arXiv subjects

Weixiao Meng

Publications and source records attributed to Weixiao Meng.

15 recordsLinked to original sources

arXiv2025

Multi-layer RIS on Edge: Communication, Computation and Wireless Power Transfer

The rapid expansion of Internet of Things (IoT) and its integration into various applications highlight the need for advanced communication, computation, and energy transfer techniques. However, the traditional hardware-based evolution of communication systems faces challenges due to excessive power consumption and prohibitive hardware cost. With the rapid advancement of reconfigurable intelligent surface (RIS), a new approach by parallel stacking a series of RIS, i.e., multi-layer RIS, has been proposed. Benefiting from the characteristics of scalability, passivity, low cost, and enhanced computation capability, multi-layer RIS is a promising technology for future massive IoT scenarios. Thus, this article proposes a multi-layer RIS-based universal paradigm at the network edge, enabling three functions, i.e., multiple-input multiple-output (MIMO) communication, computation, and wireless power transfer (WPT). Starting by picturing the possible applications of multi-layer RIS, we explore the potential signal transmission links, energy transmission links, and computation processes in IoT scenarios, showing its ability to handle on-edge IoT tasks and associated green challenges. Then, these three key functions are analyzed respectively in detail, showing the advantages of the proposed scheme, compared with the traditional hardware-based scheme. To facilitate the implementation of this new paradigm into reality, we list the dominant future research directions at last, such as inter-layer channel modeling, resource allocation and scheduling, channel estimation, and edge training. It is anticipated that multi-layer RIS will contribute to more energy-efficient wireless networks in the future by introducing a revolutionary paradigm shift to an all-wave-based approach.

cs.IT↗

arXiv2024

Service-Oriented AoI Modeling and Analysis for Non-Terrestrial Networks

To achieve truly seamless global intelligent connectivity, non-terrestrial networks (NTN) mainly composed of low earth orbit (LEO) satellites and drones are recognized as important components of the future 6G network architecture. Meanwhile, the rapid advancement of the Internet of Things (IoT) has led to the proliferation of numerous applications with stringent requirements for timely information delivery. The Age of Information (AoI), a critical performance metric for assessing the freshness of data in information update systems, has gained significant importance in this context. However, existing modeling and analysis work on AoI mainly focuses on terrestrial networks, and the distribution characteristics of ground nodes and the high dynamics of satellites have not been fully considered, which poses challenges for more accurate evaluation. Against this background, we model the ground nodes as a hybrid distribution of Poisson point process (PPP) and Poisson cluster process (PCP) to capture the impact of ground node distribution on the AoI of status update packet transmission supported by UAVs and satellites in NTN, and the visibility and cross-traffic characteristics of satellites are additionally considered. We derived the average AoI for the system in these two different situations and examined the impact of various network parameters on AoI performance.

cs.SI↗

arXiv2024

RIS-based Over-the-air Diffractional Channel Coding

Reconfigurable Intelligent Surfaces (RIS) are programmable metasurfaces utilizing sub-wavelength meta-atoms and a controller for precise electromagnetic wave manipulation. This work introduces an innovative channel coding scheme, termed RIS-based diffractional channel coding (DCC), which capitalizes on diffraction between two RIS layers for signal-level encoding. Contrary to traditional methods, DCC expands signal dimensions through diffraction, presenting a novel countermeasure to channel effects. This paper focuses on the operational principles of DCC, including encoder and decoder designs, and explores its possibilities to construct block and trellis codes, demonstrating its potential as both an alternative and a supplementary conventional coding scheme. Key advantages of DCC include eliminating extra power requirements for encoding, achieving computation at the speed of light, and enabling adjustable code distance, making it a progressive solution for efficient wireless communication, particularly in systems with large-scale data or massive MIMO.

eess.SP↗

arXiv2024

A Survey on Resource Management in Joint Communication and Computing-Embedded SAGIN

