respectively. Finally, numerical simulation results validate the effectiveness of the proposed algorithm for multiple IRSs collaborative localization system compared to other benchmark schemes as well as the significant performance gains.

cs.IT↗

arXiv2024

Combating Advanced Persistent Threats: Challenges and Solutions

The rise of advanced persistent threats (APTs) has marked a significant cybersecurity challenge, characterized by sophisticated orchestration, stealthy execution, extended persistence, and targeting valuable assets across diverse sectors. Provenance graph-based kernel-level auditing has emerged as a promising approach to enhance visibility and traceability within intricate network environments. However, it still faces challenges including reconstructing complex lateral attack chains, detecting dynamic evasion behaviors, and defending smart adversarial subgraphs. To bridge the research gap, this paper proposes an efficient and robust APT defense scheme leveraging provenance graphs, including a network-level distributed audit model for cost-effective lateral attack reconstruction, a trust-oriented APT evasion behavior detection strategy, and a hidden Markov model based adversarial subgraph defense approach. Through prototype implementation and extensive experiments, we validate the effectiveness of our system. Lastly, crucial open research directions are outlined in this emerging field.

cs.CR↗

arXiv2024

Rate-Splitting Multiple Access for Transmissive Reconfigurable Intelligent Surface Transceiver Empowered ISAC System

In this paper, a novel transmissive reconfigurable intelligent surface (TRIS) transceiver empowered integrated sensing and communications (ISAC) system is proposed for future multi-demand terminals. To address interference management, we implement rate-splitting multiple access (RSMA), where the common stream is independently designed for the sensing service. We introduce the sensing quality of service (QoS) criteria based on this structure and construct an optimization problem with the sensing QoS criteria as the objective function to optimize the sensing stream precoding matrix and the communication stream precoding matrix. Due to the coupling of optimization variables, the formulated problem is a non-convex optimization problem that cannot be solved directly. To tackle the above-mentioned challenging problem, alternating optimization (AO) is utilized to decouple the optimization variables. Specifically, the problem is decoupled into three subproblems about the sensing stream precoding matrix, the communication stream precoding matrix, and the auxiliary variables, which is solved alternatively through AO until the convergence is reached. For solving the problem, successive convex approximation (SCA) is applied to deal with the sum-rate threshold constraints on communications, and difference-of-convex (DC) programming is utilized to solve rank-one non-convex constraints. Numerical simulation results verify the superiority of the proposed scheme in terms of improving the communication and sensing QoS.

cs.IT↗

arXiv2024

Antenna Positioning and Beamforming Design for Fluid-Antenna Enabled Multi-user Downlink Communications

This paper investigates a multiple input single output (MISO) downlink communication system in which users are equipped with fluid antennas (FAs). First, we adopt a field-response based channel model to characterize the downlink channel with respect to FAs' positions. Then, we aim to minimize the total transmit power by jointly optimizing the FAs' positions and beamforming matrix. To solve the resulting non-convex problem, we employ an alternating optimization (AO) algorithm based on penalty method and successive convex approximation (SCA) to obtain a sub-optimal solution. Numerical results demonstrate that the FA-assisted communication system performs better than conventional fixed position antennas system.

cs.IT↗

arXiv2023

Physics-Constrained Hardware-Efficient Ansatz on Quantum Computers that is Universal, Systematically Improvable, and Size-consistent

Variational wavefunction ansätze are at the heart of solving quantum many-body problems in physics and chemistry. Previous designs of hardware-efficient ansatz (HEA) on quantum computers are largely based on heuristics and lack rigorous theoretical foundations. In this work, we introduce a physics-constrained approach for designing HEA with rigorous theoretical guarantees by imposing a few fundamental constraints. Specifically, we require that the target HEA to be universal, systematically improvable, and size-consistent, which is an important concept in quantum many-body theories for scalability, but has been overlooked in previous designs of HEA. We extend the notion of size-consistency to HEA, and present a concrete realization of HEA that satisfies all these fundamental constraints while only requiring linear qubit connectivity. The developed physics-constrained HEA is superior to other heuristically designed HEA in terms of both accuracy and scalability, as demonstrated numerically for the Heisenberg model and some typical molecules. In particular, we find that restoring size-consistency can significantly reduce the number of layers needed to reach certain accuracy. In contrast, the failure of other HEA to satisfy these constraints severely limits their scalability to larger systems with more than ten qubits. Our work highlights the importance of incorporating physical constraints into the design of HEA for efficiently solving many-body problems on quantum computers.

