Search Results (98)

Wireless hierarchical federated learning (WHFL) is an implementation of wireless federated Learning (WFL) on a cloud–edge–client hierarchical architecture that accelerates model training and achieves more favorable trade-offs between communication and computation. However, due to the broadcast nature of wireless communication, the WHFL is susceptible to eavesdropping during the training process. Apart from this, recently ultra-reliable and low-latency communication (URLLC) has received much attention since it serves as a critical communication service in current 5G and upcoming 6G, and this motivates us to study the URLLC-WHFL in the presence of physical layer security (PLS) issue. In this paper, we propose a secure finite block-length (FBL) approach for the multi-antenna URLLC-WHFL, and characterize the relationship between privacy, utility, and PLS of the proposed scheme. Simulation results show that when the eavesdropper’s CSI is perfectly known by the edge server, our proposed FBL approach not only almost achieves perfect secrecy but also does not affect learning performance, and further shows the robustness of our schemes against imperfect CSI of the eavesdropper’s channel. This paper provides a new method for the URLLC-WHFL in the presence of PLS. Full article

Over the past few years, life expectancy has increased significantly. However, elderly individuals living independently often require assistance due to mobility issues, symptoms of dementia, or other health-related challenges. In these situations, high-quality elderly care systems for the aging population require innovative approaches to guarantee Quality of Service (QoS) and Quality of Experience (QoE). Traditional remote elderly care methods face several challenges, including high latency and poor service quality, which affect their transparency and stability. This paper proposes an Edge Computational Intelligence (ECI)-based haptic-driven ECI-TeleCaring system for the remote caring and monitoring of elderly people. It utilizes a Software-Defined Network (SDN) and Mobile Edge Computing (MEC) to reduce latency and enhance responsiveness. Dual Long Short-Term Memory (LSTM) models are deployed at the edge to enable real-time location-aware activity prediction to ensure QoS and QoE. The results from the simulation demonstrate that the proposed system is proficient in managing the transmission of data in real time without and with an activity recognition and location-aware model by communication latency under 2.5 ms (more than 60%) and from 11∼12 ms (60∼95%) for 10 to 1000 data packets, respectively. The results also show that the proposed system ensures a trade-off between the transparency and stability of the system from the QoS and QoE perspectives. Moreover, the proposed system serves as a testbed for implementing, investigating, and managing elder telecaring services for QoS/QoE provisioning. It facilitates real-time monitoring of the deployed technological parameters along with network delay and packet loss, and it oversees data exchange between the master domain (human operator) and slave domain (telerobot). Full article

Software-defined networking (SDN) is an emerging networking technology with a central point, called the controller, on the control plane. This controller communicates with the application and data planes. In fifth-generation (5G) mobile wireless networks and beyond, specific levels of service quality are defined for different traffic types. Ultra-reliable low-latency communication (URLLC) is one of the key services in 5G. This paper presents a fuzzy logic (FL)-based dynamic routing (FLDR) mechanism with congestion avoidance for URLLC on SDN-based 5G networks. By periodically monitoring the network status and making forwarding decisions on the basis of fuzzy inference rules, the FLDR mechanism not only can reroute in real time, but also can cope with network status uncertainty owing to FL’s fault tolerance capabilities. Three input parameters, normalized throughput, packet delay, and link utilization, were employed as crisp inputs to the FL control system because they had a more accurate correlation with the network performance measures we studied. The crisp output of the FL control system, i.e., path weight, and a predefined threshold of packet loss ratio on a path were applied to make routing decisions. We evaluated the performance of the proposed FLDR mechanism on the Mininet simulator by installing three additional modules, topology discovery, monitoring, and rerouting with FL, on the traditional control plane of SDN. The superiority of the proposed FLDR over the other existing FL-based routing schemes was demonstrated using three performance measures, system throughput, packet loss rate, and packet delay versus traffic load in the system. Full article

