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Summary: Traditional Orthogonal Multiple Access (OMA) and spectrum sharing methods struggle to provide the diverse quality of service (QoS) demands for enhanced mobile broadband (eMBB), ultra‐reliable low latency communications (uRLLC), and massive machine type communications (mMTC) leading to suboptimal performance and service quality degradation. Single‐carrier‐non‐orthogonal multiple access (SC‐NOMA) appears to be a more optimized solution. It can serve multiple users simultaneously on the same time‐frequency resources. This approach offers both enhanced spectrum efficiency and meets the QoS requirements for the coexistence of eMBB, uRLLC, and mMTC. However, SC‐NOMA has some drawbacks. Decoding a user's signal involves a complex successive interference cancellation (SIC) process that gets harder with more users causing delays and errors. Additionally, strong user signals can interfere with weaker ones, limiting the number of users per channel. In order to overcome the drawbacks associated with OMA and SC‐NOMA, this paper introduces a new method called user‐paired NOMA (hybrid NOMA). Hybrid NOMA adopts a strategic approach, employing two user pairing techniques: near‐far/far‐near (NF‐FN) and near‐near/far‐far (NN‐FF). NF‐FN pairing prioritizes users with similar signal strengths but different distances from the base station. This minimizes interference for the weaker user during SIC. NN‐FF pairing, on the other hand, groups users with similar signal strengths and proximity. This approach further simplifies SIC and minimizes potential interference altogether. The simulation results demonstrate trade‐offs between eMBB and uRLLC performance. OMA suffers with dedicated resource allocation, while SC‐NOMA balances performance but experiences interference. NN‐FF prioritizes eMBB and offers best latency, while NF‐FN prioritizes uRLLC with high spectral efficiency but suffers from higher latency. Finally, by providing a thorough grasp of how hybrid NOMA resource allocation works to improve the performance of various use cases, this research makes a significant contribution to the field of 5G spectrum optimization. [ABSTRACT FROM AUTHOR]

5G deterministic network is an important part to support the construction of 5G+ Industrial Internet, and it is of great significance to study the key technologies and landing schemes of 5G deterministic network. Firstly, 5G ultra-reliability low latency communication technology and frame replication and cancellation technology were studied to reduce transmission latency and improve reliability. Secondly, cyclic queue forwarding technology was explored in 5G networks to eliminate end-to-end jitter. Finally, a 5G deterministic network landing scheme was proposed and tested in actual industrial production labs. The test results show that the comprehensive performance of the proposed network scheme is better than the existing network schemes, and can meet the demand for 5G deterministic networks in many industrial scenarios.

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. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

Short block length "block" codes are typically not used in wireless standards as soft decision decoding is computationally intensive and hard decision decoding results in performance loss. However, short block lengths are of interest to massive machine-type communications (mMTC) and ultra-reliable low-latency communications (URLLC). In this paper, we propose a diversity preserving enhanced hard-decision decoding scheme for parity check codes (PCC) over Rayleigh fading channels. The proposed flip decoding scheme has linear complexity in the block length. Theoretical analysis and simulation results verify the correctness of the proposed detection scheme. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research work analyzes economic alternatives for the provision of ultra-reliable low latency communication (URLLC) and enhanced mobile broadband (eMBB) services by mobile network operators over the same fifth-generation (5G) network. Two business models are proposed to provide the two services to end users. Concretely, a monopoly is a single operator who offers both services, and a duopoly is two different operators that share network resources and offer one service each. In addition, two types of network scenarios for resource sharing are studied. Specifically, a shared network (SN) is a type of network scenario allowing resources to be shared between the two services without priority. A differentiated network (DN) is a type of network scenario that allows resources to be shared between the two services with a priority to URLLC service using network slicing (NS). Regarding the economic aspects, the incentive is modeled through the user’s utility and the operator’s benefit. At the same time, game theory is used to model the strategic interaction between users and operators, and queuing theory is used to model the interaction between the two services. We conclude that the monopoly social welfare (SW) is closer to the SW of the social optimum than the duopoly SW. In addition, the DN scenario to offer the services through NS is more suitable than the SN scenario since the point of view of service prices, user utilities, and operator benefit. [ABSTRACT FROM AUTHOR]

