Gateway Selection in Millimeter Wave UAV Wireless Networks Using Multi-Player Multi-Armed Bandit

Recently, unmanned aerial vehicle (UAV)-based communications gained a lot of attention due to their numerous applications, especially in rescue services in post-disaster areas where the terrestrial network is wholly malfunctioned. Multiple access/gateway UAVs are distributed to fully cover the post-disaster area as flying base stations to provide communication coverage, collect valuable information, disseminate essential instructions, etc. The access UAVs after gathering/broadcasting the necessary information should select and fly towards one of the surrounding gateways for relaying their information. In this paper, the gateway UAV selection problem is addressed. The main aim is to maximize the long-term average data rates of the UAVs relays while minimizing the flights’ battery cost, where millimeter wave links, i.e., using 30~300 GHz band, employing antenna beamforming, are used for backhauling. A tool of machine learning (ML) is exploited to address the problem as a budget-constrained multi-player multi-armed bandit (MAB) problem. In this setup, access UAVs act as the players, and the arms are the gateway UAVs, while the rewards are the average data rates of the constructed relays constrained by the battery cost of the access UAV flights. In this decentralized setting, where information is neither prior available nor exchanged among UAVs, a selfish and concurrent multi-player MAB strategy is suggested. Towards this end, three battery-aware MAB (BA-MAB) algorithms, namely upper confidence bound (UCB), Thompson sampling (TS), and the exponential weight algorithm for exploration and exploitation (EXP3), are proposed to realize gateways selection efficiently. The proposed BA-MAB-based gateway UAV selection algorithms show superior performance over approaches based on near and random selections in terms of total system rate and energy efficiency.

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5G Base Station Deployment Perspectives in Millimeter Wave Frequencies using Meta-Heuristic Algorithms

Electronics ◽

10.3390/electronics8111318 ◽

2019 ◽

Vol 8 (11) ◽

pp. 1318 ◽

Cited By ~ 4

Author(s):

Ganame ◽

Yingzhuang ◽

Ghazzai ◽

Kamissoko

Keyword(s):

Millimeter Wave ◽

Optimization Problem ◽

Heuristic Algorithms ◽

Region Of Interest ◽

Base Station ◽

Base Stations ◽

Intercell Interference ◽

High Data ◽

Data Rates ◽

5G Network

It can be predicted that the infrastructure of the existing wireless networks will not fill the requirement of the fifth generation (5G) wireless network due to the high data rates and a large number of expected traffic. Thus, a novel deployment method is crucial to satisfy 5G features. Meta-heuristic is expected to be a promising method for the complex deployment optimization problem of the 5G network. This work presents an implementation of a meta-heuristic algorithm based on swarm intelligence, to minimize the number of base stations (BSs) and optimize their placements in millimeter wave (mmWave) frequencies (e.g., 28 GHz and 38 GHz) in the context of the 5G network while satisfying user data rates requirement. Then, an iterative method is applied to remove redundant BSs. We formulate an optimization problem that takes into account multiple 5G network deployment scenarios. Further, a comparative study is conducted with the well-known simulated annealing (SA) using Monte Carlo simulations to assess the performance of the developed model. In our simulation results, we divide the region of interest into two subareas with different user distributions for different network scenarios while considering the intercell interference. The results demonstrate that the proposed approach has better network coverage with low percentage users in outage. In addition, the developed approach has less computational times to reach the desired target network quality of service (QoS).

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Miniaturized Conical Waveguide Filtenna for 5G Millimeter Wave Base Stations

2021 15th European Conference on Antennas and Propagation (EuCAP) ◽

10.23919/eucap51087.2021.9411045 ◽

2021 ◽

Author(s):

Elmine Meyer ◽

Thomas A. H. Bressner ◽

A. B. Bart Smolders ◽

Ulf Johannsen

Keyword(s):

Millimeter Wave ◽

Base Stations

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Non-Line-of-Sight Error Mitigation in Wireless Communication Systems

Advanced Engineering Forum ◽

10.4028/www.scientific.net/aef.1.173 ◽

2011 ◽

Vol 1 ◽

pp. 173-177

Author(s):

Szu Lin Su ◽

Yi Wen Su ◽

Ho Nien Shou ◽

Chien Sheng Chen

Keyword(s):

Communication Systems ◽

Hybrid Methods ◽

Mobile Station ◽

Base Stations ◽

Superior Performance ◽

Line Of Sight ◽

Time Of Arrival ◽

Angle Of Arrival ◽

Error Statistics ◽

Non Line Of Sight

When there is non-line-of-sight (NLOS) path between the mobile station (MS) and base stations (BSs), it is possible to integrate many kinds of measurements to achieve more accurate measurements of the MS location. This paper proposed hybrid methods that utilize time of arrival (TOA) at five BSs and angle of arrival (AOA) information at the serving BS to determine the MS location in NLOS environments. The methods mitigate the NLOS effect simply by the weighted sum of the intersections between five TOA circles and the AOA line without requiring priori knowledge of NLOS error statistics. Simulation results show that the proposed methods always give superior performance than Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).