quant-ph↗

arXiv2023

A distributed multi-GPU ab initio density matrix renormalization group algorithm with applications to the P-cluster of nitrogenase

The presence of many degenerate $d/f$ orbitals makes polynuclear transition metal compounds such as iron-sulfur clusters in nitrogenase challenging for state-of-the-art quantum chemistry methods. To address this challenge, we present the first distributed multi-GPU (Graphics Processing Unit) \emph{ab initio} density matrix renormalization (DMRG) algorithm, suitable for modern high-performance computing (HPC) infrastructures. The central idea is to parallelize the most computationally intensive part - the multiplication of $O(K^2)$ operators with a trial wavefunction, where $K$ is the number of spatial orbitals, by combining operator parallelism for distributing the workload with a batched algorithm for performing contractions on GPU. With this new implementation, we are able to reach an unprecedentedly large bond dimension $D=14000$ on 48 GPUs (NVIDIA A100 80 GB SXM) for an active space model (114 electrons in 73 active orbitals) of the P-cluster, which is nearly three times larger than the bond dimensions reported in previous DMRG calculations for the same system using only CPUs.

physics.chem-ph↗

arXiv2023

Reconfigurable Intelligent Surface Aided Space Shift Keying With Imperfect CSI

In this paper, we investigate the performance of reconfigurable intelligent surface (RIS)-aided spatial shift keying (SSK) wireless communication systems with imperfect channel state information (CSI). Specifically, we study the average bit error probability (ABEP) of two RIS-SSK systems based on intelligent reflection and blind reflection modes. For the intelligent RIS-SSK scheme, we first derive the conditional pairwise error probability of the composite channel through maximum likelihood (ML) detection. Subsequently, we derive the probability density function of the combined channel. Due to the intricacies of the composite channel formulation, an exact closed-form ABEP expression is unattainable through direct derivation. To this end, we resort to employing the Gaussian-Chebyshev quadrature method to estimate the results. Additionally, we employ Q-function approximation to derive the non-exact closed-form expression in the presence of channel estimation errors. For the blind RIS-SSK scheme, we derive both closed-form ABEP expression and asymptotic ABEP expression with imperfect CSI by adopting the ML detector. To offer deeper insights, we explore the impact of discrete reflection phase shifts on the performance of the RIS-SSK system. Lastly, we extensively validate all the analytical derivations via Monte Carlo simulations.

cs.IT↗

arXiv2023

On the Performance of RIS-Aided Spatial Scattering Modulation for mmWave Transmission

In this paper, we investigate a state-of-the-art reconfigurable intelligent surface (RIS)-assisted spatial scattering modulation (SSM) scheme for millimeter-wave (mmWave) systems, where a more practical scenario that the RIS is near the transmitter while the receiver is far from RIS is considered. To this end, the line-of-sight (LoS) and non-LoS links are utilized in the transmitter-RIS and RIS-receiver channels, respectively. By employing the maximum likelihood detector at the receiver, the conditional pairwise error probability (CPEP) expression for the RIS-SSM scheme is derived under the two scenarios that the received beam demodulation is correct or not. Furthermore, the union upper bound of average bit error probability (ABEP) is obtained based on the CPEP expression. Finally, the derivation results are exhaustively validated by the Monte Carlo simulations.

cs.IT↗

arXiv2023

RIS-Aided Spatial Scattering Modulation for mmWave MIMO Transmissions

This paper investigates the reconfigurable intelligent surface (RIS) assisted spatial scattering modulation (SSM) scheme for millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems, in which line-of-sight (LoS) and non-line-of-sight (NLoS) paths are respectively considered in the transmitter-RIS and RIS-receiver channels. Based on the maximum likelihood detector, the conditional pairwise error probability (CPEP) expression for the RIS-SSM scheme is derived under the two cases of received beam correct and demodulation error. Furthermore, we derive the closed-form expressions of the unconditional pairwise error probability (UPEP) by employing two different methods: the probability density function and the moment-generating function expressions with a descending order of scatterer gains. To provide more useful insights, we derive the asymptotic UPEP and the diversity gain of the RIS-SSM scheme in the high SNR region. Depending on UPEP and the corresponding Euclidean distance, we get the union upper bound of the average bit error probability (ABEP). A new framework for ergodic capacity analysis is also provided to acquire the proposed system's effective capacity. Finally, all derivation results are validated via extensive Monte Carlo simulations, revealing that the proposed RIS-SSM scheme outperforms the benchmarks in terms of reliability.

