Special Issue "Emerging Topics in Wireless Communications for Future Smart Cities"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information and Communications Technology".

Deadline for manuscript submissions: closed (30 October 2019).

Special Issue Editors

Dr. Soufiene Djahel
E-Mail Website
Guest Editor
School of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, Manchester M15 6BH, UK
Interests: Intelligent transportation systems; wireless networking; network security; connected and autonomous vehicles
Dr. Celimuge Wu
E-Mail Website
Guest Editor
Department of Computer and Network Engineering, The University of Electro-Communications, Tokyo182-8585, Japan
Interests: Ad hoc networks; sensor networks; intelligent transport systems; communication protocols; IoT; big data
Dr. Yassine Hadjadj-Aoul
E-Mail Website
Guest Editor
ESIR, University of Rennes 1, 35042 Rennes CEDEX, France
Interests: quality of service and quality of experience; wireless and mobile networks; future networks; performance evaluation
Prof. Dr. Claudio Pallazi
E-Mail Website
Guest Editor
Dipartimento di Matematica, Università degli Studi di Padova, 35131 Padova, Italy
Interests: Wireless networks; web squared; online entertainment; mobile applications
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The concept of the smart city has emerged in recent years as a futuristic vision of cities, building sustainable ecosystems while promoting citizen welfare and economic growth. A smart city fosters the use of advanced ubiquitous ICT technologies to smartly and efficiently monitor and manage its critical assets such as energy, water, and transportation infrastructure. Building smart cities, however, strongly depends on various enabling advanced technologies, such as wireless sensing technologies, the Internet of Things (IoT), 5G networks, connected vehicles, the cloud, etc. The myriad of novel applications expected to emerge in smart cities introduces unique challenges for the wireless communication technologies underpinning them in terms of scalability, robustness, security, energy-efficiency, and latency requirements. Moreover, the heterogeneity of the used wireless devices, ranging from tiny wearable sensors and IoT devices to connected vehicles, in terms of processing and storage capabilities, energy supply, and transmission rate and range add further complications to the above challenges.

This Special Issue is, therefore, soliciting original contributions presenting solutions, models, prototypes, and novel applications in relation to the above technologies and their associated challenges.

This Special Issue will also provide a great opportunity for authors of selected papers presented at the IFIP Wireless Days 2019 conference to submit extended versions of their manuscripts to a broader audience.

Dr. Soufiene Djahel
Dr. Celimuge Wu
Dr. Yassine Hadjadj-Aoul
Prof. Dr. Claudio Pallazi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Wireless communication and networking
  • Wireless models and simulation
  • Wireless Sensing technologies and their applications in health, transport, and energy
  • Internet of Things (IoT)
  • Connected and autonomous vehicles on land and water and in the sky
  • Mobile networking and computing
  • Security and privacy issues in wireless and mobile networks

Published Papers (4 papers)

