arXiv subjects

Zhiqing Wei

Publications and source records attributed to Zhiqing Wei.

At least 73 records · Page 4Linked to original sources

arXiv2023

Cooperation Based Joint Active and Passive Sensing with Asynchronous Transceivers for Perceptive Mobile Networks

Perceptive mobile network (PMN) is an emerging concept for next-generation wireless networks capable of conducting integrated sensing and communication (ISAC). A major challenge for realizing high performance sensing in PMNs is how to deal with spatially separated asynchronous transceivers. Asynchronicity results in timing offsets (TOs) and carrier frequency offsets (CFOs), which further cause ambiguity in ranging and velocity sensing. Most existing algorithms mitigate TOs and CFOs based on the line-of-sight (LOS) propagation path between sensing transceivers. However, LOS paths may not exist in realistic scenarios. In this paper, we propose a cooperation based joint active and passive sensing scheme for the non-LOS (NLOS) scenarios having asynchronous transceivers. This scheme relies on the cross-correlation cooperative sensing (CCCS) algorithm, which regards active sensing as a reference and mitigates TOs and CFOs by correlating active and passive sensing information. Another major challenge for realizing high performance sensing in PMNs is how to realize high accuracy angle-of-arrival (AoA) estimation with low complexity. Correspondingly, we propose a low complexity AoA algorithm based on cooperative sensing, which comprises coarse AoA estimation and fine AoA estimation. Analytical and numerical simulation results verify the performance advantages of the proposed CCCS algorithm and the low complexity AoA estimation algorithm.

cs.IT↗

arXiv2023

Spectrum Sharing Towards Delay Deterministic Wireless Network: Delay Performance Analysis

To accommodate Machine-type Communication (MTC) service, the wireless network needs to support low-delay and low-jitter data transmission, realizing delay deterministic wireless network. This paper analyzes the delay and jitter of the wireless network with and without spectrum sharing. When sharing the spectrum of the licensed network, the spectrum band of wireless network can be expanded, such that the delay and jitter of data transmission are reduced. The challenge of this research is to model the relation between the delay/jitter and the parameters such as node distribution, transmit power, and bandwidth, etc. To this end, this paper applies stochastic geometry and queueing theory to analyze the outage probability of the licensed network and the delay performance of the wireless network with and without spectrum sharing. By establishing the M/G/1 queueing model for the queueing of the Base Station (BS) in the wireless network, the downlink delay and jitter are derived. Monte Carlo simulation results show that the spectrum sharing reduces the delay and jitter without causing serious interference to the licensed network, which can lay a foundation for the application of spectrum sharing in delay deterministic wireless network supporting MTC service.

cs.PF↗

arXiv2023

Integrated Sensing and Communication enabled Sensing Base Station: System Design, Beamforming, Interference Cancellation and Performance Analysis

This paper studies the sensing base station (SBS) that has great potential to improve the safety of vehicles and pedestrians on roads. It can detect the targets on the road with communication signals using the integrated sensing and communication (ISAC) technique. Compared with vehicle-mounted radar, SBS has a better sensing field due to its higher deployment position, which can help solve the problem of sensing blind areas. In this paper, key technologies of SBS are studied, including the beamforming algorithm, beam scanning scheme, and interference cancellation algorithm. To transmit and receive ISAC signals simultaneously, a double-coupling antenna array is applied. The free detection beam and directional communication beam are proposed for joint communication and sensing to meet the requirements of beamwidth and pointing directions. The joint time-space-frequency domain division multiple access algorithm is proposed to cancel the interference of SBS, including multiuser interference and duplex interference between sensing and communication. Finally, the sensing and communication performance of SBS under the industrial scientific medical power limitation is analyzed and simulated. Simulation results show that the communication rate of SBS can reach over 100 Mbps and the range of sensing and communication can reach about 500 m.

math.NA↗

arXiv2023

Integrated Sensing and Communication enabled Doppler Frequency Shift Estimation and Compensation

Despite the millimeter wave technology fulfills the low-latency and high data transmission, it will cause severe Doppler Frequency Shift (DFS) for high-speed vehicular network, which tremendously damages the communication performance. In this paper, we propose an Integrated Sensing and Communication (ISAC) enabled DFS estimation and compensation algorithm. Firstly, the DFS is coarsely estimated and compensated using radar detection. Then, the designed preamble sequence is used to accurately estimate and compensate DFS. In addition, an adaptive DFS estimator is designed to reduce the computational complexity. Compared with the traditional DFS estimation algorithm, the improvement of the proposed algorithm is verified in bit error rate and mean square error performance by simulation results.

