Mobile Broadband Research Articles

Primary Health Care Data Management System for Pregnancy Women

Abstract: In this design a Primary Health Care data operation for pregnant women, an Android operation is developed. The design is grounded on the features of, Data Analysis and Data operation. This design is grounded on an Android operation for mobile druggies for data operation. All druggies (Croakers, Staff & Case) will have their Unique (USER_ID) and word for login into the operation. By using theUSER_ID (Croakers, Staff & Case), the croakers and staff can manage the Case data in the database and cases can view their gestation report to their consult croaker (particular) or for their view. Background: Increasing portable possession, practicality and access to mobile-broad band web services has triggered growing interest to harness the potential of portable technology to boost health services in low-income settings. This project aimed toward coming up with Associate in Primary health care data management system that assists midlevel physicians to supply higher maternal health care services by automating the info assortment and decision-making method. It have check yearly for regular check – ups. when the patient needs to appoint a croaker, they can login to the case login and fix the niche and the croaker can fix whether they available. This paper describes the event method and technical aspects of the system thought

Modification and Validation of an mHealth App Quality Assessment Methodology for International Use: Cross-sectional and eDelphi Studies.

BackgroundOver 325,000 mobile health (mHealth) apps are available to download across various app stores. However, quality assurance in this field of medicine remains relatively undefined. Globally, around 84% of the population have access to mobile broadband networks. Given the potential for mHealth app use in health promotion and disease prevention, their role in patient care worldwide is ever apparent. Quality assurance regulations both nationally and internationally will take time to develop. Frameworks such as the Mobile App Rating Scale and Enlight Suite have demonstrated potential for use in the interim. However, these frameworks require adaptation to be suitable for international use.ObjectiveThis study aims to modify the Enlight Suite, a comprehensive app quality assessment methodology, to improve its applicability internationally and to assess the preliminary validity and reliability of this modified tool in practice.MethodsA two-round Delphi study involving 7 international mHealth experts with varied backgrounds in health, technology, and clinical psychology was conducted to modify the Enlight Suite for international use and to improve its content validity. The Modified Enlight Suite (MES) was then used by 800 health care professionals and health care students in Ireland to assess a COVID-19 tracker app in an online survey. The reliability of the MES was assessed using Cronbach alpha, while the construct validity was evaluated using confirmatory factor analysis.ResultsThe final version of the MES has 7 sections with 32 evaluating items. Of these items, 5 were novel and based on consensus for inclusion by Delphi panel members. The MES has satisfactory reliability with a Cronbach alpha score of .925. The subscales also demonstrated acceptable internal consistency. Similarly, the confirmatory factor analysis demonstrated a positive and significant factor loading for all 32 items in the MES with a modestly acceptable model fit, thus indicating the construct validity of the MES.ConclusionsThe Enlight Suite was modified to improve its international relevance to app quality assessment by introducing new items relating to cultural appropriateness, accessibility, and readability of mHealth app content. This study indicates both the reliability and validity of the MES for assessing the quality of mHealth apps in a high-income country, with further studies being planned to extrapolate these findings to low- and middle-income countries.

A tenant-driven slicing enforcement scheme based on Pervasive Intelligence in the Radio Access Network

In Beyond 5G mobile networks, the network slicing paradigm offers the possibility of sharing the network infrastructure among different tenants: the tenant declares communication service requirements and the Infrastructure Provider configures (potentially on-demand) the corresponding network slice instances. The management of network slicing in the core network has been deeply investigated in the current scientific literature. On the contrary, handling network slicing in the Radio Access Network still represents an open and very challenging research topic, mostly due to the unpredictable variability of the wireless channel, network dynamics and heterogeneity, slice isolation, as well as different Quality of Service requirements of various services. In order to achieve an important step forward in this direction, this paper proposes a tenant-driven Radio Access Network slicing enforcement scheme based on Pervasive Intelligence. The proposed approach grounds its roots in the Pay for What You Get paradigm: it promises to avoid the radio resources over-provisioning while saving bandwidth. To achieve these goals, Artificial Intelligence mechanisms are innovatively and pervasively integrated into some key functionalities of both Infrastructure Provider and tenants. On the one hand, the Infrastructure Provider exploits a Deep Learning scheme (i.e., convolutional autoencoder) to compress the information on network resources and connectivity and share the actual (but hidden through compression) network status with the tenants. On the other hand, each tenant implements a Deep Reinforcement Learning algorithm (i.e., Deep Deterministic Policy Gradient) to dynamically adapt bandwidth requests according to its own users’ requirements. The outcomes of this algorithm are then used by the Infrastructure Provider to effectively enforce network slicing at the Radio Access Network level. Computer simulations investigate the proposed approach in a realistic scenario, which jointly embraces enhanced Mobile BroadBand, Advanced Driver Assistant Systems, and best-effort applications. Obtained results demonstrate the effectiveness of the proposal against conventional resource allocation methods.