The advent of the 6G era aims for ubiquitous connectivity, with the integration of non-terrestrial networks (NTN) offering extensive coverage and enhanced capacity. As manufacturing advances and user demands evolve, space-air-ground integrated networks (SAGIN) with computational capabilities emerge as a viable solution for services requiring low latency and high computational power. Resource management within joint communication and computing-embedded SAGIN (JCC-SAGIN) presents greater complexity than traditional terrestrial networks. This complexity arises from the spatiotemporal dynamics of network topology and service demand, the interdependency of large-scale resource variables, and intricate tradeoffs among various performance metrics. Thus, a thorough examination of resource management strategies in JCC-SAGIN is crucial, emphasizing the role of non-terrestrial platforms with processing capabilities in 6G. This paper begins by reviewing the architecture, enabling technologies, and applications in JCC-SAGIN. Then, we offer a detailed overview of resource management modeling and optimization methods, encompassing both traditional optimization approaches and learning-based intelligent decision-making frameworks. Finally, we outline the prospective research directions in JCC-SAGIN.

cs.NI↗

arXiv2024

Enhancing LEO Mega-Constellations with Inter-Satellite Links: Vision and Challenges

Low Earth orbit (LEO) satellites have been envisioned as a significant component of the sixth generation (6G) network architecture for achieving ubiquitous coverage and seamless access. However, the implementation of LEO satellites is largely restricted by the deployment of ground stations. Inter-satellite links (ISLs) have been regarded as a promising technique to fully exploit the potentials of LEO mega constellations by concatenating multiple satellites to constitute an autonomous space network. In this article, we present the merits of implementing ISLs in LEO mega constellations and the representative applications empowered/inspired by ISLs. Moreover, we outline several key technical challenges as well as potential solutions related to LEO satellite networks with ISLs, including performance analysis for system design, routing and load balancing, and resource allocation. Particularly, the potential of using ISLs in enhancing in-flight connectivity is showcased with a preliminary performance evaluation. Finally, some open issues are discussed to inspire future research.

cs.IT↗

arXiv2024

Inter-Satellite Link-Enhanced Transmission Scheme Towards Aviation IoT in SAGIN

The rapid development of the aviation Internet of Things (IoT) has positioned in-flight connectivity (IFC) as one of its critical applications. Space-air-ground integrated networks (SAGIN) are essential for ensuring the performance of IFC by enabling seamless and reliable connectivity. However, most existing research treats satellites merely as transparent forwarding nodes and overlooks their potential caching capabilities to enhance IFC data rates. In this article, we explore an IFC-oriented SAGIN where satellites and ground stations (GSs) work together to transmit content to airborne passengers, thereby facilitating airborne communication. By categorizing files into cached (instantly accessible via satellites) and non-cached files (available only through GSs), this article pioneers the integration of multiple inter-satellite links (ISLs) into the IFC framework, thus innovating the content delivery process for both types of files. To minimize the average delay of content delivery, we formulate the corresponding optimization problems: 1) For cached files, we propose an exact penalty-based method to determine the satellite association scheme. 2) For non-cached files, we present an efficient algorithm based on alternating optimization to jointly optimize satellite association and GS bandwidth allocation. Our proposed framework is low in complexity, paving the way for high-speed Internet connectivity for aviation passengers. Finally, simulation results are provided to demonstrate the effectiveness of our proposed IFC framework for SAGIN.

cs.IT↗

arXiv2023

RIS-Based On-the-Air Semantic Communications -- a Diffractional Deep Neural Network Approach

Semantic communication has gained significant attention recently due to its advantages in achieving higher transmission efficiency by focusing on semantic information instead of bit-level information. However, current AI-based semantic communication methods require digital hardware for implementation. With the rapid advancement on reconfigurable intelligence surfaces (RISs), a new approach called on-the-air diffractional deep neural networks (D$^2$NN) can be utilized to enable semantic communications on the wave domain. This paper proposes a new paradigm of RIS-based on-the-air semantic communications, where the computational process occurs inherently as wireless signals pass through RISs. We present the system model and discuss the data and control flows of this scheme, followed by a performance analysis using image transmission as an example. In comparison to traditional hardware-based approaches, RIS-based semantic communications offer appealing features, such as light-speed computation, low computational power requirements, and the ability to handle multiple tasks simultaneously.

eess.SP↗

arXiv2022

Physical Layer Security Assisted Computation Offloading in Intelligently Connected Vehicle Networks