eess.SP↗

arXiv2023

Integrated Sensing and Communication Neighbor Discovery for MANET with Gossip Mechanism

Mobile Ad hoc Network (MANET), supporting Machine-Type Communication(MTC), has a strong demand for rapid networking. Neighbor Discovery (ND) is a key initial step in configuring MANETs and faces a serious challenge in decreasing convergence time. Integrated Sensing and Communication (ISAC), as one of the potential key technologies in the 6th Generation (6G) mobile networks, can obtain the sensing data as the priori information to accelerate ND convergence. In order to further reduce the convergence time of ND, this paper introduces the ISAC-enabled gossip mechanism into the ND algorithm. The prior information acquired by ISAC reduces the information redundancy brought by the gossip mechanism and thus decreases the probability of collision, which further improves convergence speed. The average number of discovered nodes within a given period is derived, which is applied as the critical metric to evaluate the performance of ND algorithms. The simulation results confirm the correctness of the theoretical derivation and show that the interplay between the prior mechanisms and the gossip mechanism significantly reduces the convergence time. In addition, to solve the problem of imperfect sensing information, reinforcement learning is applied. Under the constraints of the convergence condition, the non-Reply and non-Stop Algorithm based on Gossip and Q-learning (GQ-nRnS) proposed in this paper not only ensures the completeness of ND, but also maintains a high convergence speed of ND. Compared with the Q-learning-based ND algorithm (Q-ND), the average convergence time of the GQ-nRnS algorithm is reduced by about 66.4%.

eess.SY↗

arXiv2023

Fast Neighbor Discovery for Wireless Ad Hoc Network with Successive Interference Cancellation

Neighbor discovery (ND) is a key step in wireless ad hoc network, which directly affects the efficiency of wireless networking. Improving the speed of ND has always been the goal of ND algorithms. The classical ND algorithms lose packets due to the collision of multiple packets, which greatly affects the speed of the ND algorithms. Traditional methods detect packet collision and implement retransmission when encountering packet loss. However, they does not solve the packet collision problem and the performance improvement of ND algorithms is limited. In this paper, the successive interference cancellation (SIC) technology is introduced into the ND algorithms to unpack multiple collision packets by distinguishing multiple packets in the power domain. Besides, the multi-packet reception (MPR) is further applied to reduce the probability of packet collision by distinguishing multiple received packets, thus further improving the speed of ND algorithms. Six ND algorithms, namely completely random algorithm (CRA), CRA based on SIC (CRA-SIC), CRA based on SIC and MPR (CRA-SIC-MPR), scan-based algorithm (SBA), SBA based on SIC (SBA-SIC), and SBA based on SIC and MPR (SBA-SIC-MPR), are theoretically analyzed and verified by simulation. The simulation results show that SIC and MPR reduce the ND time of SBA by 69.02% and CRA by 66.03% averagely.

cs.NI↗

arXiv2023

Mutual Information Metrics for Uplink MIMO-OFDM Integrated Sensing and Communication System

As the uplink sensing has the advantage of easy implementation, it attracts great attention in integrated sensing and communication (ISAC) system. This paper presents an uplink ISAC system based on multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) technology. The mutual information (MI) is introduced as a unified metric to evaluate the performance of communication and sensing. In this paper, firstly, the upper and lower bounds of communication and sensing MI are derived in details based on the interaction between communication and sensing. And the ISAC waveform is optimized by maximizing the weighted sum of sensing and communication MI. The Monte Carlo simulation results show that, compared with other waveform optimization schemes, the proposed ISAC scheme has the best overall performance.

cs.IT↗

arXiv2023

Waveform Design for MIMO-OFDM Integrated Sensing and Communication System: An Information Theoretical Approach