RIS-Assisted Network Slicing Resource Optimization Algorithm for Coexistence of eMBB and URLLC

Enhanced mobile broadband (eMBB) and Ultra-Reliable and Low-Latency Communications (URLLC) are the two main services in the fifth-generation mobile network. URLLC services have stringent latency and reliability requirements, while eMBB services are designed to provide extremely high data rates for content delivery. The differentiated Quality of Service (QoS) requirements of the two services make their coexistence on the same bandwidth resources a challenging issue. To meet this challenge, we introduce reconfigurable intelligent surface (RIS) technology to assist in solving the resource allocation problem. The problem is formulated as two optimization problems. For the eMBB allocation problem, we jointly optimize the resource block allocation, power allocation, and RIS phase shift matrix and propose a two-stage alternating iterative algorithm to maximize the total traversal capacity of eMBB users. For the URLLC allocation problem, we maximize the URLLC packet reception rate and minimize the amount of eMBB rate loss while ensuring the quality of service for eMBB and URLLC. A heuristic URLLC allocation algorithm based on pre-configured RIS is proposed. Simulation results show that the proposed algorithm can meet the strict delay requirements of URLLC even when the URLLC packet reception rate is nearly 95.5%. Meanwhile, the total loss rate of eMBB service caused by the reuse of URLLC service is less than 6%. Thus, the applicability of the proposed solution to the coexistence problem is demonstrated.

Physical layer enhancements in 5G‐NR for direct access via satellite systems

SummaryAmong the several features and capabilities introduced by every new 3GPP release on 5G cellular systems, the latest Release 17 will be remembered as the first that specifies a set of enhancements and adaptations to support mobile broadband services via satellite direct access. Specifically focused on the necessary physical layer mechanism and procedure modifications, this paper will present in detail the 3GPP work about the inclusion of satellite systems in 5G networks.

New determinants of spectrum price in a 5G world

ABSTRACT The theoretical models presented in the article establish the possibility that reduced congestion in unlicenced bands can reduce the profits of telecommunications operators, and consequently, depress spectrum prices. Further, certain modes of deploying licenced and unlicenced spectrum bands to provide services may render competitive dynamics uncertain, unpredictable, and unstable. Finally, the advent of Content and Application Providers (CAPs) providing substitutes or complements to traditional telecommunications services can also reduce operator profits. On the other hand, benign impacts on operator profits and spectrum prices cannot be ruled out. Given these possibilities, an empirical analysis is carried out to examine the impact of the participation of CAPs and the reduced congestion in unlicenced networks on spectrum prices. The variables of VOIP fixed-line subscribtions and mobile broadband density are used as proxies for the increased usage of unlicenced spectrum and the entry of CAPs as providers of substitutes and complements. These variables are consistently significant in our analysis indicating that there are indeed new drivers determining spectrum prices. Policy implications of the findings are enumerated.

Improved Belief Propagation List Decoding for Polar Codes

Polar codes have become the channel coding scheme for control channel of enhanced mobile broadband in the 5G communication systems. Belief propagation (BP) decoding of polar codes has advantages of low decoding latency and high parallelism but achieves worse bit error ratio (BER) performance compared with the successive cancellation list (SCL) decoding scheme. In this paper, an improved BP list (IBPL) decoding algorithm is proposed with comparable BER performance to SCL algoritm. Firstly, the optimal permuted factor graph is analyzed for polar codes, which improves the performance of the BP decoder without path extension. Furthermore, based on the optimal graph, the bit metric and decoding path metric are proposed to extend and prune the decoding path. The proposed IBPL decoder is focused on not only the permutation of polar codes but also the reliabilities of decoded codewords during each iteration of BP decoding, which has a more accurate decoding path list. The simulation results show that the proposed IBPL decoder improves the BER performance compared with the original BP decoder significantly, and can approach the performance of the SCL decoder at low signal to noise ratio regions.

