Showing papers on "Mobile telephony published in 2021"
11 Jan 2021
TL;DR: In this paper, the relevant millimeter-wave enabling technologies are reviewed: they include the recent developments on the system architectures of active beamforming arrays, beamforming integrated circuits, antennas for base stations and user terminals, system measurement and calibration, and channel characterization.
Abstract: Ever since the deployment of the first-generation of mobile telecommunications, wireless communication technology has evolved at a dramatically fast pace over the past four decades. The upcoming fifth-generation (5G) holds a great promise in providing an ultra-fast data rate, a very low latency, and a significantly improved spectral efficiency by exploiting the millimeter-wave spectrum for the first time in mobile communication infrastructures. In the years beyond 2030, newly emerged data-hungry applications and the greatly expanded wireless network will call for the sixth-generation (6G) communication that represents a significant upgrade from the 5G network – covering almost the entire surface of the earth and the near outer space. In both the 5G and future 6G networks, millimeter-wave technologies will play an important role in accomplishing the envisioned network performance and communication tasks. In this paper, the relevant millimeter-wave enabling technologies are reviewed: they include the recent developments on the system architectures of active beamforming arrays, beamforming integrated circuits, antennas for base stations and user terminals, system measurement and calibration, and channel characterization. The requirements of each part for future 6G communications are also briefly discussed.
278 citations
TL;DR: The 6G enabled network in box (NIB) architecture is presented as a powerful integrated solution that can support comprehensive network management and operations of next-generation mobile networks by dynamically reconfiguring the deployment of network functions.
Abstract: The ongoing deployment of 5G network involves the Internet of Things (IoT) as a new technology for the development of mobile communication, where the Internet of Everything (IoE) as the expansion of IoT has catalyzed the explosion of data and can trigger new eras. However, the fundamental and key component of the IoE depends on the computational intelligence (CI), which may be utilized in the sixth generation mobile communication system (6G). The motivation of this article presents the 6G enabled network in box (NIB) architecture as a powerful integrated solution that can support comprehensive network management and operations. The 6G enabled NIB can be used as an alternative method to meet the needs of next-generation mobile networks by dynamically reconfiguring the deployment of network functions, providing a high degree of flexibility for connection services in various situations. Especially the CI technology such as evolutionary computing, neural computing and fuzzy systems utilized as a part of NIB have inherent capabilities to handle various uncertainties, which have unique advantages in processing the variability and diversity of large amounts of data. Finally, CI technology for NIB, which is widely used is also introduced such as distributed computing, fog computing, and mobile edge computing in order to achieve different levels of sustainable computing infrastructure. This article discusses the key technologies, advantages, industrial scenario applications of CI technology as NIB, typical use cases and development trends based on IoE, which provides directional guidance for the development of CI technology as NIB for 6G.
87 citations
TL;DR: In this paper, a detailed review of the developed and proposed use cases for 5G communications by SDO and other key players in mobile communication is provided, which serves as a guideline for understanding the future 5G deployment scenarios in various environments.
Abstract: The mobile demands and future business context are anticipated to be resolved by the fifth-generation (5G) of mobile communication systems. It is expected to provide an utterly mobile device, connected society, and support the demanding services of various use cases (UCs). This is intended to meet the demand requirement by providing services at tens of Gbps in terms of data rates, higher mobility range, lower latencies, and massive connectivity density devices per square kilometer. A comprehensive and up-to-date survey of the different developed and proposed use cases is presented in this paper. The first part of the paper presents the overview of the new 5G Architecture by introducing new features such as the new radio interface (New Radio), an overview of the 5G Core Network, minimum requirements, and the Radio Access Network, 5G spectrum requirements and other fundamentals of the network. Secondly, a detailed review of the developed and proposed use cases for 5G communications by the standards development organizations (SDO) and other key players in mobile communication is provided. Thirdly, we went ahead to propose spectrum bands for the deployment of the various use cases based on the low-, mid-, and high-band spectrum and further classified the use cases with respect to their relevance and family, identifying the IMT-2020 test environments and the usage scenarios derived by the 3GPP, fourthly, the channel capacity and the bandwidth of the spectrum was studied, simulated and compared to ascertain the spectrum proposed in this paper for each UC family. Hence, this paper serves as a guideline for understanding the future 5G deployment scenarios in various environments. This would allow system developers to design and implement 5G channel characterization models specific to the usage scenarios to meet the system requirements.
