Cell-free systems significantly improve network capacity by enabling joint user service without cell boundaries, eliminating inter-cell interference. However, to satisfy further capacity demands, it leads to high-cost problems of both hardware and power consumption. In this paper, we investigate multiple reconfigurable intelligent surfaces (RISs) aided cell-free systems where RISs are introduced to improve spectrum efficiency in an energy-efficient way. To overcome the centralized high complexity and avoid frequent information exchanges, a cooperative distributed beamforming design is proposed to maximize the weighted sum-rate performance. In particular, the alternating optimization method is utilized with the distributed closed-form solution of active beamforming being derived locally at access points, and phase shifts are obtained centrally based on the Riemannian conjugate gradient (RCG) manifold method. Simulation results verify the effectiveness of the proposed design whose performance is comparable to the centralized scheme and show great superiority of the RISs-aided system over the conventional cellular and cell-free system.

Femtosecond laser direct inscription is a technique especially useful for prototyping purposes due to its distinctive advantages such as high fabrication accuracy, true 3D processing flexibility, and no need for mold or photomask. In this paper, we demonstrate the design and fabrication of a planar lightwave circuit (PLC) power splitter encoded with waveguide Bragg gratings (WBG) using a femtosecond laser inscription technique for passive optical network (PON) fault localization application. Both the reflected wavelengths and intervals of WBGs can be conveniently tuned. In the experiment, we succeeded in directly inscribing WBGs in 1×4 PLC splitter chips with a wavelength interval of about 4 nm and an adjustable reflectivity of up to 70% in the C-band. The proposed method is suitable for the prototyping of a PLC splitter encoded with WBG for PON fault localization applications.

This paper proposes an adaptive hybrid forward error correction (AH-FEC) coding scheme for coping with dynamic packet loss events in video and audio transmission. Specifically, the proposed scheme consists of a hybrid Reed-Solomon and low-density parity-check (RS-LDPC) coding system, combined with a Kalman filter-based adaptive algorithm. The hybrid RS-LDPC coding accommodates a wide range of code length requirements, employing RS coding for short codes and LDPC coding for medium-long codes. We delimit the short and medium-length codes by coding performance so that both codes remain in the optimal region. Additionally, a Kalman filter-based adaptive algorithm has been developed to handle dynamic alterations in a packet loss rate. The Kalman filter estimates packet loss rate utilizing observation data and system models, and then we establish the redundancy decision module through receiver feedback. As a result, the lost packets can be perfectly recovered by the receiver based on the redundant packets. Experimental results show that the proposed method enhances the decoding performance significantly under the same redundancy and channel packet loss.

A distributed acoustic sensing (DAS) system is proposed and a data processing method for vibration is designed in this paper. The proposed DAS system is based on the Rayleigh scattering signal and utilizes phase-sensitive optical time-domain reflectometry ( ? -OTDR) to demodulate the environmental vibration. It can collect the vibration information in railways and implement vibration classification based on the feature of sensed vibration signals. This system has been deployed in Guangzhou Shenzhen High-Speed Railway, and the experimental results validate its effectiveness.

Deadlock detection is an essential aspect of concurrency control in parallel and distributed systems, as it ensures the efficient utilization of resources and prevents indefinite delays. This paper presents a comprehensive analysis of the various deadlock detection techniques, including static and dynamic approaches. We discuss the future improvements associated with deadlock detection and provide a comparative evaluation of these techniques in terms of their accuracy, complexity, and scalability. Furthermore, we outline potential future research directions to improve deadlock detection mechanisms and enhance system performance.

In recent years, various internet architectures, such as Integrated Services (IntServ), Differentiated Services (DiffServ), Time Sensitive Networking (TSN) and Deterministic Networking (DetNet), have been proposed to meet the quality-of-service (QoS) requirements of different network services. Concurrently, network calculus has found widespread application in network modeling and QoS analysis. Network calculus abstracts the details of how nodes or networks process data packets using the concept of service curves. This paper summarizes the service curves for typical scheduling algorithms, including Strict Priority (SP), Round Robin (RR), Cycling Queuing and Forwarding (CQF), Time Aware Shaper (TAS), Credit Based Shaper (CBS), and Asynchronous Traffic Shaper (ATS). It introduces the theory of network calculus and then provides an overview of various scheduling algorithms and their associated service curves. The delay bound analysis for different scheduling algorithms in specific scenarios is also conducted for more insights.