Integrated sensing and communication (ISAC) is regarded as the enabling technology in the future 5th-Generation-Advanced (5G-A) and 6th-Generation (6G) mobile communication system. ISAC waveform design is critical in ISAC system. However, the difference of the performance metrics between sensing and communication brings challenges for the ISAC waveform design. This paper applies the unified performance metrics in information theory, namely mutual information (MI), to measure the communication and sensing performance in multicarrier ISAC system. In multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) ISAC system, we first derive the sensing and communication MI with subcarrier correlation and spatial correlation. Then, we propose optimal waveform designs for maximizing the sensing MI, communication MI and the weighted sum of sensing and communication MI, respectively. The optimization results are validated by Monte Carlo simulations. Our work provides effective closed-form expressions for waveform design, enabling the realization of MIMO-OFDM ISAC system with balanced performance in communication and sensing.

cs.IT↗

arXiv2023

Joint Data Collection and Sensor Positioning in Multi-UAV-Assisted Wireless Sensor Network

Due to the high mobility and easy deployment, unmanned aerial vehicles (UAVs) have attracted much attention in the field of wireless communication and positioning. To meet the challenges of lack of infrastructure coverage, uncertain sensor position and large amount of sensing data collection in wireless sensor network (WSN), this paper presents an efficient joint data collection and sensor positioning scheme for WSN supported by multiple UAVs. Specifically, a UAV is set as the main UAV to collect data, and other UAVs are used as auxiliary UAVs for sensor positioning using time difference of arrival (TDoA). A mixed-integer non-convex optimization problem with uncertain sensor position is established. The goal is to minimize the average positioning error of all sensors by jointly optimizing the UAV trajectories, sensor transmission schedule and positioning observation points (POPs). To solve this optimization model, the original problem is decomposed into two sub-problems based on the path discrete method. Firstly, the block coordinate descent (BCD) and successive convex approximation (SCA) techniques are applied to iteratively optimize the trajectory of the main UAV and the sensor transmission schedule, so as to maximize the minimum amount of data uploaded by the sensor. Then, based on the trajectory of the main UAV, a particle swarm optimization (PSO)-based algorithm is designed to optimize the POPs of UAVs. Finally, the spline curve is applied to generate the trajectories of auxiliary UAVs. The simulation results show that the proposed scheme can meet the requirements of data collection and has a good positioning performance.

eess.SY↗

arXiv2023

UD-MAC: Delay Tolerant Multiple Access Control Protocol for Unmanned Aerial Vehicle Networks

In unmanned aerial vehicle (UAV) networks, high-capacity data transmission is of utmost importance for applications such as intelligent transportation, smart cities, and forest monitoring, which rely on the mobility of UAVs to collect and transmit large amount of data, including video and image data. Due to the short flight time of UAVs, the network capacity will be reduced when they return to the ground unit for charging. Hence, we suggest that UAVs can apply a store-carry-and-forward (SCF) transmission mode to carry packets on their way back to the ground unit for improving network throughput. In this paper, we propose a novel protocol, named UAV delay-tolerant multiple access control (UD-MAC), which can support different transmission modes in UAV networks. We set a higher priority for SCF transmission and analyze the probability of being in SCF mode to derive network throughput. The simulation results show that the network throughput of UD-MAC is improved by 57% to 83% compared to VeMAC.

cs.NI↗

arXiv2023

Symbol-level Integrated Sensing and Communication enabled Multiple Base Stations Cooperative Sensing

With the support of integrated sensing and communication (ISAC) technology, mobile communication system will integrate the function of wireless sensing, thereby facilitating new intelligent applications such as smart city and intelligent transportation. Due to the limited sensing accuracy and sensing range of single base station (BS), multi-BS cooperative sensing can be applied to realize high-accurate, long-range and continuous sensing, exploiting the specific advantages of large-scale networked mobile communication system. This paper proposes a cooperative sensing method suitable to mobile communication systems, which applies symbol-level sensing information fusion to estimate the location and velocity of target. With the demodulation symbols obtained from the echo signals of multiple BSs, the phase features contained in the demodulation symbols are used in the fusion procedure, which realizes cooperative sensing with the synchronization level of mobile communication system. Compared with the signal-level fusion in the area of distributed aperture coherence-synthetic radars, the requirement of synchronization is much lower. When signal-to-noise ratio (SNR) is -5 dB, it is evaluated that symbol-level multi-BS cooperative sensing effectively improves the accuracy of distance and velocity estimation of target. Compared with single-BS sensing, the accuracy of distance and velocity estimation is improved by 40% and 72%, respectively. Compared with data-level multi-BS cooperative sensing based on maximum likelihood (ML) estimation, the accuracy of location and velocity estimation is improved by 12% and 63%, respectively. This work may provide a guideline for the design of multi-BS cooperative sensing system to exploit the widely deployed networked mobile communication system.