41 citations
TL;DR: An overview of the concept of coverage is presented, highlighting the ways it is studied, measured, and how it impacts the network performance, and an overlook of the most important key performance indicators influenced by coverage are discussed.
Abstract: Seamless and ubiquitous coverage are key factors for future cellular networks. Despite capacity and data rates being the main topics under discussion when envisioning the Fifth Generation (5G) and beyond of mobile communications, network coverage remains one of the major issues since coverage quality highly impacts the system performance and end-user experience. The increasing number of base stations and user terminals is anticipated to negatively impact the network coverage due to increasing interference. Furthermore, the “ubiquitous coverage” use cases, including rural and isolated areas, present a significant challenge for mobile communication technologies. This survey presents an overview of the concept of coverage, highlighting the ways it is studied, measured, and how it impacts the network performance. Additionally, an overlook of the most important key performance indicators influenced by coverage, which may affect the envisioned use cases with respect to throughput, latency, and massive connectivity, are discussed. Moreover, the main existing developments and deployments which are expected to augment the network coverage, in order to meet the requirements of the emerging systems, are presented as well as implementation challenges.
39 citations
TL;DR: This paper proposes a joint match-coalitional game based security-aware resource allocation scheme to deliver mobile social big data and proves that the proposal scheme outperforms other existing schemes.
Abstract: As both the scale of mobile networks and the population of mobile users keep increasing, the applications of mobile social big data have emerged where mobile social users can use their mobile devices to exchange and share contents with each other. The security resource is needed to protect mobile social big data during the delivery. However, due to the limited security resource, how to allocate the security resource becomes a new challenge. Therefore, in this paper we propose a joint match-coalitional game based security-aware resource allocation scheme to deliver mobile social big data. In the proposed scheme, first a coalition game model is introduced for base stations (BSs) to form groups to provide both wireless and security resource, where the resource efficiency and profits can be improved. Second, a matching theory based model is employed to determine the selecting process between communities and the coalitions of BSs so that mobile social users can form communities to select the optimal coalition to obtain security resource. Third, a joint matching-coalition algorithm is presented to obtain the stable security-aware resource allocation. At last, the simulation experiments prove that the proposal scheme outperforms other existing schemes.
36 citations
TL;DR: In this paper, a two-stage auction scheme is proposed to maximize utilities for both sellers and buyers in the network, and two algorithms are proposed to further refine TARCO on the social welfare of the network.
Abstract: In heterogeneous cellular network, task scheduling for computation offloading is one of the biggest challenges. Most works focus on alleviating heavy burden of macro base stations by moving the computation tasks on macro cell user equipment (MUE) to remote cloud or small cell base stations. But the selfishness of network users is seldom considered. Motivated by the multiple access mobile edge computing, this paper provides incentive for task transfer from macro cell users to small cell base stations. The proposed incentive scheme utilizes small cell user equipments to provide relay services. The problem of computation offloading is modeled as a two-stage auction, in which the remote MUEs with common social character can form a group and then buy the computation resource of small cell base stations with the relaying of small cell user equipment. A two-stage auction scheme named TARCO is contributed to maximize utilities for both sellers and buyers in the network. The truthfulness, individual rational and budget balance properties of TARCO are also proved in this paper. In addition, two algorithms are proposed to further refine TARCO on the social welfare of the network. One can achieve higher utility of MUEs and the other can obtain higher total social welfare. Extensive simulation results demonstrate that, TARCO is better than random algorithm by 104.90 percent in terms of average utility of MUEs, while the performance of TARCO is further improved up to 28.75 percent and 17.06 percent by the proposed two algorithms, respectively.
36 citations
08 Apr 2021
TL;DR: In this paper, the authors have discussed the 5G and IoT along with its implementation, specifications, potential challenges and other similar parameters related to the modern 5G technology are discussed in this paper.