Guest Editorial: Artificial Intelligence Enabled Internet of UAVs for Emergency Communications

The unprecedented demands for high-quality and ubiquitous wireless services impose enormous challenges to the existing cellular networks to meet the challenges of connectivity, reliability, etc. The targeted applications in designing the beyond fifth generation (BSG) systems include enhanced mobile broadband (eMBB), ultra-reliable, low latency communications (URLLC), and massive machine-type communications (mMTC). Recently to meet those diverse requirements, the latest technologies like millimeter wave (mmWave) communications, ultra-dense networks (UDN), and massive multiple-input and multiple-output (MIMO) are under consideration. Moreover, we also require an evolution in an architectural platform that performs joint communications, sensing, localization, and computing while ensuring ultra-high throughput, ultra-low latency, and ultra-high reliability for real-time emergency communications.

Coordinated Resource Allocations for eMBB and URLLC in 5G Communication Networks

Enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communications (URLLC) are the two core services of the emerging fifth-generation (5G) systems. URLLC services require lower latency and high reliability, whereas eMBB services expect maximum data rates. Since 5G new radio (NR) aims to support heterogeneous services, the 3rd generation partnership project (3GPP) supports a highly flexible frame structure by introducing mixed numerology and mini-slot approaches. In these systems, the time slot is further divided into mini-slots. The coexistence of these two heterogeneous services leads to a challenging resource allocation problem. In this paper, we study the joint resource allocation problem of eMBB and URLLC schedulers to maximize the minimum expected achieved rate (MEAR) of eMBB users while satisfying URLLC users’ quality of service (QoS) constraints. The resource allocation of eMBB traffic occurs at time slot boundaries. In contrast, URLLC traffic is overlapped at the mini-slot timescale by adopting the non-orthogonal multiple access (NOMA) superposition technique. The suitable pairs of eMBB, URLLC users are evaluated using the one-one matching theory by inculcating fairness among eMBB users while satisfying the QoS parameters of URLCC users. The significance of the proposed approach over the baseline approaches is evaluated through numerical simulations in terms of the MEAR, mixed numerologies, and fairness scores among eMBB users.

Evolution Toward 6G Multi-Band Wireless Networks: A Resource Management Perspective

In this article, we first present the vision, key performance indicators, key enabling techniques (KETs), and services of 6G wireless networks. Then, we highlight a series of general resource management (RM) challenges as well as unique RM challenges corresponding to each KET. The unique RM challenges in 6G necessitate the transformation of existing optimization-based solutions to artificial intelligence/machine learning-empowered solutions. In the sequel, we formulate a joint network selection and subchannel allocation problem for 6G multi-band network that provides both further enhanced mobile broadband (FeMBB) and extreme ultra reliable low latency communication (eURLLC) services to the terrestrial and aerial users. Our solution highlights the efficacy of multi-band network and demonstrates the robustness of dueling deep Q-network in obtaining efficient RM solution with faster convergence rate compared to deep Q-network and double deep Q-network algorithms.

5G-Enabled Medical Data Transmission in Mobile Hospital Systems

As one of the healthcare development trends, mobile hospital systems nowadays need more advanced means of treatment and diagnosis and require higher data transmission speed and capacity with lower latency. With its ability to simultaneously support a variety of services in a wide range of application scenarios using network slicing technique, the emerging fifth generation communication system (5G) is expected to offer significant communication performances, including higher throughput, higher mobility, higher connection density, higher transmission reliability with lower latency than the current fourth generation (4G). Hence, 5G can serve as an effective transmission means to meet the modern mobile hospital systems requirements. This article proposes a 5G network slicing-based mobile hospital system where two types of slices, namely, enhanced mobile broadband (eMBB) slice and ultrareliable and low-latency communications (uRLLC) slice, are dedicated to the medical data. We propose an optimization method to maximize the throughput of the medical data assigned to the eMBB slice. We also propose a resource allocation algorithm for very high transmission reliability with very low latency of the medical data assigned to the uRLLC slice. Simulation results indicate that our proposed approach can effectively meet mobile hospital systems requirements for data transmission throughput, reliability, and latency from remote sites to hospital centers.