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Research

Open AccessArticle
Cooperative Smartphone Relay Selection Based on Fair Power Utilization for Network Coverage Extension
Information 2019, 10(12), 381; https://doi.org/10.3390/info10120381 - 03 Dec 2019
Abstract
This paper presents a relay selection algorithm based on fair battery power utilization for extending mobile network coverage and capacity by using a cooperative communication strategy where mobile devices can be utilized as relays. Cooperation improves the network performance for mobile terminals, either [...] Read more.
This paper presents a relay selection algorithm based on fair battery power utilization for extending mobile network coverage and capacity by using a cooperative communication strategy where mobile devices can be utilized as relays. Cooperation improves the network performance for mobile terminals, either by providing access to out-of-range devices or by facilitating multi-path network access to connected devices. In this work, we assume that all mobile devices can benefit from using other mobile devices as relays and investigate the fairness of relay selection algorithms. We point out that signal strength based relay selection inevitably leads to unfair relay selection and devise a new algorithm that is based on fair utilization of power resources on mobile devices. We call this algorithm Credit based Fair Relay Selection (CF-RS) and in this paper show through simulation that the algorithm results in fair battery power utilization, while providing similar data rates compared with traditional approaches. We then extend the solution to demonstrate that adding incentives for relay operation adds clear value for mobile devices in the case they require relay service. Typically, mobile devices represent self-interested users who are reluctant to cooperate with other network users, mainly due to the cost in terms of power and network capacity. In this paper, we present an incentive based solution which provides clear mutual benefit for mobile devices and demonstrate this benefit in the simulation of symmetric and asymmetric network topologies. The CF-RS algorithm achieves the same performance in terms of achievable data rate, Jain’s fairness index and utility of end devices in both symmetric and asymmetric network configurations. Full article
(This article belongs to the Special Issue Emerging Topics in Wireless Communications for Future Smart Cities)
Open AccessFeature PaperArticle
A Comparison of Reinforcement Learning Algorithms in Fairness-Oriented OFDMA Schedulers
Information 2019, 10(10), 315; https://doi.org/10.3390/info10100315 - 14 Oct 2019
Abstract
Due to large-scale control problems in 5G access networks, the complexity of radio resource management is expected to increase significantly. Reinforcement learning is seen as a promising solution that can enable intelligent decision-making and reduce the complexity of different optimization problems for radio [...] Read more.
Due to large-scale control problems in 5G access networks, the complexity of radio resource management is expected to increase significantly. Reinforcement learning is seen as a promising solution that can enable intelligent decision-making and reduce the complexity of different optimization problems for radio resource management. The packet scheduler is an important entity of radio resource management that allocates users’ data packets in the frequency domain according to the implemented scheduling rule. In this context, by making use of reinforcement learning, we could actually determine, in each state, the most suitable scheduling rule to be employed that could improve the quality of service provisioning. In this paper, we propose a reinforcement learning-based framework to solve scheduling problems with the main focus on meeting the user fairness requirements. This framework makes use of feed forward neural networks to map momentary states to proper parameterization decisions for the proportional fair scheduler. The simulation results show that our reinforcement learning framework outperforms the conventional adaptive schedulers oriented on fairness objective. Discussions are also raised to determine the best reinforcement learning algorithm to be implemented in the proposed framework based on various scheduler settings. Full article
(This article belongs to the Special Issue Emerging Topics in Wireless Communications for Future Smart Cities)
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Open AccessArticle
Delay-Tolerant Sequential Decision Making for Task Offloading in Mobile Edge Computing Environments
Information 2019, 10(10), 312; https://doi.org/10.3390/info10100312 - 12 Oct 2019
Abstract
In recent years, there has been a significant increase in the use of mobile devices and their applications. Meanwhile, cloud computing has been considered as the latest generation of computing infrastructure. There has also been a transformation in cloud computing ideas and their [...] Read more.
In recent years, there has been a significant increase in the use of mobile devices and their applications. Meanwhile, cloud computing has been considered as the latest generation of computing infrastructure. There has also been a transformation in cloud computing ideas and their implementation so as to meet the demand for the latest applications. mobile edge computing (MEC) is a computing paradigm that provides cloud services near to the users at the edge of the network. Given the movement of mobile nodes between different MEC servers, the main aim would be the connection to the best server and at the right time in terms of the load of the server in order to optimize the quality of service (QoS) of the mobile nodes. We tackle the offloading decision making problem by adopting the principles of optimal stopping theory (OST) to minimize the execution delay in a sequential decision manner. A performance evaluation is provided using real world data sets with baseline deterministic and stochastic offloading models. The results show that our approach significantly minimizes the execution delay for task execution and the results are closer to the optimal solution than other offloading methods. Full article
(This article belongs to the Special Issue Emerging Topics in Wireless Communications for Future Smart Cities)
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Open AccessArticle
Clustering Algorithms and Validation Indices for a Wide mmWave Spectrum
Information 2019, 10(9), 287; https://doi.org/10.3390/info10090287 - 19 Sep 2019
Abstract
Radio channel propagation models for the millimeter wave (mmWave) spectrum are extremely important for planning future 5G wireless communication systems. Transmitted radio signals are received as clusters of multipath rays. Identifying these clusters provides better spatial and temporal characteristics of the mmWave channel. [...] Read more.
Radio channel propagation models for the millimeter wave (mmWave) spectrum are extremely important for planning future 5G wireless communication systems. Transmitted radio signals are received as clusters of multipath rays. Identifying these clusters provides better spatial and temporal characteristics of the mmWave channel. This paper deals with the clustering process and its validation across a wide range of frequencies in the mmWave spectrum below 100 GHz. By way of simulations, we show that in outdoor communication scenarios clustering of received rays is influenced by the frequency of the transmitted signal. This demonstrates the sparse characteristic of the mmWave spectrum (i.e., we obtain a lower number of rays at the receiver for the same urban scenario). We use the well-known k-means clustering algorithm to group arriving rays at the receiver. The accuracy of this partitioning is studied with both cluster validity indices (CVIs) and score fusion techniques. Finally, we analyze how the clustering solution changes with narrower-beam antennas, and we provide a comparison of the cluster characteristics for different types of antennas. Full article
(This article belongs to the Special Issue Emerging Topics in Wireless Communications for Future Smart Cities)
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