Abstract: 5G (The Fifth generation) is the state-of-the-art technology, which has the potential to create new interfaces for the daily used devices and networking components. To communicate with devices, wireless technologies are generally used and also 5G plays a major role in connecting larger number of users to provide smarter and faster communications. This is majorly designed for achieving better coverage, bandwidth, reliability & latency, which can grow faster across the globe. Basically, the concept behind the 5G and wireless technology is to reduce the load & stabilize the technical solutions to enable applications for better mobile communication and utilized with latest applications in the business area. The current 4G network i.e long term evolution advanced (LTE - A) is not as good as 5G for meeting the demands of multiple unified communication devices that requires a very high data speed , low latency quality of service (QoS) , higher bandwidth and negligence interference. Henceforth, IoT (Internet of Things) & 5G plays a major role in mobile applications & network for e.g. health applications, smart watches, smart cities, smart cards, beacons, etc. The concept of 5G & IoT along with its implementation, specifications, potential challenges and other similar parameters related to the modern 5G technology are discussed in this paper.
35 citations
TL;DR: In this article, a weighted Markov prediction model based on mobile user classification was proposed to predict the mobility of mobile users by analyzing real mobile communication data, where the complexity of a user's trajectory was measured using the mobile trajectory entropy.
Abstract: The vast amounts of mobile communication data collected by mobile operators can provide important insights regarding epidemic transmission or traffic patterns. By analyzing historical data and extracting user location information, various methods can be used to predict the mobility of mobile users. However, existing prediction algorithms are mainly based on the historical data of all users at an aggregated level and ignore the heterogeneity of individual behavior patterns. To improve prediction accuracy, this paper proposes a weighted Markov prediction model based on mobile user classification. The trajectory information of a user is extracted first by analyzing real mobile communication data, where the complexity of a user’s trajectory is measured using the mobile trajectory entropy. Second, classification criteria are proposed based on different user behavior patterns, and all users are classified with machine learning algorithms. Finally, according to the characteristics of each user classification, the step threshold and the weighting coefficients of the weighted Markov prediction model are optimized, and mobility prediction is performed for each user classification. Our results show that the optimized weighting coefficients can improve the performance of the weighted Markov prediction model.
31 citations
TL;DR: In this paper, the authors provide an overview on the handover management for connected drones in future mobile networks, with a special focus on the drone handover process and discuss specific solutions for addressing possible problems.
Abstract: Drones will be a significant part of future mobile communication networks, serving as mobile users or acting as mobile base stations at sky. Although they will provide several solutions related to mobile communication networks and other non-communication services, drones also possess numerous challenges, especially when it comes to their handover management. Unlike terrestrial networks, drones are mobile devices that move in a three-dimension (3D) environment, which further complicates mobility issues. Therefore, this paper provides an overview on the handover management for connected drones in the future mobile networks. The study summarizes how current research efforts approach the issues that characterize drones, with special focus on the handover process. This work also provides a general concept of drone integration in heterogeneous networks and discusses specific solutions for addressing possible problems. This survey further offers a brief discussion and guidance for upcoming research directions related to connected drones in future heterogeneous networks.
27 citations
TL;DR: This paper verifies the superiority of the improved data fusion algorithm in terms of energy consumption in the Wireless Sensor Network (WSN), the number of surviving nodes in the WSN, the communication traffic in theWSN, and the applicability of the ladder-type fusion algorithm.
Abstract: This paper analyzes the network architecture of the Iridium system, Orbcomm system, Narrow Band-Internet of Things (NB-IoT) and Long Range Radio (Lo Ra) in the satellite 5G mobile communication system. A new Dynamic Routing based on Multi-factor Forwarding (MF-DR) protocol is proposed. This paper simulates the ladder-type data fusion algorithm in terms of energy consumption in the Wireless Sensor Network (WSN), the number of surviving nodes in the WSN, the communication traffic in the WSN, and the applicability of the ladder-type fusion algorithm. This verifies the superiority of the improved data fusion algorithm.
26 citations
TL;DR: In this paper, the authors demonstrate how spectrum up to 1 THz will support mobile communications beyond 5G in the coming decades, and show the natural isolation between terrestrial networks and surrogate satellite systems, as well as between terrestrial mobile users and co-channel fixed backhaul links.