cs.IT↗

arXiv2023

Robust Weighted Sum-Rate Maximization for Transmissive RIS Transmitter Enabled RSMA Networks

Due to the low power consumption and low cost nature of transmissive reconfigurable intelligent surface (RIS),in this paper, we propose a downlink multi-user rate-splitting multiple access (RSMA) architecture based on the transmissive RIS transmitter, where the channel state information (CSI) is only accquired partially. We investigate the weighted sum-rate maximization problem by jointly optimizing the power, RIS transmissive coefficients and common rate allocated to each user. Due to the coupling of optimization variables, the problem is nonconvex, and it is difficult to directly obtain the optimal solution. Hence, a block coordinate descent (BCD) algorithm based on sample average approximation (SAA) and weighted minimum mean square error (WMMSE) is proposed to tackle it. Numerical results illustrate that the transmissive RIS transmitter with ratesplitting architecture has advantages over conventional space division multiple access (SDMA) and non-orthgonal multiple access (NOMA).

cs.IT↗

arXiv2023

Intelligent Omni Surfaces assisted Integrated Multi Target Sensing and Multi User MIMO Communications

Drawing inspiration from the advantages of intelligent reflecting surfaces (IRS) in wireless networks,this paper presents a novel design for intelligent omni surface (IOS) enabled integrated sensing and communications (ISAC). By harnessing the power of multi antennas and a multitude of elements, the dual-function base station (BS) and IOS collaborate to realize joint active and passive beamforming, enabling seamless 360-degree ISAC coverage. The objective is to maximize the minimum signal-tointerference-plus-noise ratio (SINR) of multi-target sensing, while ensuring the multi-user multi-stream communications. To achieve this, a comprehensive optimization approach is employed, encompassing the design of radar receive vector, transmit beamforming matrix, and IOS transmissive and reflective coefficients. Due to the non-convex nature of the formulated problem, an auxiliary variable is introduced to transform it into a more tractable form. Consequently, the problem is decomposed into three subproblems based on the block coordinate descent algorithm. Semidefinite relaxation and successive convex approximation methods are leveraged to convert the sub-problem into a convex problem, while the iterative rank minimization algorithm and penalty function method ensure the equivalence. Furthermore,the scenario is extended to mode switching and time switching protocols. Simulation results validate the convergence and superior performance of the proposed algorithm compared to other benchmark algorithms.

eess.SP↗

arXiv2023

Transmissive Reconfigurable Intelligent Surface Transmitter Empowered Cognitive RSMA Networks

In this paper, we investigated the downlink transmission problem of a cognitive radio network (CRN) equipped with a novel transmissive reconfigurable intelligent surface (TRIS) transmitter. In order to achieve low power consumption and high-rate multi-streams communication, time-modulated arrays (TMA) is implemented and users access the network using rate splitting multiple access (RSMA). With such a network framework, a multi-objective optimization problem with joint design of the precoding matrix and the common stream rate is constructed to achieve higher energy efficiency (EE) and spectral efficiency (SE). Since the objective function is a non-convex fractional function, we proposed a joint optimization algorithm based on difference-of-convex (DC) programming and successive convex approximation (SCA). Numerical results show that under this framework the proposed algorithm can considerably improve and balance the EE and SE.

eess.SP↗

arXiv2023

Design and Optimization for Transmissive RIS Transceiver Enabled Uplink Communication Systems