An intelligent energy efficient handover mechanism with adaptive discontinuous reception in next generation telecommunication networks

Long Term Evolution (LTE) and LTE-Advanced (A) networks have been introduced to accommodate the User Equipment (UEs) that supports high complex technologies such as OFDM, SC-FDMA, MIMO. Recently, 3GPP presented 5G technology to meet the performance requirement of the International Mobile Telecommunication (IMT)-2020. It supports three specific services like Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communication (URLLC), massive Machine Type Communication (mMTC). To increase the capacity of the network, 5G will deploy an ultra-dense network in the metro area. It fulfils the spectral efficiency requirement but at the same time increases handover rate. Due to handover, the power consumption of UEs may increase dramatically. To overcome this issue, LTE-A network adopts Discontinuous Reception (DRX) to conserve battery life of UE. 5G networks will also apply evolved variations of this scheme. In general, DRX is composed of some parameters and these need to be optimized during mobility. This paper presents a method for preservation of the battery life of UEs during mobility. The proposed mechanism comprises of three parts. In the first part, Part 1, the operation of normal DRX during mobility is explored. The next parts, Part 2 and Part 3, utilize the machine learning-based methods for the pre-prediction of Target eNB (TeNB) and provide ranks to the UEs during handover. Further, DRX parameters are adjusted according to the dynamic behaviour of the network. Handover latency, end-to-end delay is improved by 20% and 55%, respectively as compared to the conventional scheme. Further, machine learning based (Part 2) and dynamic adjustment of DRX parameters (Part 3) contribute to enhance the power saving factor by maximum up to 85%, and 33% as compared to state of art mechanism.

A Service-Aware Latency-Relaxed uRLLC Multiplexing Strategy within eMBB Traffic for Hyperloop Communications

The train-to-ground communications for Hyperloop encounter numerous challenges compared to the previous systems as a result of ultrahigh velocity, metal confined tube, severe penetration attenuation, frequent handover, etc. Ultrareliable low latency communication (uRLLC) services are extremely pivotal to the operation of Hyperloops since they are responsible for the transmission of safety-related messages like train control system (TCS) information. Furthermore, the sporadic generated uRLLC traffic is strictly latency-sensitive and requires stringent transmission reliability, which is usually realized by multiplexing with the enhanced mobile broadband (eMBB) traffic when coexisting with heterogeneous traffic. Different from current multiplexing schemes which handle all uRLLC traffic indiscriminately, we focus on the detailed demands of different uRLLC services for Hyperloops, including the end-to-end transmission latency and bit error rate (BER). Then, we classify the safety-related uRLLC traffic into 5 levels according to the metrics and relax the multiplexing latency properly. On this basis, an optimization problem incorporating minimizing uRLLC power and maximizing the eMBB throughput is formulated. Then, a particle swarm optimization (PSO) algorithm is proposed to cope with this nondeterministic polynomial- (NP-) hard problem. Simulation results imply that our proposed service-aware latency-relaxed concept enables a flexible multiplexing of the uRLLC traffic, and the proposed PSO algorithm can obtain the suboptimal solutions with the constraints of BER and time-frequency range, which can cater to the demands of uRLLC and improve the passengers’ in-journey communication quality of services to some degree.

Towards a self-sufficient mobile broadband seismological recording system for year-round operation in Antarctica

Abstract. Passive seismic measurements allow the study of the deeper Earth beneath the thick Antarctic ice sheet cover. Due to logistical and weather constraints, only a fraction of the area of the Antarctic ice sheet can be surveyed with long-term or temporary sensors. A fundamental limitation is the power supply and operation of the instruments during the polar winter. In addition, there is only a limited time window during the field seasons to deploy the stations over the year. Here we present a rapidly and simple deployable self-sufficient mobile seismic station concept. The station consists of different energy supply modules aligned according to the survey needs, measuring duration, and survey aim. Parts of the concept are integrated into an already existing pool of mobile stations and in the seismological network of the geophysical observatory at Neumayer III Station. Other concepts and features are still under development. The overall goal is to use these temporary mobile arrays in regions where little is known about local and regional tectonic earthquake activity.