eess.SP↗

arXiv2023

ISAC-NET: Model-driven Deep Learning for Integrated Passive Sensing and Communication

Recent advances in wireless communication with the enormous demands of sensing ability have given rise to the integrated sensing and communication (ISAC) technology, among which passive sensing plays an important role. The main challenge of passive sensing is how to achieve high sensing performance in the condition of communication demodulation errors. In this paper, we propose an ISAC network (ISAC-NET) that combines passive sensing with communication signal detection by using model-driven deep learning (DL). Dissimilar to existing passive sensing algorithms that first demodulate the transmitted symbols and then obtain passive sensing results from the demodulated symbols, ISAC-NET obtains passive sensing results and communication demodulated symbols simultaneously. Different from the data-driven DL method, we adopt the block-by-block signal processing method that divides the ISAC-NET into the passive sensing module, signal detection module and channel reconstruction module. From the simulation results, ISAC-NET obtains better communication performance than the traditional signal demodulation algorithm, which is close to OAMP-Net2. Compared to the 2D-DFT algorithm, ISAC-NET demonstrates significantly enhanced sensing performance. In summary, ISAC-NET is a promising tool for passive sensing and communication in wireless communications.

cs.IT↗

arXiv2023

Coherent Compensation based ISAC Signal Processing for Long-range Sensing

Integrated sensing and communication (ISAC) will greatly enhance the efficiency of physical resource utilization. The design of ISAC signal based on the orthogonal frequency division multiplex (OFDM) signal is the mainstream. However, when detecting the long-range target, the delay of echo signal exceeds CP duration, which will result in inter-symbol interference (ISI) and inter-carrier interference (ICI), limiting the sensing range. Facing the above problem, we propose to increase useful signal power through coherent compensation and improve the signal to interference plus noise power ratio (SINR) of each OFDM block. Compared with the traditional 2D-FFT algorithm, the improvement of SINR of range-doppler map (RDM) is verified by simulation, which will expand the sensing range.

eess.SP↗

arXiv2023

Topology-Aware Resilient Routing Protocol for FANETs: An Adaptive Q-Learning Approach

Flying ad hoc networks (FANETs) play a crucial role in numerous military and civil applications since it shortens mission duration and enhances coverage significantly compared with a single unmanned aerial vehicle (UAV). Whereas, designing an energy-efficient FANET routing protocol with a high packet delivery rate (PDR) and low delay is challenging owing to the dynamic topology changes. In this article, we propose a topology-aware resilient routing strategy based on adaptive Q-learning (TARRAQ) to accurately capture topology changes with low overhead and make routing decisions in a distributed and autonomous way. First, we analyze the dynamic behavior of UAV nodes via the queuing theory, and then the closed-form solutions of neighbors' change rate (NCR) and neighbors' change interarrival time (NCIT) distribution are derived. Based on the real-time NCR and NCIT, a resilient sensing interval (SI) is determined by defining the expected sensing delay of network events. Besides, we also present an adaptive Q-learning approach that enables UAVs to make distributed, autonomous, and adaptive routing decisions, where the above SI ensures that the action space can be updated in time at a low cost. The simulation results verify the accuracy of the topology dynamic analysis model and also prove that our TARRAQ outperforms the Q-learning-based topology-aware routing (QTAR), mobility prediction-based virtual routing (MPVR), and greedy perimeter stateless routing based on energy-efficient hello (EE-Hello) in terms of 25.23%, 20.24%, and 13.73% lower overhead, 9.41%, 14.77%, and 16.70% higher PDR, and 5.12%, 15.65%, and 11.31% lower energy consumption, respectively.