The fifth-generation (5G) technology standard in telecommunications is expected to support ultra-reliable low latency communication to enable real-time applications such as industrial automation and control. 5G configured grant (CG) scheduling features a pre-allocated periodicity-based scheduling approach, which reduces control signaling time and guarantees service quality. Although this enables 5G to support hard real-time periodic traffics, synthesizing the schedule efficiently and achieving high resource efficiency, while serving multiple communications, are still an open problem. In this work, we study the trade-off between scheduling flexibility and control overhead when performing CG scheduling. To address the CG scheduling problem, we first formulate it using satisfiability modulo theories (SMT) so that an SMT solver can be used to generate optimal solutions. To enhance scalability, we propose two heuristic approaches. The first one as the baseline, Co1, follows the basic idea of the 5G CG scheduling scheme that minimizes the control overhead. The second one, CoU, enables increased scheduling flexibility while considering the involved control overhead. The effectiveness and scalability of the proposed techniques and the superiority of CoU compared to Co1 have been evaluated using a large number of generated benchmarks as well as a realistic case study for industrial automation. [ABSTRACT FROM AUTHOR]

The fifth generation (5G) of mobile networks is emerging as a key enabler of modern factory automation (FA) applications that ensure timely and reliable data exchange between network components. Network slicing (NS), which shares an underlying infrastructure with different applications and ensures application isolation, is the key 5G technology to support the diverse quality of service requirements of modern FA applications. In this article, an end-to-end (E2E) NS solution is proposed for FA applications in a 5G network. Regression approaches are used to construct a performance model for each slice to map the service level agreement to the network attributes. Interference coordination approaches for switched beam systems are proposed to optimize radio access network (RAN) performance models. A case study of a non-public network is used to show the proposed NS solution. Simulation result shows that for services with different QoS requirements, different IC approaches should be used as optimization methods. Design prediction using regression approach has been evaluated and shows that the prediction successful rate increases when more existing data are used. [ABSTRACT FROM AUTHOR]

Abstract Integration of unmanned aerial vehicles (UAVs) with ultra-reliable and low-latency communication (URLLC) systems can improve the real-time communication performance for various industrial internet of things (IIoT) applications. Designing an intelligent resource allocation system is one of the challenges posed by an energy-constrained UAV communication system. Therefore, we formulate a sum rate maximization problem, subject to the UAVs’ energy by optimizing the blocklength allocation and the power control jointly in the uplink UAV-assisted URLLC systems, in which the probabilistic channel model between UAV and users is adopted. The problem is difficult to solve due to the non-convex objective function and the energy constraints, and also challenging to make fast decision in the complex communication environment. Thus, we propose a deep reinforcement learning (DRL)-based scheme to optimize the blocklength allocation and power control jointly. First, transform the original problem into the multi-agent reinforcement learning process, where each subcarrier is regarded as the agent that optimizes its individual blocklength allocation and power control. Then, each agent makes the intelligent decision to obtain the maximum reward value depending on the weighted segmented reward function, which is related to the UAV energy consumption and user rates to improve the rate performance. Finally, the simulation results show that the proposed scheme outperforms the benchmark schemes and has the stable convergence in different settings, such as the learning rate, the error probability, the subcarrier spacing, and the number of users.

At present, the society is in an era of rapid development of science and technology, and the rapid development of wireless communication technology has not only promoted the digital transformation of industry, transportation, medical and other fields, but also continuously upgraded wireless communication networks, trying to move from wired to wireless. With the continuous evolution of computer technology and wireless communication technology, many application scenarios require highly reliable transmission in a wireless environment. Especially in the fields of modern industrial automation and autonomous driving, the demand for highly reliable transmission is more urgent. 5G technology was delved into, which was one of the most advanced wireless transmission technologies in the industry, focusing on multi-channel redundant transmission technology within 5G systems. The key points of the technology in terms of application background, technical principles and technical route were summarized. In terms of application background, the practical application requirements of 5G redundant transmission in wireless scenarios such as modern industrial automation and autonomous driving were highlighted. In terms of technical principles, the relevant research was summarized and sorted out from the end-to-end multi-channel redundant transmission of services, the analysis of the technical principles of 5G multi-channel redundant transmission were focused on, and its unique advantages in improving transmission reliability were explained. In terms of technical routes, the development direction of 5G multi-channel redundant transmission technology and various possible implementation paths were comprehensively considered. Finally, the difficulties and challenges of the future development of 5G multi-channel redundant transmission technology were pointed out, and its future development trend was discussed, so as to better understand the key role and prospect of 5G redundant transmission technology in the field of wireless communication.