Ensuring high reliability and low latency poses challenges for numerous applications that require rigid performance guarantees, such as industrial automation and autonomous vehicles. Our research primarily concentrates on addressing the real-time requirements of ultra-reliable low-latency communication (URLLC). Specifically, we tackle the challenge of hard delay constraints in real-time transmission systems, overcoming this obstacle through a finite blocklength coding scheme. In the physical layer, we encode randomly arriving packets using a variable-length coding scheme and transmit the encoded symbols by truncated channel inversion over parallel channels. In the network layer, we model the encoding and transmission processes as tandem queues. These queues backlog the data bits waiting to be encoded and the encoded symbols to be transmitted, respectively. This way, we represent the system as a two-dimensional Markov chain. By focusing on instances when the symbol queue is empty, we simplify the Markov chain into a one-dimensional Markov chain, with the packet queue being the system state. This approach allows us to analytically express power consumption and formulate a power minimization problem under hard delay constraints. Finally, we propose a heuristic algorithm to solve the problem and provide an extensive evaluation of the trade-offs between the hard delay constraint and power consumption. Full article

This novel research introduces a game-changing architecture design for Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) decoders in Fifth-Generation New-Radio (5G-NR) wireless communications, specifically designed to meet precise specifications and leveraging the layered Min-Sum (MS) algorithm. Our innovative approach presents a fully parallel architecture that is precisely engineered to cater to the demanding high-throughput requirements of enhanced Mobile Broadband (eMBB) applications. To ensure smooth computation in the MS algorithm, we use the Sub-Optimal Low-Latency (SOLL) technique to optimize the critical check node process. Thus, our design has the potential to greatly benefit certain Ultra-Reliable Low-Latency Communications (URLLC) scenarios. We conducted precise Bit Error Rate (BER) performance analysis on our LDPC decoder using a Hardware Description Language (HDL) Co-Simulation (MATLAB/Simulink/ModelSim) for two codeword rates (2/3 and 1/3), simulating the challenging Additive White Gaussian Noise (AWGN) channel environment. Full article

One of the core features of 5G networks is the ability to support multiple services on the same infrastructure, with network slicing being a key technology. However, existing network slicing architectures have limitations in efficiently handling slice requests with different requirements, particularly when addressing high-reliability and high-demand services, where many issues remain unresolved. For example, predicting whether actual physical resources can meet network slice request demands and achieving flexible, on-demand resource allocation for different types of slice requests are significant challenges. To address the need for more flexible and efficient service demands, this paper proposes a 5G network slicing deployment algorithm based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG). Firstly, a new 5G network slicing deployment system framework is established, which measures resources for three typical 5G network slicing scenarios (eMBB, mMTC, uRLLC) and processes different types of slice requests by predicting slice request traffic. Secondly, by adopting the multi-agent approach of MADDPG, the algorithm enhances cooperation between multiple service requests, decentralizes action selection for requests, and schedules resources separately for the three types of slice requests, thereby optimizing resource allocation. Finally, simulation results demonstrate that the proposed algorithm significantly outperforms existing algorithms in terms of resource efficiency and slice request acceptance rate, showcasing the advantages of multi-agent approaches in slice request handling. Full article

This work focuses on maximizing the sum rate of ultra-reliable low-latency communication (URLLC) systems by leveraging unmanned aerial vehicle-mounted reconfigurable intelligent surface (UAV-RIS) to provide short packet services for users based on the non-orthogonal multiple access (NOMA) protocol. To optimize the sum rate of system, a joint optimization is performed with respect to the power allocation, UAV position, decoding order, and RIS phase shifts. As the original problem is a non-convex integer optimization problem, it is challenging to obtain the optimal solution. Therefore, approximate solutions are derived using successive convex approximation (SCA), slack variables, and penalty-based methods. The simulation results demonstrate the superiority of the proposed resource allocation algorithm compared with the benchmark algorithm with orthogonal multiple access (OMA) scheme. In addition, this work emphasizes the performance gap between the proposed communication system and the traditional Shannon communication system in terms of throughput and the performance capacity sacrificed to achieve lower latency. Full article

Network slicing is a concept introduced in 5G networks that supports the provisioning of multiple types of mobile services with diversified quality of service (QoS) requirements in a shared network. Network slicing concerns the placement/allocation of radio processing resources and traffic flow transport over the Xhaul transport network—connecting the 5G radio access network (RAN) elements—for multiple services while ensuring the slices’ isolation and fulfilling specific service requirements. This work focuses on modeling and optimizing network slicing in packet-switched Xhaul networks, a cost-effective, flexible, and scalable transport solution in 5G RANs. The considered network scenario assumes two types of network slices related to enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications (URLLC) services. We formulate a network slicing planning optimization problem and model it as a mixed-integer linear programming (MILP) problem. Moreover, we develop an efficient price-and-branch algorithm (PBA) based on column generation (CG). This advanced optimization technique allows for overcoming the MILP model’s poor performance when solving larger network problem instances. Using extensive numerical experiments, we show the advantages of the PBA regarding the quality of the solutions obtained and the computation times, and analyze the packet-switched Xhaul network’s performance in various network slicing scenarios. Full article

