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) | Viewed by 36667

Special Issue Editors


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Guest Editor
Department of Computer Science, University of Huddersfield, Huddersfield HD1 3DH, UK
Interests: ITS; wireless networking; network security; connected and autonomous vehicles
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Computer and Network Engineering, Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1, Chofugaoka, Chofu-shi, Tokyo 182-8585, Japan
Interests: ad hoc networks; sensor networks; intelligent transport systems; communication protocols; IoT; big data
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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
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Dipartimento di Matematica, Università degli Studi di Padova, 35131 Padova, Italy
Interests: wireless networks; web squared; online entertainment; mobile applications
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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

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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 1600 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 (7 papers)

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Research

20 pages, 802 KiB  
Article
An Efficient Adaptive Traffic Light Control System for Urban Road Traffic Congestion Reduction in Smart Cities
by Dex R. ALEKO and Soufiene Djahel
Information 2020, 11(2), 119; https://doi.org/10.3390/info11020119 - 21 Feb 2020
Cited by 31 | Viewed by 14596
Abstract
Traffic lights have been used for decades to control and manage traffic flows crossing road intersections to increase traffic efficiency and road safety. However, relying on fixed time cycles may not be ideal in dealing with the increasing congestion level in cities. Therefore, [...] Read more.
Traffic lights have been used for decades to control and manage traffic flows crossing road intersections to increase traffic efficiency and road safety. However, relying on fixed time cycles may not be ideal in dealing with the increasing congestion level in cities. Therefore, we propose a new Adaptive Traffic Light Control System (ATLCS) to assist traffic management authorities in efficiently dealing with traffic congestion in cities. The main idea of our ATLCS consists in synchronizing a number of traffic lights controlling consecutive junctions by creating a delay between the times at which each of them switches to green in a given direction. Such a delay is dynamically updated based on the number of vehicles waiting at each junction, thereby allowing vehicles leaving the city centre to travel a long distance without stopping (i.e., minimizing the number of occurrences of the ‘stop and go’ phenomenon), which in turn reduces their travel time as well. The performance evaluation of our ATLCS has shown that the average travel time of vehicles traveling in the synchronized direction has been significantly reduced (by up to 39%) compared to non-synchronized fixed time Traffic Light Control Systems. Moreover, the overall achieved improvement across the simulated road network was 17%. Full article
(This article belongs to the Special Issue Emerging Topics in Wireless Communications for Future Smart Cities)
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13 pages, 2751 KiB  
Article
Upgrading Physical Layer of Multi-Carrier OGFDM Waveform for Improving Wireless Channel Capacity of 5G Mobile Networks and Beyond
by Mohammad R. Kadhum
Information 2020, 11(1), 35; https://doi.org/10.3390/info11010035 - 10 Jan 2020
Viewed by 3280
Abstract
On the brink of sophisticated generations of mobile starting with the fifth-generation (5G) and moving on to the future mobile technologies, the necessity for developing the wireless telecommunications waveform is extremely required. The main reason beyond this is to support the future digital [...] Read more.
On the brink of sophisticated generations of mobile starting with the fifth-generation (5G) and moving on to the future mobile technologies, the necessity for developing the wireless telecommunications waveform is extremely required. The main reason beyond this is to support the future digital lifestyle that tends principally to maximize wireless channel capacity and number of connected users. In this paper, the upgraded design of the multi-carrier orthogonal generalized frequency division multiplexing (OGFDM) that aims to enlarge the number of mobile subscribers yet sustaining each one with a high transmission capacity is presented, explored, and evaluated. The expanded multi-carrier OGFDM can improve the performance of the future wireless network that targets equally the broad sharing operation (scalability) and elevated transmission rate. From a spectrum perspective, the upgraded OGFDM can manipulate the side effect of the increased number of network subscribers on the transmission bit-rate for each frequency subcarrier. This primarily can be achieved by utilizing the developed OGFDM features, like acceleration ability, filter orthogonality, interference avoidance, subcarrier scalability, and flexible bit loading. Consequently, the introduced OGFDM can supply lower latency, better BW efficiency, higher robustness, wider sharing, and more resilient bit loading than the current waveform. To highlight the main advantages of the proposed OGFDM, the system performance is compared with the initial design of the multicarrier OGFDM side by side with the 5G waveform generalized frequency division multiplexing (GFDM). The experimented results show that by moving from both the conventional OGFDM and GFDM with 4 GHz to the advanced OGFDM with 6 GHz, the gained channel capacity is improved. Because of the efficient use of Hilbert filters and improved rate of sampling acceleration, the upgraded system can gain about 3 dB and 1.5 dB increments in relative to the OGFDM and GFDM respectively. This, as a result, can maximize mainly the overall channel capacity of the enhanced OGFDM, which in turn can raise the bit-rate of each user in the mobile network. In addition, by employing the OGFDM with the dual oversampling, the achieved channel capacity in worst transmission condition is increased to around six and twelve times relative to the OGFDM and GFDM with the normal oversampling. Furthermore, applying the promoted OGFDM with the adaptive modulation comes up with maximizing the overall channel capacity up to around 1.66 dB and 3.32 dB compared to the initial OGFDM and GFDM respectively. A MATLAB simulation is applied to evaluate the transmission performance in terms of the channel capacity and the bit error rate (BER) in an electrical back-to-back wireless transmission system. Full article