当前社会正处在科技高速发展的时代，无线通信技术的迅猛发展不仅推动了工业、交通、医疗等领域的数字化转型，也在不断升级无线通信网络，试图从有线向无线化迈进。随着计算机技术和无线通信技术的不断演进，许多应用场景要求在无线环境下实现高可靠传输。特别是面向现代工业自动化、自动驾驶等领域，对高可靠传输的需求更为迫切。深入研究了作为当前业界最先进的无线传输技术之一的5G技术，重点关注了5G系统内多路冗余传输技术。综述了该技术在应用背景、技术原理和技术路线方面的关键要点。在应用背景方面，突出了5G冗余传输在现代工业自动化、自动驾驶等无线场景中的实际应用需求。在技术原理方面，有针对性地从业务端到端多路冗余传输对有关研究进行归纳和梳理，重点分析5G多路冗余传输的技术原理，解释了其在提高传输可靠性方面的独特优势。在技术路线方面，综合考虑了5G多路冗余传输技术的发展方向和各种可能的实施路径。最后，指出5G多路冗余传输技术未来发展的困难和挑战，并探讨其未来发展趋势，以更好地理解5G冗余传输技术在无线通信领域的关键作用和前景

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Recently, 5G has become an important mechanism to serve a growing amount of users in the network, which provides enhanced mobile broadband (eMBB) and ultra-reliable low latency communications (URLLC) services. Meanwhile, Carrier Aggregation (CA) is a promising 5G technology which lets users aggregate fragmented carrier components (CCs) to enhance transmission efficiency. This paper addresses 5G scheduling problem in the CA-enabled eMBB–URLLC coexistence network using genetic algorithm (GA). The key idea is first treating the serving time slot of each user equipment (UE) as a gene and combining all genes to form a chromosome, then generating a set of chromosomes as the initial population and letting the population evolve to iteratively select the fittest one as the resource scheduling decision. Up to now, this is the first work using GA for solving the scheduling problem in the CA-enabled 5G network. Simulation results show that our proposed method can serve the most UEs (⁠|$4\%$|⁠) with the highest throughput (⁠|$7.1\%$|⁠) and lower delay. [ABSTRACT FROM AUTHOR]

The core value of 5G in the field of digital distribution network is to give play to the technical advantages of 5G in ultra-high reliability and low latency, and provide high reliability and low latency communication for the control related business of distribution network. In order to provide a systematic theoretical analysis scheme for the latency and reliability of 5G communication deployment applications in the distribution network, a typical architecture of 5G communication in the distribution network in combination with digital distribution network services was given, the latency model for 5G communication in the distribution network was deeply analyzed. The end-to-end latency analysis for 5G frame structures of four operators in China was conducted with 5G reliability values of 3GPP Rel-15 and Rel-16 through 5G link level simulation. At last, a joint analysis method of time latency and reliability of 5G communication in distribution network was proposed.

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.

One of the required communication solutions to support novel use cases, e.g., in industrial environments, for 5G systems and beyond is ultra-reliability low-latency communication (URLLC). An enabling technology for URLLC is massive multiple-input multiple-output (MIMO), which with its large antenna arrays can increase reliability due to improved user separation, array gain and the channel hardening effect. Measurements have been performed in an operating factory environment at 3.7 GHz with a co-located massive MIMO array and a unique randomly distributed array. Channel hardening can appear when the number of antennas is increased such that the variations of channel gain (small-scale fading) is decreased and it is here quantified. The cumulative distribution function (CDF) of the channel gains then becomes steeper and its tail is reduced. This CDF is modeled and the required fading margins are quantified. By deploying a distributed array, the large-scale power variations can also be reduced, further improving reliability. The large array in this rich scattering environment, creates a more reliable channel as it approaches an independent identically distributed (i.i.d.) complex Gaussian channel, indicating that one can rethink the system design in terms of, e.g., channel coding and re-transmission strategies, in order to reduce latency. To conclude, massive MIMO is a highly interesting technology for reliable connectivity in reflective and heavily shadowed industrial environments.