Broadband Mobile Applications’ Adoption by SMEs in Taiwan—A Multi-Perspective Study of Determinants

The purpose of this study is to explore what determinants affect small and medium enterprises regarding the adoption of broadband mobile applications. Today, broadband mobile applications are changing the business landscape rapidly, which presents a vital issue for enterprises to understand and tackle. Both qualitative and quantitative methods were applied in this study in order to analyze the issues enterprises may face with broadband mobile applications. Qualitatively, a preliminary study was conducted based on a review of literature to explore the factors that impact small and medium enterprises. Quantitatively, Structural Equation Modeling and AMOS were deployed to further examine the potential factors. As broadband mobile applications are mostly installed in the personal mobile device and operated by individuals, this study integrated the perspective of internal users along with the Technology-Organization-Environment framework to develop an ITOE research model to provide a more comprehensive view on the determinants and factors. The practicality and feasibility of the ITOE research model were then verified by the study results through the fifteen determinants identified. Based on the findings, implications and future research directions are proposed.

Proactive Traffic Offloading in Dynamic Integrated Multisatellite Terrestrial Networks

The integration between the satellite network and the terrestrial network will play a key role in the upcoming sixth-generation (6G) of mobile cellular networks thanks to the wide coverage and bandwidth offered by satellite networks. To leverage this integration, we propose a proactive traffic offloading scheme in an integrated multi-satellite terrestrial network (IMSTN) that considers the future networks’ heterogeneity and predicts their variability. Our proposed offloading scheme hinges on traffic prediction to answer the stringent requirements of data-rate, latency and reliability imposed by heterogeneous and coexisting services and traffic namely enhanced mobile broadband (eMBB), massive machine-type communications (mMTC) and ultra-reliable low latency communication (URLLC). However, the fulfilment of these requirements during offloading in dynamic IMSTN comes at the expense of significant energy consumption and introduces inherently supplementary latency. Therefore, our offloading scheme aims to balance the fundamental trade-offs first between energy consumption and the achievable data-rate and second between energy consumption and latency while meeting the respective needs of the present traffic. Our findings prove the importance of the cooperation between the multi-satellite network and the terrestrial network conditioned by traffic prediction to enhance the performance of IMTSN in terms of latency and energy consumption.

Network Operator-Provided 5G Streaming Media and Future Broadcast Services

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Beyond the spectral efficiency and throughput improvement for enhanced mobile broadband (eMBB), 5G brings many new features targeting vertical applications. To leverage the new 5G features and capabilities for media distribution, 5G offers the 5G Media Streaming Architecture (5GMSA), which supports a full set of collaboration scenarios between third-party content providers and mobile network operators (MNOs) with various degrees of integration adapted to the over-the-top (OTT) ecosystem. While the first version of 5GMSA focuses on media delivery over unicast, multicast/broadcast in 5G is one of the key new features currently specified by 3GPP and expected for Release 17. Integration of 5G multicast/broadcast capabilities within 5GMSA is essential to scale up the network capacity for linear contents. With the publication of Digital Video Broadcast-I (DVB-I) in 2020, DVB allows for the delivery of linear television services to internet-connected devices over broadband and broadcast networks. As an access-independent service layer, DVB-I becomes a strong candidate for providing a converging service layer for 5G. This article explores the growing capabilities offered by the 5GMSA, how the multicast/broadcast capabilities will be integrated, and how it will enable the delivery of DVB-I services</i> .