The Internet of Things (IoT) has revolutionized connected devices, with applications in healthcare, data analytics, and smart cities. For time-sensitive applications, 5G wireless networks provide ultra-reliable low-latency communication (URLLC) and fog computing offloads IoT processing. Integrating 5G and fog computing can address cloud computing’s deficiencies, but security challenges remain, especially in Authentication and Key Agreement aspects due to the distributed and dynamic nature of fog computing. This study presents an innovative mutual Authentication and Key Agreement protocol that is specifically tailored to meet the security needs of fog computing in the context of the edge–fog–cloud three-tier architecture, enhanced by the incorporation of the 5G network. This study improves security in the edge–fog–cloud context by introducing a stateless authentication mechanism and conducting a comparative analysis of the proposed protocol with well-known alternatives, such as TLS 1.3, 5G-AKA, and various handover protocols. The suggested approach has a total transmission cost of only 1280 bits in the authentication phase, which is approximately 30% lower than other protocols. In addition, the suggested handover protocol only involves two signaling expenses. The computational cost for handover authentication for the edge user is significantly low, measuring 0.243 ms, which is under 10% of the computing costs of other authentication protocols. Full article

The expansion of mobile connectivity with the arrival of 6G paves the way for the new Internet of Verticals (6G-IoV), benefiting autonomous driving. This article highlights the importance of vehicle-to-everything (V2X) and vehicle-to-vehicle (V2V) communication in improving road safety. Current technologies such as IEEE 802.11p and LTE-V2X are being improved, while new radio access technologies promise more reliable, lower-latency communications. Moreover, 3GPP is developing NR-V2X to improve the performance of communications between vehicles, while IEEE proposes the 802.11bd protocol, aiming for the greater interoperability and detection of transmissions between vehicles. Both new protocols are being developed and improved to make autonomous driving more efficient. This study analyzes and compares the performance of the protocols mentioned, namely 802.11p, 802.11bd, LTE-V2X, and NR-V2X. The contribution of this study is to identify the most suitable protocol that meets the requirements of V2V communications in autonomous driving. The relevance of V2V communication has driven intense research in the scientific community. Among the various applications of V2V communication are Cooperative Awareness, V2V Unicast Exchange, and V2V Decentralized Environmental Notification, among others. To this end, the performance of the Link Layer of these protocols is evaluated and compared. Based on the analysis of the results, it can be concluded that NR-V2X outperforms IEEE 802.11bd in terms of transmission latency (L) and data rate (DR). In terms of the packet error rate (PER), it is shown that both LTE-V2X and NR-V2X exhibit a lower PER compared to IEEE protocols, especially as the distance between the vehicles increases. This advantage becomes even more significant in scenarios with greater congestion and network interference. Full article

Sharing resources through network slicing in a physical infrastructure facilitates service delivery to various sectors and industries. Nevertheless, ensuring security of the slices remains a significant hurdle. In this paper, we investigate the utilization of State-of-the-Art (SoA) Virtual Private Network (VPN) solutions in 5G networks to enhance security and performance when isolating slices. We deploy and orchestrate cloud-native network functions to create multiple scenarios that emulate real-life cellular networks. We evaluate the performance of the WireGuard, IPSec, and OpenVPN solutions while ensuring confidentiality and data protection within 5G network slices. The proposed architecture provides secure communication tunnels and performance isolation. Evaluation results demonstrate that WireGuard provides slice isolation in the control and data planes with higher throughput for enhanced Mobile Broadband (eMBB) and lower latency for Ultra-Reliable Low-Latency Communications (URLLC) slices compared to IPSec and OpenVPN. Our developments show the potential of implementing WireGuard isolation, as a promising solution, for providing secure and efficient network slicing, which fulfills the 5G key performance indicator values. Full article