Industry 4.0 incorporates the integration of cloud computing, Industrial Internet of Things (IIoT), and modern communication technologies within the industrial automation systems. Various devices with different network requirements of high reliability and low latency, rely on connectivity. The 5G and Beyond (B5G) software-defined architecture facilitates Network Function Virtualization (NFV), which is an essential solution for fulfilling these stringent demands. NFV allows for the implementation and control of Virtual Network Functions (VNFs) in dynamic network environments. VNF placement optimization has been extensively studied in the 5G perspective outside the industry environment with a focus on minimizing delay and cost, increasing VNF reliability, and increasing resource efficiency. However, the complex dynamics of the wireless channel in industrial environments have a considerable impact on the essential delay factors that are important for optimizing the deployment of VNFs. This study focuses on modeling a Wireless Sensor Network (WSN) based Industry 4.0 factory automation scenario at mmWave band, formulating an optimization problem to minimize overall delay while considering packet loss rate in the 5G industrial wireless channel. The optimization problem is formulated as a Markov Decision Process (MDP) and two Reinforcement Learning (RL) based algorithms AVP-Q and AVP-DQN are proposed for optimizing the VNF placement. The proposed algorithms are extensively evaluated against the Value Iteration algorithm which assumes a completely known MDP model and two other algorithms from the literature. The simulated results show that AVP-DQN outperforms existing algorithms for this scenario by 39% and 22.6% and the achieved performance is only close to that of the Value Iteration algorithm.

As the complexity of wireless mobile networks increases significantly, artificial intelligence (AI) and machine learning (ML) have become key enablers for radio resource management and orchestration. In this paper, we propose a multi-agent reinforcement learning (RL) method for allocating radio resources to mobile users under random traffic arrivals, in which Ultra-Reliable Low-Latency Communications (URLLC) and enhanced Mobile Broad-Band (eMBB) services are jointly considered in the same radio access network (RAN). The proposed system includes hierarchically placed RL agents, where the main-agent residing on the upper hierarchy performs inter-slice resource allocation between the URLLC and eMBB slices. The URLLC and eMBB sub-agents are responsible for the resource allocation within their own slice, where the objective is to maximize the eMBB throughput while satisfying the latency requirements of the URLLC slice. In the RL algorithm, the state space includes the queue occupancy and the channel quality information of mobile users while the action space specifies the resource allocation to the users. For a computationally efficient RL training, the state space is significantly reduced by quantizing the queue occupancy and grouping the users according to their channel qualities. The numerical results for the URLLC show that the proposed RL-based approach provides the average delay results of lower than 1 ms for all experiments while the worst case eMBB throughput degradation is limited to 4%.

The demand for ultra-reliable low-latency communications (URLLC) has led to the adoption of grant-free (GF) access techniques by the 5G NR, with the goal of reducing uplink access time. When GF access is employed, the base station (BS) preallocates multiple transmission opportunities (TOs) that can be utilized by the user equipment (UE) as needed. However, this approach results in inefficient resource utilization as unused TOs are wasted. To overcome this inefficiency, the 5G NR allows the assignment of configured grants (CG) to a group of UEs instead of a single one. This development has led research into group-based CG (GCG) schemes, whose reliance on shared resources can result in collisions. The collisions can be prevented by the use of stop-and-wait IR-HARQ schemes. Nevertheless, the delay caused by feedback latency is also undesirable as it severely affects latency performance. This work proposes two new IR-HARQ GCG schemes to efficiently handle feedback latency. The first one is able to eliminate the feedback latency overhead and is proven to simultaneously achieve the latency of a one-shot transmission and the energy efficiency of IR-HARQ, even in the presence of non-instantaneous feedback signaling. The second one features both a feedback latency protection mechanism, similar to the first scheme, and a mechanism specifically designed to further reduce latency. The performance of the proposed schemes is compared with scenarios where each UE uses either an individual one-shot or an IR-HARQ scheme. These comparisons encompass scenarios with either power or energy constraints. The results have shown that the second scheme always outperforms the IR-HARQ scheme and that it is able to outperform the one-shot scheme on a wide interval of feedback latency values, achieving a lower latency both for power and energy constrained cases.