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A Monte Carlo Analysis of Actual Maximum Exposure From a 5G Millimeter-Wave Base Station Antenna for EMF Compliance Assessments

Frontiers in Public Health ◽

10.3389/fpubh.2021.777759 ◽

2022 ◽

Vol 9 ◽

Author(s):

Bo Xu ◽

David Anguiano Sanjurjo ◽

Davide Colombi ◽

Christer Törnevik

Keyword(s):

Monte Carlo ◽

Millimeter Wave ◽

Near Field ◽

Multiple Input Multiple Output ◽

Monte Carlo Analysis ◽

Base Station ◽

Base Stations ◽

Far Field ◽

Wave Radio ◽

Maximum Exposure

International radio frequency (RF) electromagnetic field (EMF) exposure assessment standards and regulatory bodies have developed methods and specified requirements to assess the actual maximum RF EMF exposure from radio base stations enabling massive multiple-input multiple-output (MIMO) and beamforming. Such techniques are based on the applications of power reduction factors (PRFs), which lead to more realistic, albeit conservative, exposure assessments. In this study, the actual maximum EMF exposure and the corresponding PRFs are computed for a millimeter-wave radio base station array antenna. The computed incident power densities based on near-field and far-field approaches are derived using a Monte Carlo analysis. The results show that the actual maximum exposure is well below the theoretical maximum, and the PRFs similar to those applicable for massive MIMO radio base stations operating below 6 GHz are also applicable for millimeter-wave frequencies. Despite the very low power levels that currently characterize millimeter-wave radio base stations, using the far-field approach can also guarantee the conservativeness of the PRFs used to assess the actual maximum exposure close to the antenna.

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Smart Energy Consumption of IoT With Millimeter-Wave Cognitive Radiofor 5G Cellular Network

10.21203/rs.3.rs-621335/v1 ◽

2021 ◽

Author(s):

Dan Ye

Keyword(s):

Energy Consumption ◽

Cognitive Radio ◽

Energy Saving ◽

Millimeter Wave ◽

Resource Sharing ◽

Network Capacity ◽

Visible Light Communications ◽

Radio Access ◽

Data Rates ◽

Iot Devices

Abstract Millimeter-wave technology is rising as a crucial component for 5G radio access and other emerging ancillary wireless networks including Gb/s device-to-device communication and mobile backhaul. This paper envisions that millimeter-wave cognitive radio in 5G network is a proposed smart energy consumption solution of Internet of Things (IoT) devices. Improving resource efficiency and enhancing data rates, resource sharing is a proposed advantage over millimeter wave cognitive radio in 5G IoT network. IoT Fog collaboration is proposed to apply artificial intelligence techniques to offer important energy-saving services allowing integrated systems to perceive, reason, learn, and act intelligently in intelligent gateway control. Smart energy meters are the current energy-saving utility in the flexible deployment of IoT architecture. NarrowBand IoT (NB-IoT) delivers Low Power Wide Area access (LPWA) to a new generation of connected things in the race to 5G IoT network, reducing energy computation and achieving promising network capacity. The renewable energy strategy is a proposed energy-efficiency solution in IoT network, maximizing the power supply while minimizing power consumption. A novel kind of visible light communications (VLC) is proposed to enable mmWave cognitive radio receiver in 5G IoT network. Simulation results show the proposed solution can reap the benefits of higher data rates, more IoT device connectivity, and lower energy consumption.