Abstract: This letter demonstrates how spectrum up to 1 THz will support mobile communications beyond 5G in the coming decades. Results of rooftop surrogate satellite/tower base station measurements at 140 GHz show the natural isolation between terrestrial networks and surrogate satellite systems, as well as between terrestrial mobile users and co-channel fixed backhaul links. These first-of-their-kind measurements and accompanying analysis show that by keeping the energy radiated by terrestrial emitters on the horizon (e.g., elevation angles ≤ 15°), there will not likely be interference in the same or adjacent bands between passive satellite sensors and terrestrial terminals, or between mobile links and terrestrial backhaul links at frequencies above 100 GHz.
TL;DR: In this paper, the authors analyzed the challenges imposed by the considerably increased delay in the communication link on the random access (RA) procedure and proposed new solutions to overcome those challenges.
Abstract: Non-terrestrial Networks (NTNs) have become an appealing concept over the last few years and they are foreseen as a cornerstone for the next generations of mobile communication systems. Despite opening up new market opportunities and use cases for the future, the novel impairments caused by the signal propagation over the NTN channel, compromises several procedures of the current cellular standards. One of the first and most important procedures impacted is the random access (RA) procedure, which is mainly utilized for achieving uplink synchronization among users in several standards, such as the fourth and fifth generation of mobile communication (4 & 5G) and narrowband internet of things (NB-IoT). In this work, we analyse the challenges imposed by the considerably increased delay in the communication link on the RA procedure and propose new solutions to overcome those challenges. A trade-off analysis of various solutions is provided taking into account also the already existing ones in the literature. In order to broaden the scope of applicability, we keep the analysis general targeting 4G, 5G and NB-IoT systems since the RA procedure is quasi-identical among these technologies. Last but not least, we go one step further and validate our techniques in an experimental setup, consisting of a user and a base station implemented in open air interface (OAI), and an NTN channel implemented in hardware that emulates the signal propagation delay. The laboratory test-bed built in this work, not only enables us to validate various solutions, but also plays a crucial role in identifying novel challenges not previously treated in the literature. Finally, an important key performance indicator (KPI) of the RA procedure over NTN is shown, which is the time that a single user requires to establish a connection with the base station.
TL;DR: This article presents and discusses how to develop a scalable massive access S-IoT network by leveraging introduced technologies, including intelligent hybrid non-orthogonal multiple access (NOMA) transmission, grant-free superimposed pilot NOMA random access and multi-slot pilot allocation random access protocol.
Abstract: The integration of fifth generation (5G) mobile network and satellite communication promises a promotion on the interconnection of everything, and has become one of the key development directions of beyond 5G and even 6G. As an inevitable development trend of mobile communication, the space-based Internet of Things (S-IoT) is expected to be commercially available in building an integrated information infrastructure network of the space, air, ground and oceans, and so on. However, the tremendous growth in the number of connected user equipments poses a fundamental rethinking of conventional multiple access technologies, which is considered one of the open challenges in future S-IoT networks. In this article, we first review the main challenges of massive access in S-IoT. Then, we present and discuss how to develop a scalable massive access S–IoT network by leveraging introduced technologies, including intelligent hybrid non-orthogonal multiple access (NOMA) transmission, grant-free superimposed pilot NOMA random access and multi-slot pilot allocation random access protocol. Finally, some exciting future directions of massive access in S-IoT are revealed.
TL;DR: The methods used for developing applications for mobile devices have become an important field of research as mentioned in this paper, and the two most popular approaches, native and cross platform, and compare identical applications developed using various tools.
Abstract: The methods used for developing applications for mobile devices have become an important field of research. In this article, we analyze the two most popular approaches, native and cross platform, and compare identical applications developed using various tools.
TL;DR: This article presents a novel reliability-aware and deadline-constrained service composition method for mobile opportunistic networks capable of estimating service availability at run-time and leveraging a Krill–Herd-based algorithm to yield the deadline- Constrained, reliability- aware, and well-executable service composition schedules.