The query processing in distributed database management systems (DBMS) faces more challenges, such as more operators, and more factors in cost models and meta-data, than that in a single-node DMBS, in which query optimization is already an NP-hard problem. Learned query optimizers (mainly in the single-node DBMS) receive attention due to its capability to capture data distributions and flexible ways to avoid hard-craft rules in refinement and adaptation to new hardware. In this paper, we focus on extensions of learned query optimizers to distributed DBMSs. Specifically, we propose one possible but general architecture of the learned query optimizer in the distributed context and highlight differences from the learned optimizer in the single-node ones. In addition, we discuss the challenges and possible solutions.

In the context of edge computing environments in general and the metaverse in particular, federated learning (FL) has emerged as a distributed machine learning paradigm that allows multiple users to collaborate on training a shared machine learning model locally, eliminating the need for uploading raw data to a central server. It is perhaps the only training paradigm that preserves the privacy of user data, which is essential for computing environments as personal as the metaverse. However, the original FL architecture proposed is not scalable to a large number of user devices in the metaverse community. To mitigate this problem, hierarchical federated learning (HFL) has been introduced as a general distributed learning paradigm, inspiring a number of research works. In this paper, we present several types of HFL architectures, with a special focus on the three-layer client-edge-cloud HFL architecture, which is most pertinent to the metaverse due to its delay-sensitive nature. We also examine works that take advantage of the natural layered organization of three-layer client-edge-cloud HFL to tackle some of the most challenging problems in FL within the metaverse. Finally, we outline some future research directions of HFL in the metaverse.

Traditional methods of identity authentication often rely on centralized architectures, which poses risks of computational overload and single points of failure. We propose a protocol that offers a decentralized approach by distributing authentication services to edge authentication gateways and servers, facilitated by blockchain technology, thus aligning with the decentralized ethos of Web3 infrastructure. Additionally, we enhance device security against physical and cloning attacks by integrating physical unclonable functions with certificateless cryptography, bolstering the integrity of Internet of Thins (IoT) devices within the evolving landscape of the metaverse. To achieve dynamic anonymity and ensure privacy within Web3 environments, we employ fuzzy extractor technology, allowing for updates to pseudonymous identity identifiers while maintaining key consistency. The proposed protocol ensures continuous and secure identity authentication for IoT devices in practical applications, effectively addressing the pressing security concerns inherent in IoT network environments and contributing to the development of robust security infrastructure essential for the proliferation of IoT devices across diverse settings.

With the maturation and advancement of blockchain technology, a novel execute-order-validate (EOV) architecture has been proposed, allowing transactions to be executed in parallel during the execution phase. However, parallel execution may lead to multi-version concurrency control (MVCC) conflicts during the validation phase, resulting in transaction invalidation. Based on different causes, we categorize conflicts in the EOV blockchain into two types: within-block conflicts and cross-block conflicts, and propose an optimization solution called FabricMan based on Fabric v2.4. For within-block conflicts, a reordering algorithm is designed to improve the transaction success rate and parallel validation is implemented based on the transaction conflict graph. We also merge transfer transactions to prevent triggering multiple version checks. For cross-block conflicts, a cache-based version validation mechanism is implemented to detect and terminate invalid transactions in advance. Experimental comparisons are conducted between FabricMan and two other systems, Fabric and Fabric++. The results show that FabricMan outperforms the other two systems in terms of throughput, transaction abort rate, algorithm execution time, and other experimental metrics.

Recent rapid advancements in communication technology have brought forth the era of Web 3.0, representing a substantial transformation in the Internet landscape. This shift has led to the emergence of various decentralized metaverse applications that leverage blockchain as their underlying technology to enable users to exchange value directly from point to point. However, blockchains are blind to the real world, and smart contracts cannot directly access data from the external world. To address this limitation, the technology of oracles has been introduced to provide real-world data for smart contracts and other blockchain applications. In this paper, we focus on mitigating the risks associated with oracles providing corrupt or incorrect data. We propose a novel Web 3.0 architecture for the Metaverse based on the multi-identifier network (MIN), and its decentralized blockchain oracle model called MetaOracle. The experimental results show that the proposed scheme can achieve minor time investment in return for significantly more reliable data and increased throughput.

The emergence of Web3 technologies promises to revolutionize the Internet and redefine our interactions with digital assets and applications. This essay explores the pivotal role of 5G infrastructure in bolstering the growth and potential of Web3. By focusing on several crucial aspects—network speed, edge computing, network capacity, security and power consumption—we shed light on how 5G technology offers a robust and transformative foundation for the decentralized future of the Internet. Prior to delving into the specifics, we undertake a technical review of the historical progression and development of Internet and telecommunication technologies.

