26 research outputs found
Business Case and Technology Analysis for 5G Low Latency Applications
A large number of new consumer and industrial applications are likely to
change the classic operator's business models and provide a wide range of new
markets to enter. This article analyses the most relevant 5G use cases that
require ultra-low latency, from both technical and business perspectives. Low
latency services pose challenging requirements to the network, and to fulfill
them operators need to invest in costly changes in their network. In this
sense, it is not clear whether such investments are going to be amortized with
these new business models. In light of this, specific applications and
requirements are described and the potential market benefits for operators are
analysed. Conclusions show that operators have clear opportunities to add value
and position themselves strongly with the increasing number of services to be
provided by 5G.Comment: 18 pages, 5 figure
Impact of Correlated Failures in 5G Dual Connectivity Architectures for URLLC Applications
Achieving end-to-end ultra-reliability and resiliency in mission critical
communications is a major challenge for future wireless networks. Dual
connectivity has been proposed by 3GPP as one of the viable solutions to
fulfill the reliability requirements. However, the potential correlation in
failures occurring over different wireless links is commonly neglected in
current network design approaches. In this paper, we investigate the impact of
realistic correlation among different wireless links on end-to-end reliability
for two selected architectures from 3GPP. In ultra-reliable use-cases, we show
that even small values of correlation can increase the end-to-end error rate by
orders of magnitude. This may suggest alternative feasible architecture designs
and paves the way towards serving ultra-reliable communications in 5G networks.Comment: Accepted in 2019 IEEE Globecom Workshops (GC Wkshps
Performance Comparison of Schedulers in MmWave Communication using NS-3
Millimeter-wave (mmWave) has proven to provide the bandwidth requirement for the new radio (NR) on 5G. MmWave has been developed as a new technology to support enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and ultra-reliable low latency communication (URLLC). Since using a high frequency, mmWave also has some disadvantages that could not be avoided, such as small coverage, high signal attenuation, limited against some obstacles, and sensitive to the influence of signal quality. This paper discusses the effect of signal quality on 5G performance using mmWave while sending or receiving packet data by using three types of the scheduler, such as Round Robin, Proportional Fairness, and Max Rate scheduler. Signal quality will impact the value of modulation and coding scheme (MCS) that will be used. Our experiments using NS-3 based on the scenario showed that in the same location and number of UEs, performance throughput using Round Robin and Max Rate with excellent signal strength could reach the maximum throughput. The use of Proportional Fairness could lead only to reaching 50% of the maximum throughput. On the other hand, the use of the Proportional Fairness scheduler causes the weak signal to be unstable. Using Round Robin scheduler, the throughput is more stable. Different from the result using the Max Rate scheduler, the UE with the best signal quality compared to other UEs, was the only UE that get the resources allocation
Deep Learning for Channel Estimation and Signal Detection in OFDM-Based Communication Systems
The goal of 6G communication networks requires higher transmission speeds, tremendous data processing, and low-latency communication. Orthogonal frequency-division multiplexing (OFDM), which is widely utilized in 5G communication systems, may be a viable alternative for 6G. It significantly reduces inter symbol interference (ISI) in the frequency-selective fading environment. Channel estimation is critical in OFDM to optimize system performance. Deep learning has been employed as an appealing alternative for channel estimation and signal detection in OFDM-based communication systems due to its better potential for feature learning and representation. In this study, we examine the deep neural network (DNN) layers created from long-short term memory (LSTM) for detecting the signals by learning the received signal as well as channel information. We investigate the performance of the system under various conditions. The simulation results show that the signal bit error (SER) is equivalent to and better than that of the minimum mean squared error (MMSE) and least square (LS) methods
Characteristics for verifying 5G applications in production
5G offers the manufacturing industry a wireless, fast and secure transmission technology with high range, low latency and the ability to connect a large number of devices. Existing transmission technologies are reaching their limits due to the increasing number of networked devices and high demands on reliability, data volume, security and latency. 5G fulfills these requirements and also combines the potential and use cases of previous transmission technologies so that unwanted isolated solutions can be merged. Use cases of transmission technologies that previously required a multitude of solutions can now be realized with a single technology. However, the general literature often refers to 5G use cases that can also be realized over cables in particular. In this paper, a literature review presents the current state of research on the various 5G application scenarios in production . Furthermore, concrete characteristics of 5G use cases are identified and assigned to the identified application scenarios. The goal is to verify the identified 5G use cases and to work out their 5G relevance in order to be able to concretely differentiate them from already existing Industrie 4.0 applications
