Search Results (56)

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

In Mycobacterium tuberculosis, molecular predictions of ethambutol resistance rely primarily on the detection of mutations within embB. However, discordance between embB406 mutations and gold standard phenotypic drug sensitivity testing (DST) questions the significance of embB406 mutations used in molecular DST. This study tabulates embB mutations found in Canadian M. tuberculosis isolates and evaluates the impact of specific mutations on ethambutol resistance. The National Reference Centre for Mycobacteriology culture collection (n = 2796) was screened for isolates with embB mutations. Phenotypic DST was performed on the BACTEC™ MGIT™ 960 at ethambutol concentrations of 2–5 μg/mL. Whole genome sequencing was used for drug resistance predictions, phylogenomics and single nucleotide polymorphism analysis. Detection of resistance-associated embB mutations corresponded to a positive predictive value of 64.3%, negative predictive value of 99.2%, 98.7% specificity, and 73.3% sensitivity compared to phenotypic DST. Two embB406 mutation subtypes (Gly406Asp, Gly406Ala) were found among 16 isolates, of which 12 were sensitive at 5 µg/mL ethambutol with variable resistance between 2–4 µg/mL. A novel frameshift mutation in regulator embR (Gln258fs) was found in nine isolates. Mutations in embB406 were associated with low-level ethambutol resistance undetectable at the recommended critical concentration (5 μg/mL). These novel mutations may exacerbate variability in ethambutol resistance. 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

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

6G will connect heterogeneous intelligent agents to make them natively operate complex cooperative tasks. When connecting intelligence, two main research questions arise to identify how artificial intelligence and machine learning models behave depending on (i) their input data quality, affected by errors induced by interference and additive noise during wireless communication; (ii) their contextual effectiveness and resilience to interpret and exploit the meaning behind the data. Both questions are within the realm of semantic and goal-oriented communications. With this paper, we investigate how to effectively share communication spectrum resources between a legacy communication system (i.e., data-oriented) and a new goal-oriented edge intelligence one. Specifically, we address the scenario of an enhanced Mobile Broadband (eMBB) service, i.e., a user uploading a video stream to a radio access point, interfering with an edge inference system, in which a user uploads images to a Mobile Edge Host that runs a classification task. Our objective is to achieve, through cooperation, the highest eMBB service data rate, subject to a targeted goal effectiveness of the edge inference service, namely the probability of confident inference on time. We first formalize a general definition of a goal in the context of wireless communications. This includes the goal effectiveness, (i.e., the goal achievability rate, or the probability of achieving the goal), as well as goal cost (i.e., the network resource consumption needed to achieve the goal with target effectiveness). We argue and show, through numerical evaluations, that communication reliability and goal effectiveness are not straightforwardly linked. Then, after a performance evaluation aiming to clarify the difference between communication performance and goal effectiveness, a long-term optimization problem is formulated and solved via Lyapunov stochastic network optimization tools to guarantee the desired target performance. Finally, our numerical results assess the advantages of the proposed optimization and the superiority of the goal-oriented strategy against baseline 5G-compliant legacy approaches, under both stationary and non-stationary communication (and computation) environments. Full article

Network slicing shows promise as a means to endow 5G networks with flexible and dynamic features. Network function virtualization (NFV) and software-defined networking (SDN) are the key methods for deploying network slicing, which will enable end-to-end (E2E) isolation services permitting each slice to be customized depending on service requirements. The goal of this investigation is to construct network slices through a machine learning algorithm and allocate resources for the newly created slices using dynamic programming in an efficient manner. A substrate network is constructed with a list of key performance indicators (KPIs) like CPU capacity, bandwidth, delay, link capacity, and security level. After that, network slices are produced by employing multi-layer perceptron (MLP) using the adaptive moment estimation (ADAM) optimization algorithm. For each requested service, the network slices are categorized as massive machine-type communications (mMTC), enhanced mobile broadband (eMBB), and ultra-reliable low-latency communications (uRLLC). After network slicing, resources are provided to the services that have been requested. In order to maximize the total user access rate and resource efficiency, Dijkstra’s algorithm is adopted for resource allocation that determines the shortest path between nodes in the substrate network. The simulation output shows that the present model allocates optimum slices to the requested services with high resource efficiency and reduced total bandwidth utilization. Full article