A key feature of 5G systems is the Ultra-Reliable Low-Latency Communication (URLLC), which can be used for remote surgery, smart grids, industrial control, etc. URLLC requires millisecond-level delays and very high reliability, i.e., less than $10^{-5}$ packet loss probability. The ability to satisfy these very strict quality of service requirements depends on selecting the Modulation and Coding Schemes (MCS) for data transmissions. On the one hand, the selected MCS shall be robust enough to avoid multiple retransmissions within a small delay budget. On the other hand, the MCS shall be high-rate to reduce channel resource consumption and, thus, shall increase the system capacity for URLLC. The MCS selection problem is extremely challenging to capture the quickly varying wireless channel effects, e.g., in highly mobile scenarios, because the decision shall be made long before the actual transmission occurs. The paper proposes a novel MCS selection algorithm called ALPACA (Asymmetric Loss Prediction Algorithm for Channel Adaptation), which relies on a widely used class of convolutional-recurrent neural networks. However, in contrast to existing approaches, ALPACA explicitly considers the asymmetric error cost for channel prediction by utilizing quantile regression loss. Both real-life channel measurements and 3GPP channel models are used to evaluate the performance of ALPACA. Numerical results demonstrate the increase in the reliability and reduction in resource consumption compared with the existing MCS selection algorithms, which results in 40% growth of the network capacity.

5G is basically a new technology which had been already launched in the year 2020. These technologies have a huge development in the real world. Now 5G have been upgraded to 5G Advanced. The usage of 5G is increased than the previous 4G LTE. There will be increase in massive number of devices. The 5G devices can be utilized in buildings, pedestrian, vehicles etc. which means that the devices should be utilized in static as well as dynamic purpose. In case of vehicles, velocity is the important parameter. The analysis of throughput, BLER and throughput fraction can be done by varying the velocity. On the other hand, due to variation in velocity, there will be Doppler Effect which causes the shift in frequency. The main cause of Doppler Effect is due to the movement of vehicles. The shift in frequency creates the variation of carrier frequency instantly and affected the throughput and BLER. For ignoring the Doppler Effect, a counter balance must be inserted at the receiver by following the Doppler Effect which will able to keep carrier frequency constant and further there will be no effect in Doppler frequency due to variation in frequency. This scenario has been specified the evaluation of throughput and BLER during the movement of vehicles without Doppler effect. It had been estimated that after a certain stage, with the increase in velocity, the throughput is decreased whereas the BLER is increased. The way of communication between device and base station can be done both in uplink and downlink mode. [ABSTRACT FROM AUTHOR]

Cost efficiency is an essential metric in the design of major part of what is expected to be the 5G network. Some of the 5G solutions, mainly those involving mmWave technology and network densification, are extremely expensive. Much of what was said about 5G rollout strategies has been said with regard to the world's major leaders in 5G technology and telecom infrastructure investment. However, a much more numerous group of countries often referred as emerging markets or middle-income economies has never hold a leadership in the development of cellular technologies. To date, few of them have fully leveraged the potential of 4G systems while many still have not ensured a return on investment in 3G. This gave rise to the views that these countries are not ready for 5G challenges. However, all of them are doomed to enter the era of another industrial revolution, where exactly 5G is to become the main driver. Yet, the use cases and the portfolio of services of the future networks will apparently depend on economic realities of the country where it will be deployed. There is a rather vague picture at the moment of how the 5G rollout may take place in this part of the world and that is the main reason for this study. In this paper, we outline the technical challenges and economic tensions associated with the developing of 5G physical infrastructure and address spectrum allocation issues with a particular focus on the needs of the future enhanced mobile broadband component. Then we discuss the role of government in establishing favorable regulatory framework, providing supportive policies and finding local drivers to facilitate 5G rollout and the challenges, confronting the operators paving their way to 5G. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) will be essential to support mission-critical applications of Ultra Reliable Low Latency Communication (URLLC) in futuristic Sixth-Generation (6G) networks. However, several security vulnerabilities and attacks have plagued previous generations of communication systems; thus, physical layer security, especially against eavesdroppers, is vital, especially for upcoming 6G networks. In this regard, UAVs have appeared as a winning candidate to mitigate security risks. In this paper, we leverage UAVs to propose two methods. The first method utilizes a UAV as Decode-and-Forward (DF) relay, whereas the second method utilizes a UAV as a jammer to mitigate eavesdropping attacks for URLLC between transmitter and receiver devices. Moreover, we present a low-complexity algorithm that outlines the two aforementioned methods of mitigating interception, i.e. increasing secrecy rate, and we compare them with the benchmark null method in which there is a direct communication link between transmitter and receiver without the UAV DF relay. Additionally, simulation results show the effectiveness of such methods by improving the secrecy rate and its dependency on UAV height, blocklength, decoding error probability and transmitter-receiver separation distance. Lastly, we recommend the best method to enhance the secrecy rate in the presence of an eavesdropper based on our simulations.

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).