Abstract: An opportunistic link between two mobile devices or nodes can be constructed when they are within each other’s communication range. Typically, cyber–physical environments consist of a number of mobile devices that are potentially able to establish opportunistic contacts and serve mobile applications in a cost-effective way. Opportunistic mobile service computing is a promising paradigm capable of utilizing the pervasive mobile computational resources around the users. Mobile users are thus allowed to exploit nearby mobile services to boost their computing capabilities without investment in their resource pool. Nevertheless, various challenges, especially its quality-of-service and reliability-aware scheduling, are yet to be addressed. Existing studies and related scheduling strategies consider mobile users to be fully stable and available. In this article, we propose a novel method for reliability-aware and deadline-constrained service composition over opportunistic networks. We leverage the Krill–Herd-based algorithm to yield a deadline-constrained, reliability-aware, and well-executable service composition schedule based on the estimation of completion time and reliability of schedule candidates. We carry out extensive case studies based on some well-known mobile service composition templates and a real-world opportunistic contact data set. The comparison results suggest that the proposed approach outperforms existing ones in terms of success rate and completion time of composed services. Note to Practitioners —Recently, the rapid development of mobile devices and mobile communication leads to the prosperity of mobile service computing. Services running on mobile devices within a limited range are allowed to be composed to coordinate through wireless communication technologies and perform complex tasks and business processes. Despite its great potential, mobile service compositions remains a challenge since the mobility of users and devices imposes high unpredictability on the execution of tasks. A careful investigation into existing methods has found their various limitations, e.g., assuming time-invariant availability of mobile services. This article presents a novel reliability-aware and deadline-constrained service composition method for mobile opportunistic networks. Instead of assuming time-invariant availability of mobile nodes, the proposed method is capable of estimating service availability at run-time and leveraging a Krill–Herd-based algorithm to yield the deadline-constrained, reliability-aware, and well-executable service composition schedules. Case studies based on well-known service composition templates and real-world data sets suggest that it outperforms traditional ones in terms of success and completion time of composed services. It can thus aid the design and optimization of composite services as well as their smooth execution in a mobile environment. It can help practitioners better manage the reliability and performance of real-world applications built upon mobile services.
TL;DR: The experimental results show that the optimal deployment and allocation strategy for deploying edge servers in Ultra-dense network can minimize the cost of deployment and guarantee mobile users’ requirements on offloaded tasks’ completion time.
TL;DR: The goal is to put forward the so-called mixed improved communication architecture, which combines the benefits of cloud computing access edge and multi-source code resources, and performance of the proposed network architecture is the use of a discrete event simulation model.
TL;DR: This work addresses the question of whether radios can learn a pre-given target protocol as an intermediate step towards evolving their own and trains cellular radios to emerge a channel access policy that performs optimally under the constraints of the target protocol.
Abstract: Communication protocols are the languages used by network nodes. Before a user equipment (UE) can exchange data with a base station (BS), it must first negotiate the conditions and parameters for that transmission. This negotiation is supported by signaling messages at all layers of the protocol stack. Each year, the mobile communications industry defines and standardizes these messages, which are designed by humans during lengthy technical (and often political) debates. Following this standardization effort, the development phase begins, wherein the industry interprets and implements the resulting standards. But is this massive development undertaking the only way to implement a given protocol? We address the question of whether radios can learn a pre-given target protocol as an intermediate step towards evolving their own. Furthermore, we train cellular radios to emerge a channel access policy that performs optimally under the constraints of the target protocol. We show that multi-agent reinforcement learning (MARL) and learning-to-communicate (L2C) techniques achieve this goal with gains over expert systems. Finally, we provide insight into the transferability of these results to scenarios never seen during training.
TL;DR: In this paper, a multilink communication system combining ultra-high-frequency communication link, 4G cellular mobile communication link and BeiDou satellite communication link was proposed to realize the functions such as data receiving and sending, data encryption, and resuming transfer from the break point based on multiple links.
Abstract: To overcome the problem of data transmission of the aeroengine health management system, a multilink communication system combining ultrahigh-frequency communication link, 4G cellular mobile communication link, and BeiDou satellite communication link was proposed. This system can realize the functions such as data receiving and sending, data encryption, and resuming transfer from the break point based on multiple links. When the flight altitude is not high, the communication distance is short, so the UHF digital transmission radio communication link is adopted, which is highly efficient and stable. When the communication distance is long, the 4G cellular mobile communication link can ensure both the communication distance and the communication rate. In the area where 4G signal cannot be covered in extreme terrain environment, BeiDou satellite communication link is used for data transmission. Besides, in order to ensure the communication rate of the link, a multilink adaptive switching technology was also developed. The test verified that the system can perform adaptive switching among multiple links, realize air-ground data communication in the whole airspace, and achieve a good communication rate, which has significative value of engineering application.