The usage scenarios defined in the ITU-M2150-1 recommendation for IMT-2020 systems, including enhanced Mobile Broadband (eMBB), Ultra-reliable Low-latency Communication (URLLC), and massive Machine Type Communication (mMTC), allow the possibility of accessing different services through the set of Radio Interface Technologies (RITs), Long-term Evolution (LTE), and New Radio (NR), which are components of RIT. The potential of the low and medium frequency bands allocated by the Federal Communications Commission (FCC) for the fifth generation of mobile communications (5G) is described. In addition, in the Internet of Things (IoT) applications that will be covered by the case of use of the mMTC are framed. In this sense, a propagation channel measurement campaign was carried out at 850 MHz and 5.9 GHz in a covered corridor environment, located in an open space within the facilities of the Pedagogical and Technological University of Colombia campus. The measurements were carried out in the time domain using a channel sounder based on a Universal Software Radio Peripheral (USRP) to obtain the received signal power levels over a range of separation distances between the transmitter and receiver from 2.00 m to 67.5 m. Then, a link budget was proposed to describe the path loss behavior as a function of these distances to obtain the parameters for the close-in free space reference distance (CI) and the floating intercept (FI) path loss prediction models. These parameters were estimated from the measurements made using the Minimum Mean Square Error (MMSE) approach. The estimated path loss exponent (PLE) values for both the CI and FI path loss models at 850 MHz and 3.5 GHz are in the range of 2.21 to 2.41, respectively. This shows that the multipath effect causes a lack of constructive interference to the received power signal for this type of outdoor corridor scenario. These results can be used in simulation tools to evaluate the path loss behavior and optimize the deployment of device and sensor network infrastructure to enable 5G-IoT connectivity in smart university campus scenarios. Full article

The emergence of the sixth generation of cellular systems (6G) signals a transformative era and ecosystem for mobile communications, driven by demands from technologies like the internet of everything (IoE), V2X communications, and factory automation. To support this connectivity, mission-critical applications are emerging with challenging network requirements. The primary goals of 6G include providing sophisticated and high-quality services, extremely reliable and further-enhanced mobile broadband (feMBB), low-latency communication (ERLLC), long-distance and high-mobility communications (LDHMC), ultra-massive machine-type communications (umMTC), extremely low-power communications (ELPC), holographic communications, and quality of experience (QoE), grounded in incorporating massive broad-bandwidth machine-type (mBBMT), mobile broad-bandwidth and low-latency (MBBLL), and massive low-latency machine-type (mLLMT) communications. In attaining its objectives, 6G faces challenges that demand inventive solutions, incorporating AI, softwarization, cloudification, virtualization, and slicing features. Technologies like network function virtualization (NFV), network slicing, and software-defined networking (SDN) play pivotal roles in this integration, which facilitates efficient resource utilization, responsive service provisioning, expanded coverage, enhanced network reliability, increased capacity, densification, heightened availability, safety, security, and reduced energy consumption. It presents innovative network infrastructure concepts, such as resource-as-a-service (RaaS) and infrastructure-as-a-service (IaaS), featuring management and service orchestration mechanisms. This includes nomadic networks, AI-aware networking strategies, and dynamic management of diverse network resources. This paper provides an in-depth survey of the wireless evolution leading to 6G networks, addressing future issues and challenges associated with 6G technology to support V2X environments considering presenting +challenges in architecture, spectrum, air interface, reliability, availability, density, flexibility, mobility, and security. Full article

Fifth generation (5G) networks support ultra-reliable low-latency communications (URLLC) and enhanced mobile broadband (eMBB). The coexistence of URLLC and eMBB is often organized by non-orthogonal multiple access (NOMA), giving priority to URLLC and resulting in eMBB quality of service (QoS) degradation. In this paper, we address the issue of joint URLLC and eMBB transmission, focusing on the problem from the perspective of delay-tolerant eMBB. Due to the priority given to URLLC, we assume that an eMBB session may be interrupted if there are no free resources available for URLLC or delayed when a new eMBB session arrives. To make the scheme more flexible, we propose that interrupted and delayed eMBB sessions periodically check for free resources, rather than continuously. To analyze this scenario, we propose a retrial queuing system with two retrial buffers (orbits) for interrupted and delayed eMBB sessions. The stationary probability distribution, provided in matrix form by recursive formulas, is presented. The paper concludes with a numerical example showing that the scheme with two buffers, compared to one buffer, practically doubles the average number of active eMBB sessions while keeping the interruption probability below 0.001. We provide an illustration of the configuration of eMBB retrial rates to meet its QoS requirements. Full article

Tuberculosis remains the leading cause of death from a single pathogen. On the other hand, antimicrobial resistance (AMR) makes it increasingly difficult to deal with this disease. We present the hyperbolic embedding of the Mycobacterium tuberculosis protein interaction network (mtbPIN) of resistant strain (MTB XDR1219) to determine the biological relevance of its latent geometry. In this hypermap, proteins with similar interacting partners occupy close positions. An analysis of the hypermap of available drug targets (DTs) and their direct and intermediate interactors was used to identify potentially useful drug combinations and drug targets. We identify rpsA and rpsL as close DTs targeted by different drugs (pyrazinamide and aminoglycosides, respectively) and propose that the combination of these drugs could have a synergistic effect. We also used the hypermap to explain the effects of drugs that affect multiple DTs, for example, forcing the bacteria to deal with multiple stresses like ethambutol, which affects the synthesis of both arabinogalactan and lipoarabinomannan. Our strategy uncovers novel potential DTs, such as dprE1 and dnaK proteins, which interact with two close DT pairs: arabinosyltransferases (embC and embB), Ser/Thr protein kinase (pknB) and RNA polymerase (rpoB), respectively. Our approach provides mechanistic explanations for existing drugs and suggests new DTs. This strategy can also be applied to the study of other resistant strains. Full article