Economic Feasibility of Wireless Sensor Network-Based Service Provision in a Duopoly Setting with a Monopolist Operator
[EN] We analyze the feasibility of providing Wireless Sensor Network-data-based services in an
Internet of Things scenario from an economical point of view. The scenario has two competing service
providers with their own private sensor networks, a network operator and final users. The scenario
is analyzed as two games using game theory. In the first game, sensors decide to subscribe or not
to the network operator to upload the collected sensing-data, based on a utility function related to
the mean service time and the price charged by the operator. In the second game, users decide to
subscribe or not to the sensor-data-based service of the service providers based on a Logit discrete
choice model related to the quality of the data collected and the subscription price. The sinks and
users subscription stages are analyzed using population games and discrete choice models, while
network operator and service providers pricing stages are analyzed using optimization and Nash
equilibrium concepts respectively. The model is shown feasible from an economic point of view for
all the actors if there are enough interested final users and opens the possibility of developing more
efficient models with different types of services.This work was supported by the Spanish Ministry of Economy and Competitiveness through projects TIN2013-47272-C2-1-R and (co-supported by the European Social Fund) BES-2014-068998.Sanchis-Cano, Á.; Romero-Chavarro, JC.; Sacoto-Cabrera, E.; Guijarro, L. (2017). Economic Feasibility of Wireless Sensor Network-Based Service Provision in a Duopoly Setting with a Monopolist Operator. Sensors. 17 (12)(2727):1-22. https://doi.org/10.3390/s17122727S12217 (12)272
5G Smart and innovative Healthcare services: opportunities, challenges and prospective solutions
Due to its abilities to boost productivity, reduce costs and enhance user experiences, smart healthcare is widely recognised as a potential solution to reduce pressures on existing health systems. Since the new era of 5G will unite enhanced connectivity, improved cloud-based storage and interconnection of an array of devices and services, a massive boost in the digital transformation of healthcare is expected. In this transformation process, healthcare services such as medical diagnosis, treatment and remote surgery will be facilitated by a range of technologies such as Internet of Things, Robotics and Artificial Intelligence, among others, that will advance further under 5G. Moreover, real-time health services will become a reality and will offer people with quality care and improved experiences. On the other hand, different challenges can hinder the proliferation of 5G smart and innovative healthcare solutions, including security and heterogeneous devices. This chapter presents how 5G will boost digital transformation of healthcare through delivery and consumption of smart and innovative healthcare services, while probing into key hurdles in the process as well as prospective solutions
A Survey on the Security and the Evolution of Osmotic and Catalytic Computing for 5G Networks
The 5G networks have the capability to provide high compatibility for the new
applications, industries, and business models. These networks can tremendously
improve the quality of life by enabling various use cases that require high
data-rate, low latency, and continuous connectivity for applications pertaining
to eHealth, automatic vehicles, smart cities, smart grid, and the Internet of
Things (IoT). However, these applications need secure servicing as well as
resource policing for effective network formations. There have been a lot of
studies, which emphasized the security aspects of 5G networks while focusing
only on the adaptability features of these networks. However, there is a gap in
the literature which particularly needs to follow recent computing paradigms as
alternative mechanisms for the enhancement of security. To cover this, a
detailed description of the security for the 5G networks is presented in this
article along with the discussions on the evolution of osmotic and catalytic
computing-based security modules. The taxonomy on the basis of security
requirements is presented, which also includes the comparison of the existing
state-of-the-art solutions. This article also provides a security model,
"CATMOSIS", which idealizes the incorporation of security features on the basis
of catalytic and osmotic computing in the 5G networks. Finally, various
security challenges and open issues are discussed to emphasize the works to
follow in this direction of research.Comment: 34 pages, 7 tables, 7 figures, Published In 5G Enabled Secure
Wireless Networks, pp. 69-102. Springer, Cham, 201