TL;DR: In this article, a new source coding method based on the combination of compressed sensing and split-multistage vector quantization is proposed for secure and robust speech communications in an end-to-end communication system.
Abstract: A new source coding is proposed for secure and robust speech communications. The method is based on the combination of compressed sensing and split-multistage vector quantization. The proposed codec is integrated in an end-to-end communication system, and its performance is investigated in real mobile communication conditions. Channel compensation techniques are considered to mitigate the Rayleigh channel effects usually observed in mobile communications. Using the proposed speech coding scheme instead of current standards (e.g., AMR-WB) within the communication system results in a new end-to-end mobile communication design. The proposed design increases the transmission speed, robustness, and security without additional costs. For a bit rate of 8.85 kbit/s and in 10 dB Rayleigh environment, the recovered speech has a good perceptual evaluation of speech quality score close to 3.14 and a fair coherence speech intelligibility index value of around 0.47. Comparison with recent CS-based speech coding methods shows the merit of the proposed coder.
TL;DR: This work proposes a framework designed only with user-aggregated mobile phone data to synthesise realistic daily individual mobility — Digital Twin Travellers, and shows how with a series of histograms provided by the telecommunication service provider it is possible and plausible to disaggregate them into new synthetic and useful individual-level information.
Abstract: Mobile phone data generated in mobile communication networks has the potential to improve current travel demand models and in general, how we plan for better urban transportation systems. However, due to its high-dimensionality, even if anonymised there still exists the possibility to re-identify the users behind the mobile phone traces. This risk makes its usage outside the telecommunication network incompatible with recent data privacy regulations, hampering its adoption in transportation-related applications. To address this issue, we propose a framework designed only with user-aggregated mobile phone data to synthesise realistic daily individual mobility — Digital Twin Travellers. We explore different strategies built around modified Markov models and an adaption of the Rejection Sampling algorithm to recreate realistic daily schedules and locations. We also define a one-day mobility population score to measure the similarity between the population of generated agents and the real mobile phone user population. Ultimately, we show how with a series of histograms provided by the telecommunication service provider (TSP) it is possible and plausible to disaggregate them into new synthetic and useful individual-level information, building in this way a big data travel demand framework that is designed in accordance with current data privacy regulations.
TL;DR: This research paper presents a proposed model for an electromagnetically frequency tunable antenna that can cover a wide range of operating frequencies and shows that the resonance frequency of the proposed model can be adjusted by altering the electromagnetic properties of the ferrite material that forms the antenna.
Abstract: Current mobile communications technology relies heavily on efficient design of antennas, where the operational characteristics of the wireless communication systems are largely dependent on the directional specifications of the antenna. Consequently, the antennas that can be flexibly tuned to operate over a reasonable wide band of frequencies are of greatest interest for efficacious designs of mobile communication devices. In this research paper, a proposed model for an electromagnetically frequency tunable antenna that can cover a wide range of operating frequencies is presented. This design is based on altering the electromagnetic properties of the ferrite material that forms the antenna. It is shown that the resonance frequency of the proposed model can be adjusted by altering one of the main electromagnetic properties of the ferrite material of the antenna; that is its permeability. This can take place without introducing any modifications to the physical dimensions of the antenna. The proposed approach provides flexible operation of the antenna over a reasonable range of operating frequencies, which in turn results in an overall improvement in the performance of the mobile communication systems.
TL;DR: This paper proposes FANS, a Flexible and Anonymous Network Slicing method for cloud radio access network enabled authentication of emerging 5G service that achieves users’ identity privacy protection by hiding the public key associated with the actual identity in transmitted messages.
TL;DR: The results show no significant differences between the perceptions of teachers and students regarding the influence of MIM on the increasingly less normative linguistic uses of school-age children.
Abstract: The globalisation of mobile instant messaging (MIM) in applications like WhatsApp encourages the use of a non-standard linguistic register. The purpose of this study is to determine and assess the ...
TL;DR: An experimental mobile communication system with user tracking based on PM beamforming at 28 GHz is proposed and implemented, and beam management algorithms comparable to the 3GPP 5G NR standards are used.