The 5G network is designed to serve three main use cases: enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable and low-latency communications (uRLLC). There are many new technological enablers, including the cloud radio access network (C-RAN) and network slicing, that can support 5G and meet its requirements. The C-RAN combines both network virtualization and based band unit (BBU) centralization. Using the network slicing concept, the C-RAN BBU pool can be virtually sliced into three different slices. 5G slices require a number of Quality of service (QoS) metrics, such as average response time and resource utilization. In order to enhance the C-RAN BBUs utilization while protecting the minimum QoS of the coexisting three slices, a priority-based resource allocation with queuing model is proposed. The uRLLC is given the highest priority, while eMBB has a higher priority than mMTC services. The proposed model allows the eMBB and mMTC to be queued and the interrupted mMTC to be restored in its queue to increase its chance to reattempt the service later. The proposed model’s performance measures are defined and derived using a continuous-time Markov chain (CTMC) model and evaluated and compared using different methodologies. Based on the results, the proposed scheme can increase C-RAN resource utilization without degrading the QoS of the highest-priority uRLLC slice. Additionally, it can reduce the forced termination priority of the interrupted mMTC slice by allowing it to re-join its queue. Therefore, the comparison of the results shows that the proposed scheme outperforms the other states of the art in terms of improving the C-RAN utilization and enhancing the QoS of eMBB and mMTC slices without degrading the QoS of the highest priority use case. Full article

Due to the COVID-19 pandemic, educational institutions globally were forced to close, resulting in a transition to online learning. However, this transition increased screen time and made e-learners more vulnerable to biopsychosocial issues. This study aimed to assess the impact of online learning on the eyes and mental health of medical science students, including those pursuing MBBS, Nursing, Optometry, Pharmacy, and Veterinary degrees during the COVID-19 lockdown period. A cross-sectional quantitative study was conducted, collecting online data from 182 samples using a socio-demographic data sheet (SDVS), Computer Vision Symptom Scale (CVSS 17), and the Perceived Stress Scale (PSS 10). Results revealed that most students spent between 2 and 4 h and >7 h on electronic devices before and during COVID-19, respectively, with many reporting moderate mental stress and eye strain. A weak positive correlation (r = 0.204 at p < 0.05) was found between perceived stress and eye strain, with the 24–29 age group reporting higher mean scores for eye strain. Female participants in the study reported higher mean scores for both eye strain and perceived stress. Additionally, the study found significant associations between eye strain and the electronic devices used, the program of study, and perceived stress levels. The participants’ ethnicity was also found to impact eye strain levels. The study concludes that the transition to online learning during COVID-19 caused moderate to severe levels of eye strain and mental stress, indicating the need for interventions for the student community. Full article

With the rapid development of the 5G power Internet of Things (IoT), new power systems have higher requirements for data transmission rates, latency, reliability, and energy efficiency. Specifically, the hybrid service of enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) has brought new challenges to the differentiated service of the 5G power IoT. To solve the above problems, this paper first constructs a power IoT model based on NOMA for the mixed service of URLLC and eMBB. Considering the shortage of resource utilization in eMBB and URLLC hybrid power service scenarios, the problem of maximizing system throughput through joint channel selection and power allocation is proposed. The channel selection algorithm based on matching as well as the power allocation algorithm based on water injection are developed to tackle the problem. Both theoretical analysis and experimental simulation verify that our method has superior performance in system throughput and spectrum efficiency. Full article

In 5G/B5G communication systems, network slicing is utilized to tackle the problem of the allocation of network resources for diverse services with changing demands. We proposed an algorithm that prioritizes the characteristic requirements of two different services and tackles the problem of allocation and scheduling of resources in the hybrid services system with eMBB and URLLC. Firstly, the resource allocation and scheduling are modeled, subject to the rate and delay constraints of both services. Secondly, the purpose of adopting a dueling deep Q network (Dueling DQN) is to approach the formulated non-convex optimization problem innovatively, in which a resource scheduling mechanism and the $ϵ$-greedy strategy were utilized to select the optimal resource allocation action. Moreover, the reward-clipping mechanism is introduced to enhance the training stability of Dueling DQN. Meanwhile, we choose a suitable bandwidth allocation resolution to increase flexibility in resource allocation. Finally, the simulations indicate that the proposed Dueling DQN algorithm has excellent performance in terms of quality of experience (QoE), spectrum efficiency (SE) and network utility, and the scheduling mechanism makes the performance much more stable. In contrast with Q-learning, DQN as well as Double DQN, the proposed algorithm based on Dueling DQN improves the network utility by 11%, 8% and 2%, respectively. Full article