In this paper, we propose a secure computation offloading scheme (SCOS) in intelligently connected vehicle (ICV) networks, aiming to minimize overall latency of computing via offloading part of computational tasks to nearby servers in small cell base stations (SBSs), while securing the information delivered during offloading and feedback phases via physical layer security. Existing computation offloading schemes usually neglected time-varying characteristics of channels and their corresponding secrecy rates, resulting in an inappropriate task partition ratio and a large secrecy outage probability. To address these issues, we utilize an ergodic secrecy rate to determine how many tasks are offloaded to the edge, where ergodic secrecy rate represents the average secrecy rate over all realizations in a time-varying wireless channel. Adaptive wiretap code rates are proposed with a secrecy outage constraint to match time-varying wireless channels. In addition, the proposed secure beamforming and artificial noise (AN) schemes can improve the ergodic secrecy rates of uplink and downlink channels even without eavesdropper channel state information (CSI). Numerical results demonstrate that the proposed schemes have a shorter system delay than the strategies neglecting time-varying characteristics.

eess.SP↗

arXiv2022

Video-based Facial Micro-Expression Analysis: A Survey of Datasets, Features and Algorithms

Unlike the conventional facial expressions, micro-expressions are involuntary and transient facial expressions capable of revealing the genuine emotions that people attempt to hide. Therefore, they can provide important information in a broad range of applications such as lie detection, criminal detection, etc. Since micro-expressions are transient and of low intensity, however, their detection and recognition is difficult and relies heavily on expert experiences. Due to its intrinsic particularity and complexity, video-based micro-expression analysis is attractive but challenging, and has recently become an active area of research. Although there have been numerous developments in this area, thus far there has been no comprehensive survey that provides researchers with a systematic overview of these developments with a unified evaluation. Accordingly, in this survey paper, we first highlight the key differences between macro- and micro-expressions, then use these differences to guide our research survey of video-based micro-expression analysis in a cascaded structure, encompassing the neuropsychological basis, datasets, features, spotting algorithms, recognition algorithms, applications and evaluation of state-of-the-art approaches. For each aspect, the basic techniques, advanced developments and major challenges are addressed and discussed. Furthermore, after considering the limitations of existing micro-expression datasets, we present and release a new dataset - called micro-and-macro expression warehouse (MMEW) - containing more video samples and more labeled emotion types. We then perform a unified comparison of representative methods on CAS(ME)2 for spotting, and on MMEW and SAMM for recognition, respectively. Finally, some potential future research directions are explored and outlined.

cs.CV↗

arXiv2019

Channel-Correlation-Enabled Transmit Optimization for MISO Wiretap Channels

An artificial-noise (AN)-aided beamformer specific to correlated main and wiretap channels is designed in this paper. We consider slow-fading multiple-input-single-output (MISO) wiretap channels with a passive single-antenna eavesdropper, in which independent transmitter-side and correlated receiver-side are assumed. Additionally, the source has accurate main channel information and statistical wiretap channel information. To reduce the secrecy loss due to receiver-side correlation, this paper proposes the scheme of channel-correlation-enabled transmit optimization. Particularly, the correlation is viewed as a resource to acquire more knowledge about wiretap channel. Based on this, the statistical distribution of wiretap channel is described more precisely. Then, the power of AN in the null space of main channel is placed more reasonably instead of simple uniform distribution and an elaborate beamformer for the information-bearing signal is designed. Finally, an efficient algorithm for power allocation between the information-bearing signal and the AN is developed. Simulation results show that the secrecy rate under transmit power and secrecy outage constraint is improved.

cs.IT↗

arXiv2019

Artificial Noisy MIMO Systems under Correlated Scattering Rayleigh Fading -- A Physical Layer Security Approach

The existing investigations on artificial noise (AN) security systems assumed that only null spaces is used to send AN signals, and all eigen-subchannels should be used to transmit messages. Our previous work proposed an AN scheme that allocates some of eigen-subchannels to transmit AN signals for improving secrecy rates. Nevertheless, our previous work considered only uncorrelated MIMO Rayleigh fading channels. In fact, the correlations among antennas exist in realistic scattering channel environments. In this paper, we extend our previous AN scheme to spatially correlated Rayleigh fading channels at both legitimate receiver- and eavesdropper-sides and derive an exact theoretical expression for the ergodic secrecy rate of the AN scheme, along with an approximate analysis. Both numerical and simulation results show that the proposed AN scheme offers a higher ergodic secrecy rate than the existing schemes, revealing a fact that the correlation among eavesdropper's antennas can potentially improve the secrecy rate of an MIMO system.