Abstract: The usage of programmable metasurfaces (PMs) offers a promising way to realize flexible and fully electronic beam steering. Compared to phased arrays, PMs are particularly attractive due to their potential as a cost-effective base station in wireless communication systems, effectively reducing power consumption and total system costs. Although PM has been a hot topic, development of its real-time implementations are rarely touched. In this letter, an experimental mobile communication system with user tracking based on PM beamforming at 28 GHz is proposed and implemented. Thereby, beam management algorithms comparable to the 3GPP 5G NR standards are used. Experiments show that the system performs precise tracking with an angle mismatch from 0.5° to 2.5°, and minimizes the beam training overhead through flexible beam refinement. Experiments also show that the tracking of a mobile user with a maximum angular speed of 37.5°/s can be realized in the established system.
14 Jun 2021
TL;DR: In this paper, a data-driven machine learning-based radio resource scheduler prototype is introduced and evaluated in this work based on a specifically developed 5G radio resource simulator, which shows promising latency optimizations and possible trade-offs in uRLLC and eMBB coexistence.
Abstract: Multiple service types such as Ultra-Reliable Low Latency Communication (uRLLC) and Enhanced Mobile Broadband (eMBB) are envisioned to be incorporated into the next generation mobile communication standard 5G based on a single physical communication network. To unite these services with partly contradicting Quality of Service (QoS) requirements, Network Slicing is considered a key technology. uRLLC slices in particular are highly demanding, requiring extremely high reliability and low latency in the single-digit milliseconds range. Consequentially, the latency impact of radio resource management on the end-to-end latency is optimized in this work by using so-called Configured Grants (CGs), which aim to minimize latency-intensive scheduling requests by pre-allocating radio resources. As predicting future traffic demands and channel conditions are required to use CGs, a data-driven machine learning-based radio resource scheduler prototype is introduced and evaluated in this work based on a specifically developed 5G radio resource simulator. The results show promising latency optimizations and possible trade-offs in uRLLC and eMBB coexistence.
TL;DR: In this article, the authors conducted a scoping review of studies and reports by systematically searching: i) electronic databases (PubMed, PLOS ONE, PLoS Neglected Tropical Disease, LILACS, WHOLIS, ScienceDirect and Google scholar), ii) grey literature, using Google web and iii) documents in the list of references of the selected papers.
Abstract: The rapid expansion of dengue, Zika and chikungunya with large scale outbreaks are an increasing public health concern in many countries. Additionally, the recent coronavirus pandemic urged the need to get connected for fast information transfer and exchange. As response, health programmes have -among other interventions- incorporated digital tools such as mobile phones for supporting the control and prevention of infectious diseases. However, little is known about the benefits of mobile phone technology in terms of input, process and outcome dimensions. The purpose of this scoping review is to analyse the evidence of the use of mobile phones as an intervention tool regarding the performance, acceptance, usability, feasibility, cost and effectiveness in dengue, Zika and chikungunya control programmes. We conducted a scoping review of studies and reports by systematically searching: i) electronic databases (PubMed, PLOS ONE, PLOS Neglected Tropical Disease, LILACS, WHOLIS, ScienceDirect and Google scholar), ii) grey literature, using Google web and iii) documents in the list of references of the selected papers. Selected studies were categorized using a pre-determined data extraction form. Finally, a narrative summary of the evidence related to general characteristics of available mobile health tools and outcomes was produced. The systematic literature search identified 1289 records, 32 of which met the inclusion criteria and 4 records from the reference lists. A total of 36 studies were included coming from twenty different countries. Five mobile phone services were identified in this review: mobile applications (n = 18), short message services (n=7), camera phone (n = 6), mobile phone tracking data (n = 4), and simple mobile communication (n = 1). Mobile phones were used for surveillance, prevention, diagnosis, and communication demonstrating good performance, acceptance and usability by users, as well as feasibility of mobile phone under real life conditions and effectiveness in terms of contributing to a reduction of vectors/ disease and improving users-oriented behaviour changes. It can be concluded that there are benefits for using mobile phones in the fight against arboviral diseases as well as other epidemic diseases. Further studies particularly on acceptance, cost and effectiveness at scale are recommended.