Weakly-coupled mode division multiplexing (MDM) technique is considered a promising candidate to enhance the capacity of an optical transmission system, in which mode multiplexers/demultiplexers (MMUX/MDEMUX) with low insertion loss and modal crosstalk are the key components. In this paper, a low-modal-crosstalk 4-mode MMUX/MDEMUX for the weakly-coupled triple-ring-core few-mode fiber (TRC-FMF) is designed and fabricated with side-polishing processing. The measurement results show that a pair of MMUX/MDEMUX and 25 km weakly-coupled TRC-FMF MDM link achieve low modal crosstalk of lower than -17.5 dB and insertion loss of lower than 11.56 dB for all the four modes. Based on the TRC-FMF and all-fiber MMUX/MDEMUX, an experiment for 25 km real-time 4-mode 3-λ wavelength division multiplexing (WDM)-MDM transmission is conducted using commercial 400G optical transport network (OTN) transceivers. The experimental results prove weakly-coupled MDM techniques facilitate a smooth upgrade of the optical transmission system.

The design of electromagnetic interference (EMI) filters needs to fulfill the EMI standards. Designing a filter is a time-consuming process for new engineers as well as for those experienced engineers. This paper measures and compares the noise spectrum of the wireless base station power prototype with and without the original filter. The ideal insertion loss (IL) of the original filter is obtained by combining calculation and simulation. It is pointed out that the effect of the original filter is not good. Based on the improved insertion-loss method, the source impedance model of the prototype is established by combining measurement and theory. A procedure for designing EMI filters for switch power supply will be presented. The filter design procedure makes it possible to design filters quickly and easily. Finally, the proposed filter design method is proved to be effective by the EMI measurement of the wireless base station power supply prototype.

Real-time system timing analysis is crucial for estimating the worst-case execution time (WCET) of a program. To achieve this, static or dynamic analysis methods are used, along with targeted modeling of the actual hardware system. This literature review focuses on calculating WCET for multi-core processors, providing a survey of traditional methods used for static and dynamic analysis and highlighting the major challenges that arise from different program execution scenarios on multi-core platforms. This paper outlines the strengths and weaknesses of current methodologies and offers insights into prospective areas of research on multi-core analysis. By presenting a comprehensive analysis of the current state of research on multi-core processor analysis for WCET estimation, this review aims to serve as a valuable resource for researchers and practitioners in the field.

Cell-free (CF) multiple-input multiple-output (MIMO) is a promising technique to enable the vision of ubiquitous wireless connectivity for next-generation network communications. Compared to traditional co-located massive MIMO, CF MIMO allows geographically distributed access points (APs) to serve all users on the same time-frequency resource with spatial multiplexing techniques, resulting in better performance in terms of both spectral efficiency and coverage enhancement. However, the performance gain is achieved at the expense of deploying more APs with high cost and power consumption. To address this issue, the recently proposed reconfigurable intelligent surface (RIS) technique stands out with its unique advantages of low cost, low energy consumption and programmability. In this paper, we provide an overview of RIS-assisted CF MIMO and its interaction with advanced optimization designs and novel applications. Particularly, recent studies on typical performance metrics such as energy efficiency (EE) and spectral efficiency (SE) are surveyed. Besides, the application of RIS-assisted CF MIMO techniques in various future communication systems is also envisioned. Additionally, we briefly discuss the technical challenges and open problems for this area to inspire research direction and fully exploit its potential in meeting the demands of future wireless communication systems.

To improve the performance of video compression for machine vision analysis tasks, a video coding for machines (VCM) standard working group was established to promote standardization procedures. In this paper, recent advances in video coding for machine standards are presented and comprehensive introductions to the use cases, requirements, evaluation frameworks and corresponding metrics of the VCM standard are given. Then the existing methods are presented, introducing the existing proposals by category and the research progress of the latest VCM conference. Finally, we give conclusions.

The Bessel beam, characterized by its unique non-diffracting properties, holds promising applications. In this paper, we provide a detailed introduction and investigation into the theory and research of the Bessel beam, with a special focus on its generation and applications in the near-field region. We provide an introduction to the concepts, properties, and foundational theories of the Bessel beam. Additionally, the current study on generating Bessel beams and their applications is categorized and discussed, and potential research challenges are proposed in this paper. This review serves as a solid foundation for researchers to understand the concept of the Bessel beam and explore its potential applications.

Holographic multiple-input multiple-output (HMIMO) has become an emerging technology for achieving ultra-high frequency spectral efficiency and spatial resolution in future wireless systems. The increasing antenna aperture leads to a more significant characterization of the spherical wavefront in near-field communications in HMIMO scenarios. Beam training as a key technique for wireless communication is worth exploring in this near-field scenario. Compared with the widely researched far-field beam training, the increased dimensionality of the search space for near-field beam training poses a challenge to the complexity and accuracy of the proposed algorithm. In this paper, we introduce several typical near-field beam training methods: exhaustive beam training, hierarchical beam training, and multi-beam training that includes equal interval multi-beam training and hash multi-beam training. The performances of these methods are compared through simulation analysis, and their effectiveness is verified on the hardware testbed as well. Additionally, we provide application scenarios, research challenges, and potential future research directions for near-field beam training.