cs.IT↗

arXiv2019

Performance Analysis of Joint Transmission Schemes in Ultra-Dense Networks - An Unified Approach

Ultra-dense network (UDN) is one of the enabling technologies to achieve 1000-fold capacity increase in 5G communication systems, and the application of joint transmission (JT) is an effective method to deal with severe inter-cell interferences in UDNs. However, most works done for performance analysis on JT schemes in the literature were based largely on simulation results due to the difficulties in quantitatively identifying the numbers of desired and interfering transmitters. In this work, we are motivated to propose an analytical approach to investigate the performance of JT schemes with a unified approach based on stochastic geometry, which is in particular useful for studying different JT methods and conventional transmission schemes without JT. Using the proposed approach, we can unveil the statistic characteristics (i.e., expectation, moment generation function, variance) of desired signal and interference powers of a given user equipment (UE), and thus system performances, such as average signal-to-interference-plus-noise ratio (SINR), and area spectral efficiency, can be evaluated analytically. The simulation results are used to verify the effectiveness of the proposed unified approach.

eess.SP↗

arXiv2018

Physical Layer Security Enhancement for Satellite Communication among Similar Channels: Relay Selection and Power Allocation

Channels of satellite communication are usually modeled as Rician fading channels with very large Rician factor or Gaussian channels. Therefore, when a legitimate user is close to an eavesdropping user, the legitimate channel is approximately the same as the eavesdropping channel. The physical layer security technology of traditional terrestrial wireless communication mainly takes advantage of the difference be-tween the legitimate channel and the eaves-dropping channel; thus, it is not suitable for satellite communication. To implement secure communication in similar channels for satellite communications, a secure communication mod-el based on collaboration of the interference relay of the satellite physical layer is proposed. Relay selection and power allocation are further studied to enhance the security performance of the satellite communication system based on the model. The relay selection standard under known instantaneous channel state information (CSI) and statistical CSI conditions is theoreti-cally derived, thereby accomplishing minimiza-tion of the probability of secrecy relay. In addi-tion, the power allocation factor is optimized based on minimization of the secrecy outage probability. Moreover, a power allocation method based on the statistical CSI is present-ed. The secrecy outage probability performance of each relay selection criterion and power al-location scheme are analyzed via a simulation.

cs.IT↗

arXiv2018

Resource Allocation Based on Deep Neural Networks for Cognitive Radio Networks

Resource allocation is of great importance in the next generation wireless communication systems, especially for cognitive radio networks (CRNs). Many resource allocation strategies have been proposed to optimize the performance of CRNs. However, it is challenging to implement these strategies and achieve real-time performance in wireless systems since most of them need accurate and timely channel state information and/or other network statistics. In this paper a resource allocation strategy based on deep neural networks (DNN) is proposed and the training method is presented to train the neural networks. Simulation results show that our proposed strategy based on DNN is efficient in terms of the computation time compared with the conventional resource allocation schemes.

cs.IT↗

arXiv2017

Improving Secrecy with Nearly Collinear Main and Wiretap Channels via a Cooperative Jamming Relay

In physical layer security (PHY-security), the frequently observed high correlation between the main and wiretap channels can cause a significant loss of secrecy. This paper investigates a slow fading scenario, where a transmitter (Alice) sends a confidential message to a legitimate receiver (Bob) while a passive eavesdropper (Eve) attempts to decode the message from its received signal. It is assumed that Alice is equipped with multiple antennas while Bob and Eve each have a single antenna (i.e., a MISOSE system). In a MISOSE system, high correlation results in nearly collinear main and wiretap channel vectors, which help Eve to see and intercept confidential information. Unfortunately, the signal processing techniques at Alice, such as beamforming and artificial noise (AN), are helpless, especially in the extreme case of completely collinear main and wiretap channel vectors. On this background, we first investigate the achievable secrecy outage probability via beamforming and AN at Alice with the optimal power allocation between the information-bearing signal and AN. Then, an ingenious model, in which a cooperative jamming relay (Relay) is introduced, is proposed to effectively mitigate the adverse effects of high correlation. Based on the proposed model, the power allocation between the information-bearing signal at Alice and the AN at Relay is also studied to maximize secrecy. Finally, to validate our proposed schemes, numerical simulations are conducted, and the results show that a significant performance gain with respect to secrecy is achieved.

cs.IT↗