TL;DR: Wang et al. as discussed by the authors presented an N-gram, semantic-based neural modeling method to detect the network traffic generated by the mobile malware and extracted the application layer payload from each packet.
Abstract: Mobile malware poses a great challenge to mobile devices and mobile communication. With the explosive growth of mobile networks, it is significant to detect mobile malware for mobile security. Since most mobile malware relies on the networks to coordinate operations, steal information, or launch attacks, evading network monitor is difficult for the mobile malware. In this paper, we present an N-gram, semantic-based neural modeling method to detect the network traffic generated by the mobile malware. In the proposed scheme, we segment the network traffic into flows and extract the application layer payload from each packet. Then, the generated flow payload data are converted into the text form as the input of the proposed model. Each flow text consists of several domains with 20 words. The proposed scheme models the domain representation using convolutional neural network with multiwidth kernels from each domain. Afterward, relationships of domains are adaptively encoded in flow representation using gated recurrent network and then the classification result is obtained from an attention layer. A series of experiments have been conducted to verify the effectiveness of our proposed scheme. In addition, to compare with the state-of-the-art methods, several comparative experiments also are conducted. The experiment results depict that our proposed scheme is better in terms of accuracy.
29 Mar 2021
TL;DR: Aiming at the high dynamic and non-centrality of the LEO satellite network, a dispersed computing paradigm was proposed in this article, which is suitable for high dynamic no-center scenarios.
Abstract: Low earth orbit (LEO) satellite network has the advantages of comprehensive coverage and has the unique benefits of short satellite-to-ground transmission distance and low construction cost, which can effectively complement the limited coverage of ground mobile communication network. Hence, LEO satellites gain extensive attention in the field of mobile communication. However, restricted by the existing mode (BP, Bent Pipe) of high transmission latency problems in the LEO space satellite computing (LSSC), it is challenging to meet the low latency requirement of time-sensitive tasks. Therefore, on-orbit collaborative computing technology for LSSC is proposed in this paper. While due to the high dynamic and non-centrality of the LEO satellite system, collaborative computing in satellite networks will face many difficulties. Aiming at the high dynamic and non-centrality of the LEO satellite network, this paper proposes a dispersed computing paradigm for the LEO satellite network, which is suitable for high dynamic no-center scenarios. In this dispersed computing paradigm, a steady-state matrix based on the time-expanded graph (TEG) model is introduced in this paper to steady-state the topology of a high dynamic LEO satellite network. According to the matrix, a transmission capacity and computing capacity based diffusion algorithm (TCGDA) is proposed to perform optimal task allocation in the LEO satellite network. The simulation results show that the proposed dispersed computing method can effectively complete the computing task with the optimized latency.
TL;DR: A CW control strategy for Wi-Fi 6 systems is proposed that leverages deep learning to search for optimal configuration of CW under different network conditions and results demonstrated that the deep learning scheme could always find the optimal CW adjustment multiple by adaptively perceiving the channel competition status.
Abstract: Internet of Things (IoT) is expected to vastly increase the number of connected devices. As a result, a multitude of IoT devices transmit various information through wireless communication technology, such as the Wi-Fi technology, cellular mobile communication technology, low-power wide-area network (LPWAN) technology. However, even the latest Wi-Fi technology is still ready to accommodate these large amounts of data. Accurately setting the contention window (CW) value significantly affects the efficiency of the Wi-Fi network. Unfortunately, the standard collision resolution used by IEEE 802.11ax networks is nonscalable; thus, it cannot maintain stable throughput for an increasing number of stations, even when Wi-Fi 6 has been designed to improve performance in dense scenarios. To this end, we propose a CW control strategy for Wi-Fi 6 systems. This strategy leverages deep learning to search for optimal configuration of CW under different network conditions. Our deep neural network is trained by data generated from a Wi-Fi 6 simulation system with some varying key parameters, e.g., the number of nodes, short interframe space (SIFS), distributed interframe space (DIFS), and data transmission rate. Numerical results demonstrated that our deep learning scheme could always find the optimal CW adjustment multiple by adaptively perceiving the channel competition status. The finalized performance of our model has been significantly improved in terms of system throughput, average transmission delay, and packet retransmission rate. This makes Wi-Fi 6 better adapted to the access of a large number of IoT devices.