Many emerging applications, such as factory automation, electric power distribution, and intelligent transportation systems, require multicast Ultra-Reliable Low-Latency Communications (mURLLC). Since 3GPP Release 17, 5G systems natively support multicast functionality, including multicast Hybrid Automatic Repeat Request and various feedback schemes. Although these features can be promising for mURLLC, the specifications and existing studies fall short in offering guidance on their efficient usage. This paper presents the first comprehensive system-level evaluation of mURLLC, leveraging insights from 3GPP specifications. It points out (i) how mURLLC differs from traditional multicast broadband wireless communications, and (ii) which approaches to provide mURLLC require changing the paradigm compared with the existing solutions. Finally, the paper provides recommendations on how to satisfy strict mURLLC requirements efficiently, i.e., with low channel resource consumption, which increases the capacity of 5G systems for mURLLC. Simulation results show that proper configuration of multicast mechanisms and the corresponding algorithms for mURLLC traffic can reduce resource consumption up to three times compared to the baseline solutions proposed for broadband multicast traffic, which significantly increases the system capacity. Full article

The expected development of the future generation of wireless communications systems such as 6G aims to achieve an ultrareliable and low-latency communications (URLLCs) while maximizing the data rates. These requirements push research into developing new advanced technologies. To this end, massive multiple input multiple output (MMIMO) is introduced as a promising transmission approach to fulfill these requirements. However, maximizing the downlink-achievable sum rate (DASR) in MMIMO with a frequency division duplex (FDD) transmission mode and limited coherence time (LCT) is very challenging. To address this challenge, this paper proposes a DASR maximization approach using a feasible power allocation optimization method. The proposed approach is based on smartly allocating the total transmit power between the data transmission and training sequence transmission for channel estimation. This can be achieved by allocating more energy to the training signal than the data transmission during the channel estimation process to improve the quality of channel estimation without compromising more training sequence length, thus maximizing the DASR. Additionally, the theory of random matrix approach is exploited to derive an asymptotic closed-form expression for the DASR with a regularized zero-forcing precoder (RZFP), which allows the power optimization process to be achieved without the need for computationally complex Monte Carlo simulations. The results provided in this paper indicate that a considerable enhancement in the DASR performance is achieved using the proposed power allocation method in comparison with the conventional uniform power allocation method. Full article

Remote control over communication networks with bandwidth-constrained channels has attracted considerable recent attention because it holds the promise of enabling a large number of real-time applications, such as autonomous driving, smart grids, and the industrial internet of things (IIoT). However, due to the limited bandwidth, the sub-packets or even bits have to be transmitted successively, thereby experiencing non-negligible latency and inducing serious performance loss in remote control. To overcome this, we introduce an incremental coding method, in which the actuator acts in real time based on a partially received packet instead of waiting until the entire packet is decoded. On this basis, we applied incremental coding to a linear control system to obtain a remote-control scheme. Both its stability conditions and average linear-quadratic-Gaussian-(LQG) cost are presented. Then, we further investigated a multi-user remote-control method, with a particular focus on its applications in the demand response of smart grids over bandwidth-constrained communication networks. The utility loss due to the bandwidth constraint and communication latency are minimized by jointly optimizing the source coding and real-time demand response. The numerical results show that the incremental-coding-aided remote control performed well in both single-user and multi-user scenarios and outperformed the conventional zero-hold control scheme significantly under the LQG metric. Full article

Currently, we exist in the 5G division of the wireless technology cycle, where the standardization is complete and deployment is being carried out. However, 5G networks do not have the capacity to deliver an automated and intelligent network that supports connected intelligence. 6G is what enables this, and globally, countries are aiming to lay the foundation for the communication needs of 2030. This brings out a very key question and discussion on how wireless communications will develop in the future, particularly adapting to the range and set of applications and user cases. Industry and academic efforts have started to explore beyond 5G and uncover 6G as 5G becomes more internationally accessible. We forecast that 6G will undergo a transition that is unheard of in the history of wireless cellular systems. 6G exists beyond mobile internet and will be required to support omnipresent AI services from the network’s core to its endpoints. Meanwhile, artificial intelligence (AI) will be crucial for developing and improving 6G designs, protocols, and operations. URLLC plays a crucial role in next-generation communication systems, particularly in 6G, for applications requiring ultra-low latency and reliability. These services support cutting-edge technologies like driverless vehicles, remote robotic surgery, smart factories, and augmented reality applications. URLLCs ensure robust connectivity and real-time responsiveness, enabling time-sensitive and safety-critical services in 6G communication infrastructures. This article illustrates the importance of URLLCs in 6G and their integration with deep learning, the security challenges, and their potential solutions. Further on, it establishes its relationship with key aspects of federated learning and security in the 6G domain. Full article