cs.NI↗

arXiv2023

Toward Trusted and Swift UAV Communication: ISAC-Enabled Dual Identity Mapping

The UAV network has recently emerged as a capable carrier for ubiquitous wireless intelligent communication in the B5G/6G era. Nevertheless, the separation of dual identity raises challenges from the perspective of communication efficiency and security, including tedious communication feedback and malicious Sybil attacks. Meanwhile, thanks to the emerging integrated sensing and communication (ISAC) technology, the sensing ability incorporated in communication advances crucial opportunities for accurately and efficiently mapping identity from dual domains. This tutorial discusses the exciting intersection of ISAC and the future intelligent and efficient UAV network. We first describe the motivation scenario and present the framework of the proposed novel ISAC-enabled dual identity solution. The detailed modules of identity production, mapping, management, and authentication are discussed. By endowing UAVs with an advanced capability: opening their eyes when communicating with each other, we detail three typical applications and the advantages of our proposal. Finally, a series of key enabling techniques, open challenges, and potential solutions for ISAC-enabled dual-domain identity are discussed. This tutorial for the intelligent and efficient UAV network brings new insight on providing dual-domain identity via ISAC technology, with an eye on trusted and swift communication research tailored for the 6G UAV network.

eess.SP↗

arXiv2023

Seeing is Believing: Detecting Sybil Attack in FANET by Matching Visual and Auditory Domains

The flying ad hoc network (FANET) will play a crucial role in the B5G/6G era since it provides wide coverage and on-demand deployment services in a distributed manner. The detection of Sybil attacks is essential to ensure trusted communication in FANET. Nevertheless, the conventional methods only utilize the untrusted information that UAV nodes passively ``heard'' from the ``auditory" domain (AD), resulting in severe communication disruptions and even collision accidents. In this paper, we present a novel VA-matching solution that matches the neighbors observed from both the AD and the ``visual'' domain (VD), which is the first solution that enables UAVs to accurately correlate what they ``see'' from VD and ``hear'' from AD to detect the Sybil attacks. Relative entropy is utilized to describe the similarity of observed characteristics from dual domains. The dynamic weight algorithm is proposed to distinguish neighbors according to the characteristics' popularity. The matching model of neighbors observed from AD and VD is established and solved by the vampire bat optimizer. Experiment results show that the proposed VA-matching solution removes the unreliability of individual characteristics and single domains. It significantly outperforms the conventional RSSI-based method in detecting Sybil attacks. Furthermore, it has strong robustness and achieves high precision and recall rates.

cs.CR↗

arXiv2023

Dual Identities Enabled Low-Latency Visual Networking for UAV Emergency Communication

The Unmanned Aerial Vehicle (UAV) swarm networks will play a crucial role in the B5G/6G network thanks to its appealing features, such as wide coverage and on-demand deployment. Emergency communication (EC) is essential to promptly inform UAVs of potential danger to avoid accidents, whereas the conventional communication-only feedback-based methods, which separate the digital and physical identities (DPI), bring intolerable latency and disturb the unintended receivers. In this paper, we present a novel DPI-Mapping solution to match the identities (IDs) of UAVs from dual domains for visual networking, which is the first solution that enables UAVs to communicate promptly with what they see without the tedious exchange of beacons. The IDs are distinguished dynamically by defining feature similarity, and the asymmetric IDs from different domains are matched via the proposed bio-inspired matching algorithm. We also consider Kalman filtering to combine the IDs and predict the states for accurate mapping. Experiment results show that the DPI-Mapping reduces individual inaccuracy of features and significantly outperforms the conventional broadcast-based and feedback-based methods in EC latency. Furthermore, it also reduces the disturbing messages without sacrificing the hit rate.

cs.NI↗

arXiv2023

Throughput of Hybrid UAV Networks with Scale-Free Topology

Unmanned Aerial Vehicles (UAVs) hold great potential to support a wide range of applications due to the high maneuverability and flexibility. Compared with single UAV, UAV swarm carries out tasks efficiently in harsh environment, where the network resilience is of vital importance to UAV swarm. The network topology has a fundamental impact on the resilience of UAV network. It is discovered that scale-free network topology, as a topology that exists widely in nature, has the ability to enhance the network resilience. Besides, increasing network throughput can enhance the efficiency of information interaction, improving the network resilience. Facing these facts, this paper studies the throughput of UAV Network with scale-free topology. Introducing the hybrid network structure combining both ad hoc transmission mode and cellular transmission mode into UAV Network, the throughput of UAV Network is improved compared with that of pure ad hoc UAV network. Furthermore, this work also investigates the optimal setting of the hop threshold for the selection of ad hoc or cellular transmission mode. It is discovered that the optimal hop threshold is related with the number of UAVs and the parameters of scale-free topology. This paper may motivate the application of hybrid network structure into UAV Network.

cs.IT↗