In this paper, a novel transmissive reconfigurable intelligent surface (RIS) enabled uplink communication system with orthogonal frequency division multiple access (OFDMA) is investigated. Specifically, a non-conventional receiver architecture equipped with a single receiving horn antenna and a transmissive RIS is first proposed, and a far-near field channel model based on planar waves and spherical waves is also given. Then, in order to maximize the system sum-rate of uplink communications, we formulate a joint optimization problem over subcarrier allocation, power allocation and RIS transmissive coefficient design while taking account of user quality-of-service (QoS) constraint. Due to the coupling of optimization variables, the optimization problem is non-convex, so it is challenging to solve it directly. In order to tackle this problem, the alternating optimization (AO) algorithm is utilized to decouple the optimization variables and divide the problem into two sub-problems to solve. First, the problem of joint subcarrier allocation and power allocation is solved via the Lagrangian dual decomposition method. Then, the RIS transmissive coefficient design scheme can be obtained by applying difference-of-convex (DC) programming, successive convex approximation (SCA) and penalty function methods. Finally, the two sub-problems are iterated alternately until convergence is achieved. Numerical results verify that the proposed algorithm has good convergence performance and can improve sum-rate of the proposed system compared with other benchmark algorithms.

cs.IT↗

arXiv2023

Quadrature Spatial Scattering Modulation for mmWave Transmission

In this letter, we investigate a novel quadrature spatial scattering modulation (QSSM) transmission technique based on millimeter wave (mmWave) systems, in which the transmitter generates two orthogonal beams targeting candidate scatterers in the channel to carry the real and imaginary parts of the conventional signal, respectively. Meanwhile, the maximum likelihood (ML) detector is adopted at the receiver to recover the received beams and signals. Based on the ML detector, we derive the closed-form average bit error probability (ABEP) expression of the QSSM scheme. Furthermore, we evaluate the asymptotic ABEP expression of the proposed scheme. Monte Carlo simulations verify the exactness and tightness of the derivation results. It is shown that the ABEP performance of QSSM is better than that of traditional spatial scattering modulation.

cs.IT↗

arXiv2022

Robust Sum-Rate Maximization in Transmissive RMS Transceiver-Enabled SWIPT Networks

In this paper, we propose a state-of-the-art downlink communication transceiver design for transmissive reconfigurable metasurface (RMS)-enabled simultaneous wireless information and power transfer (SWIPT) networks. Specifically, a feed antenna is deployed in the transmissive RMS-based transceiver, which can be used to implement beamforming. According to the relationship between wavelength and propagation distance, the spatial propagation models of plane and spherical waves are built. Then, in the case of imperfect channel state information (CSI), we formulate a robust system sum-rate maximization problem that jointly optimizes RMS transmissive coefficient, transmit power allocation, and power splitting ratio design while taking account of the non-linear energy harvesting model and outage probability criterion. Since the coupling of optimization variables, the whole optimization problem is non-convex and cannot be solved directly. Therefore, the alternating optimization (AO) framework is implemented to decompose the non-convex original problem. In detail, the whole problem is divided into three sub-problems to solve. For the non-convexity of the objective function, successive convex approximation (SCA) is used to transform it, and penalty function method and difference-of-convex (DC) programming are applied to deal with the non-convex constraints. Finally, we alternately solve the three sub-problems until the entire optimization problem converges. Numerical results show that our proposed algorithm has convergence and better performance than other benchmark algorithms.

eess.SP↗

arXiv2022

Joint Communication and Trajectory Design for Intelligent Reflecting Surface Empowered UAV SWIPT Networks

Aiming at the limited battery capacity of widely deployed low-power smart devices in the Internet-of-things (IoT), this paper proposes a novel intelligent reflecting surface (IRS) empowered unmanned aerial vehicle (UAV) simultaneous wireless information and power transfer (SWIPT) network framework, in which IRS is used to reconstruct the wireless channel to enhance the wireless energy transmission efficiency and coverage area of the UAV SWIPT networks. In this paper, we formulate an achievable sum-rate maximization problem by jointly optimizing UAV trajectory, successive interference cancellation (SIC) decoding order, UAV transmit power allocation, power splitting (PS) ratio and IRS reflection coefficient while taking account of user non-orthogonal multiple access (NOMA) and a non-linear energy harvesting model. Due to the coupling of optimization variables, this problem is a complex non-convex optimization problem, and it is challenging to solve it directly. We first transform the problem, and then apply the alternating optimization (AO) algorithm framework to divide the transformed problem into four sub-problems to solve it. Specifically, by applying successive convex approximation (SCA), penalty function method and difference-convex (DC) programming, UAV trajectory, SIC decoding order, UAV transmit power allocation, PS ratio and IRS reflection coefficient are alternately optimized until the convergence is achieved. Numerical simulation results verify the effectiveness of our proposed algorithm compared to other algorithms.

eess.SP↗