Degree of freedom (DOF) is a key indicator for spatial multiplexing layers of a wireless channel. Traditionally, the channel of a multiple-input multiple-output (MIMO) half-wavelength dipole array has a DOF that equals the antenna number. However, recent studies suggest that the DOF could be less than the antenna number when strong mutual coupling is considered. We utilize a mutual-coupling-compliant channel model to investigate the DOF of the holographic MIMO (HMIMO) channel and give a upper bound of the DOF with strong mutual coupling. Our numerical simulations demonstrate that a dense array can support more DOF per unit aperture as compared with a half-wavelength MIMO system.

Extremely large-scale hybrid reconfigurable intelligence surface (XL-HRIS), an improved version of the RIS, can receive the incident signal and enhance communication performance. However, as the RIS size increases, the phase variations of the received signal across the whole array are nonnegligible in the near-field region, and the channel model mismatch, which will decrease the estimation accuracy, must be considered. In this paper, the lower bound (LB) of the estimated parameter is studied and the impacts of the distance and signal-to-noise ratio (SNR) on LB are then evaluated. Moreover, the impacts of the array scale on LB and spectral efficiency (SE) are also studied. Simulation results verify that even in extremely large-scale array systems with infinite SNR, channel model mismatch can still limit estimation accuracy. However, this impact decreases with increasing distance.

Backscatter communications will play an important role in connecting everything for beyond 5G (B5G) and 6G systems. One open challenge for backscatter communications is that the signals suffer a round-trip path loss so that the communication distance is short. In this paper, we first calculate the communication distance upper bounds for both uplink and downlink by measuring the tag sensitivity and reflection coefficient. It is found that the activation voltage of the envelope detection diode of the downlink tag is the main factor limiting the backscatter communication distance. Based on this analysis, we then propose to implement a low-noise amplifier (LNA) module before the envelope detection at the tag to enhance the incident signal strength. Our experimental results on the hardware platform show that our method can increase the downlink communication range by nearly 20 m.

Extremely large-scale multiple-input multiple-output (XL-MIMO) and terahertz (THz) communications are pivotal candidate technologies for supporting the development of 6G mobile networks. However, these techniques invalidate the common assumptions of far-field plane waves and introduce many new properties. To accurately understand the performance of these new techniques, spherical wave modeling of near-field communications needs to be applied for future research. Hence, the investigation of near-field communication holds significant importance for the advancement of 6G, which brings many new and open research challenges in contrast to conventional far-field communication. In this paper, we first formulate a general model of the near-field channel and discuss the influence of spatial nonstationary properties on the near-field channel modeling. Subsequently, we discuss the challenges encountered in the near field in terms of beam training, localization, and transmission scheme design, respectively. Finally, we point out some promising research directions for near-field communications.

With the rapid development of immersive multimedia technologies, 360-degree video services have quickly gained popularity and how to ensure sufficient spatial presence of end users when viewing 360-degree videos becomes a new challenge. In this regard, accurately acquiring users’ sense of spatial presence is of fundamental importance for video service providers to improve their service quality. Unfortunately, there is no efficient evaluation model so far for measuring the sense of spatial presence for 360-degree videos. In this paper, we first design an assessment framework to clarify the influencing factors of spatial presence. Related parameters of 360-degree videos and head-mounted display devices are both considered in this framework. Well-designed subjective experiments are then conducted to investigate the impact of various influencing factors on the sense of presence. Based on the subjective ratings, we propose a spatial presence assessment model that can be easily deployed in 360-degree video applications. To the best of our knowledge, this is the first attempt in literature to establish a quantitative spatial presence assessment model by using technical parameters that are easily extracted. Experimental results demonstrate that the proposed model can reliably predict the sense of spatial presence.

This paper proposes a design and fine-tuning method for mixed electric and magnetic coupling filters. It derives the quantitative relationship between the coupling coefficients (electric and magnetic coupling, i.e., E_C and M_C) and the linear coefficients of frequency-dependent coupling for the first time. Different from the parameter extraction technique using the bandpass circuit model, the proposed approach explicitly relatesE_C and M_C to the coupling matrix model. This paper provides a general theoretic framework for computer-aided design and tuning of a mixed electric and magnetic coupling filter based on coupling matrices. An example of a 7th-order coaxial combline filter design is given in the paper, verifying the practical value of the approach.