(This article belongs to the Special Issue Emerging Topics in Wireless Communications for Future Smart Cities)
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22 pages, 3250 KiB  
Article
Performance Investigation of Peak Shrinking and Interpolating the PAPR Reduction Technique for LTE-Advance and 5G Signals
by Somayeh Mohammady, Ronan Farrell, David Malone and John Dooley
Information 2020, 11(1), 20; https://doi.org/10.3390/info11010020 - 28 Dec 2019
Cited by 19 | Viewed by 5103
Abstract
Orthogonal frequency division multiplexing (OFDM) has become an indispensable part of waveform generation in wideband digital communication since its first appearance in digital audio broadcasting (DAB) in Europe in 1980s, and it is indeed in use. As has been seen, the OFDM based [...] Read more.
Orthogonal frequency division multiplexing (OFDM) has become an indispensable part of waveform generation in wideband digital communication since its first appearance in digital audio broadcasting (DAB) in Europe in 1980s, and it is indeed in use. As has been seen, the OFDM based waveforms work well with time division duplex operation in new radio (NR) systems in 5G systems, supporting delay-sensitive applications, high spectral efficiency, massive multiple input multiple output (MIMO) compatibility, and ever-larger bandwidth signals, which has demonstrated successful commercial implementation for 5G downlinks and uplinks up to 256-QAM modulation schemes. However, the OFDM waveforms suffer from high peak to average power ratio (PAPR), which is not desired by system designers as they want RF power amplifiers (PAs) to operate with high efficiency. Although NR offers some options for maintaining the efficiency and spectral demand, such as cyclic prefix based (CP-OFDM), and discrete Fourier transform spread based (DFT-S-OFDM) schemes, which have limiting effects on PAPR, the PAPR is still as high as 13 dB. This value increases when the bandwidth is increased. Moreover, in LTE-Advance and 5G systems, in order to increase the bandwidth, and data-rate, carrier aggregation technology is used which increases the PAPR the same way that bandwidth increment does; therefore, it is essential to employ PAPR reduction in signal processing stage before passing the signal to PA. In this paper, we investigate the performance of an innovative peak shrinking and interpolation (PSI) technique for reducing peak to average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) based signals at waveform generation stage. The main idea behind the PSI technique is to extract high peaks, scale them down, and interpolate them back into the signal. It is shown that PSI technique is a possible candidate for reducing PAPR without compromising on computational complexity, compatible for existing and future telecommunication systems such as 4G, 5G, and beyond. In this paper, the PSI technique is tested with variety of signals in terms of inverse fast Fourier transform (IFFT) length, type of the signal modulation, and applications. Additional work has been carried out to compare the proposed technique with other promising PAPR reduction techniques. This paper further validates the PSI technique through experimental measurement with a power amplifier (PA) test bench and achieves an adjacent channel power ratio (ACPR) of less than –55 dBc. Results showed improvement in output power of PA versus given input power, and furthermore, the error vector magnitude (EVM) of less than 1 % was achieved when comparing of the signal after and before modification by the PSI technique. Full article
(This article belongs to the Special Issue Emerging Topics in Wireless Communications for Future Smart Cities)
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20 pages, 735 KiB  
Article
Cooperative Smartphone Relay Selection Based on Fair Power Utilization for Network Coverage Extension
by Naumana Ayub and Veselin Rakocevic
Information 2019, 10(12), 381; https://doi.org/10.3390/info10120381 - 03 Dec 2019
Viewed by 2844
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)
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28 pages, 931 KiB  
Article
A Comparison of Reinforcement Learning Algorithms in Fairness-Oriented OFDMA Schedulers
by Ioan-Sorin Comșa, Sijing Zhang, Mehmet Aydin, Pierre Kuonen, Ramona Trestian and Gheorghiță Ghinea
Information 2019, 10(10), 315; https://doi.org/10.3390/info10100315 - 14 Oct 2019
Cited by 12 | Viewed by 3572
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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14 pages, 648 KiB  
Article
Delay-Tolerant Sequential Decision Making for Task Offloading in Mobile Edge Computing Environments
by Ibrahim Alghamdi, Christos Anagnostopoulos and Dimitrios P. Pezaros
Information 2019, 10(10), 312; https://doi.org/10.3390/info10100312 - 12 Oct 2019
Cited by 13 | Viewed by 3244
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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17 pages, 3598 KiB  
Article
Clustering Algorithms and Validation Indices for a Wide mmWave Spectrum
by Bogdan Antonescu, Miead Tehrani Moayyed and Stefano Basagni
Information 2019, 10(9), 287; https://doi.org/10.3390/info10090287 - 19 Sep 2019
Cited by 4 | Viewed by 2483
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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