Dynamic SDN-Based Radio Access Network Slicing With Deep Reinforcement Learning for URLLC and eMBB Services

Radio access network (RAN) slicing is a key technology that enables 5G network to support heterogeneous requirements of generic services, namely ultra-reliable low-latency communication (URLLC) and enhanced mobile broadband (eMBB). In this paper, we propose a two time-scales RAN slicing mechanism to optimize the performance of URLLC and eMBB services. In a large time-scale, an SDN controller allocates radio resources to gNodeBs according to the requirements of the eMBB and URLLC services. In a short time-scale, each gNodeB allocates its available resources to its end-users and requests, if needed, additional resources from adjacent gNodeBs. We formulate this problem as a non-linear binary program and prove its NP-hardness. Next, for each time-scale, we model the problem as a Markov decision process (MDP), where the large-time scale is modeled as a single agent MDP whereas the shorter time-scale is modeled as a multi-agent MDP. We leverage the exponential-weight algorithm for exploration and exploitation (EXP3) to solve the single-agent MDP of the large time-scale MDP and the multi-agent deep Q-learning (DQL) algorithm to solve the multi-agent MDP of the short time-scale resource allocation. Extensive simulations show that our approach is efficient under different network parameters configuration and it outperforms recent benchmark solutions.

Türkiye’de bilişim teknolojileri kullanımının ÇKKV yöntemleriyle incelenmesi 2014-2021 dönemi

Electronics and communication sector investments, which have increased with the decreasing infrastructure costs in recent years in Turkey, Information Communication Technologies (ICT) is becoming widespread. According to the data of the Turkish Statistical Institute (TUIK) for 2021, the number of households with internet access has increased to 92%. The development of information and communication technologies provides social transformation by affecting the development speed of countries. Despite the regional differences in Turkey, the development of the informatics infrastructure has shown great improvement. In this study, with Multi-Criteria Decision Making Methods, a model that can measure the development performance of the regions in Turkey towards the use of information technologies at the statistical region level has been examined. In the model created, PSI (Preference Selection Index) was used to weight the criteria, and WEDBA (Weighted Euclidean Distance Based Approach) methods were used to evaluate the ICT usage level of the regions. The data in the study was taken from the TUIK database and is based on the Household Information Technologies (IT) Usage Survey of 2021 carried out by the institution. The criteria for the use of information and communication technologies consist of internet access, broadband, fixed broadband, mobile broadband, regular internet usage and internet usage. According to the findings of the study, it can be said that while the most important criterion was internet access in 2014, it was mobile bandwidth in 2021. Within the scope of the study, Istanbul and East Marmara regions showed the best performance. In addition, it was concluded that the Southeastern Anatolia region, which showed the most development, was followed by the Western Anatolia, Mediterranean, Central and Middle East Anatolia regions, and the development in other regions was less than the aforementioned regions.

Technologies Trend in the Integration of 5G Networks and IoT in Smart Cities: A Survey

This paper presents a survey of 5G and suitable concerns in the planning and development of communication model infrastructure for the deployment of Smart Cities, also called Intelligent Cities or Digital Cities. The paper first provides an overview of 5G technology, its evolution, and how it revolutionised worldwide communication. The drivers of 5G, such as enhanced mobile broadband (eMBB), ultra-reliable low-latency communication (URLLC), and massive machine-type communication (mMTC), will enable 5G to deliver higher speeds compared to the previous 4G and 3G generations and enable service providers to provide massive bandwidth catering to data-intensive applications such as Smart Cities. Besides human-computer interaction (HCI), smart cities include machine type communication (MTC), in which massive communication takes place between devices and the information infrastructure through gateways. A 5G network can successfully integrate the diversified service requirements and demands of smart city applications. Smart cities require massive IoT communication built into 5G. Multiple technologies are deployed in smart cities to enhance the standard of living for people. Citizens are provided with better health services, improved transportation, efficient energy, quality education, and safety and security to public. In this survey paper we present the contribution of 5G in the deployment of smart city applications and its pillars that play a very important role in the construction of smart cities. Better healthcare systems have been developed that integrate new communication technologies and conventional health care procedures. One of the vital segments of a smart city is its transportation system, which affects the environs and health of people. The energy efficiency of smart cities can be greatly improved by 5G by using smart appliances. Smart metres deliver real-time data about the energy consumed. Users can save energy and money. Similarly, it can assist the water board team by giving real-time statistics regarding water consumption to the consumers. Almost all the smart city infrastructure mentioned above has different requirements for delay, movement, dependability, and resilience of the network. Incorporating diverse applications into a communication network is a difficult chore. 5G has been designed for forward compatibility to support future amenities not known today. The paper outlines diverse requirements for smart cities based on application and technology requirements. Lastly, the supporting technologies are highlighted for the forthcoming integration of smart cities and communication infrastructure.