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Spectrum Handover Strategies for Cognitive Femtocell Networks

Advances in Wireless Technologies and Telecommunication - Femtocell Communications and Technologies ◽

10.4018/978-1-4666-0092-8.ch006 ◽

2012 ◽

pp. 85-102 ◽

Cited By ~ 3

Author(s):

Saba Al-Rubaye ◽

Anwer Al-Dulaimi ◽

John Cosmas

Keyword(s):

Base Stations ◽

Handover Management ◽

Spectrum Utilization ◽

Femtocell Networks ◽

Data Rates ◽

Switching Unit ◽

Geographical Cluster ◽

Service Coordinator ◽

Cognitive Femtocell

Cognitive femtocell is a promising technology for the next generation wireless networks to improve the efficiency of spectrum utilization, coverage, and to attain higher data rates for indoor communications. In this chapter, the new Cognitive Femtocell Switching Unit (CFSU) is proposed to support handover management for 10-20 cognitive femtocells as a local geographical cluster. Thus, CFSU acts as a service coordinator between femtocells and macrocell areas to improve spectrum utilization and coexistence. Then, the chapter presents solutions for spectrum handover to achieve guaranteed quality of radio service, spectrum utilization, and enable an excellent local handover management to reduce unnecessary handovers between femtocell base stations. The challenges and solutions that are presented in this chapter have the ability to maintain services by evaluating the requested quality of services.

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Deep learning–based fifth-generation millimeter-wave communication channel tracking for unmanned aerial vehicle Internet of things networks

International Journal of Distributed Sensor Networks ◽

10.1177/1550147719865882 ◽

2019 ◽

Vol 15 (8) ◽

pp. 155014771986588 ◽

Cited By ~ 3

Author(s):

Shan Meng ◽

Xin Dai ◽

Bicheng Xiao ◽

Yimin Zhou ◽

Yumei Li ◽

...

Keyword(s):

Internet Of Things ◽

Unmanned Aerial Vehicle ◽

Millimeter Wave ◽

Estimation Method ◽

Attitude Estimation ◽

Base Stations ◽

Communication Link ◽

Multiple Sensors ◽

Channel Tracking ◽

Aerial Vehicle

Using unmanned aerial vehicle as movable base stations is a promising approach to enhance network coverage. Moreover, movable unmanned aerial vehicle–base stations can dynamically move to the target devices to expand the communication range as relays in the scenario of the Internet of things. In this article, we consider a communication system with movable unmanned aerial vehicle–base stations in millimeter-Wave. The movable unmanned aerial vehicle–base stations are equipped with antennas and multiple sensors for channel tracking. The cylindrical array antenna is mounted on the movable unmanned aerial vehicle–movable base stations, making the beam omnidirectional. Furthermore, the attitude estimation method using the deep neural network can replace the traditional attitude estimation method. The estimated unmanned aerial vehicle attitude information is combined with beamforming technology to realize a reliable communication link. Simulation experiments have been performed, and the results have verified the effectiveness of the proposed method.

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Performance Analysis of Millimeter-Wave UAV Swarm Networks under Blockage Effects

Sensors ◽

10.3390/s20164593 ◽

2020 ◽

Vol 20 (16) ◽

pp. 4593

Author(s):

Haejoon Jung ◽

In-Ho Lee

Keyword(s):

Millimeter Wave ◽

Channel Model ◽

High Mobility ◽

Base Stations ◽

Shape Theory ◽

High Data ◽

Mobile Cellular ◽

Seamless Connectivity ◽

Mobile Cellular Networks ◽

Uav Swarm

Due to their high mobility, unmanned aerial vehicles (UAVs) can offer better connectivity by complement or replace with the existing terrestrial base stations (BSs) in the mobile cellular networks. In particular, introducing UAV and millimeter wave (mmWave) technologies can better support the future wireless networks with requirements of high data rate, low latency, and seamless connectivity. However, it is widely known that mmWave signals are susceptible to blockages because of their poor diffraction. In this context, we consider macro-diversity achieved by the multiple UAV BSs, which are randomly distributed in a spherical swarm. Using the widely used channel model incorporated with the distance-based random blockage effects, which is proposed based on stochastic geometry and random shape theory, we investigate the outage performance of the mmWave UAV swarm network. Further, based on our analysis, we show how to minimize the outage rate by adjusting various system parameters such as the size of the UAV swarm relative to the distance to the receiver.

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Wireless Technologies for Mobile Computing and Commerce

Mobile Computing ◽

10.4018/978-1-60566-054-7.ch097 ◽

2009 ◽

pp. 1175-1182

Author(s):

David Wright

Keyword(s):

Mobile Computing ◽

New Technologies ◽

Base Stations ◽

Wifi Networks ◽

Municipal Governments ◽

Wireless Technologies ◽

Community Associations ◽

Data Rates ◽

Business Analysis ◽

British Telecom

At the time of writing (1Q06) most countries have a small number (2-6) of major cellular operators offering competing 2.5G and 3G cellular services. In addition, there is a much larger number of operators of WiFi networks. In some cases, a major cellular operator, for example, Deutsche Telekomm and British Telecom, also offers a WiFi service. In other cases, WiFi services are provided by a proliferation of smaller network operators, such as restaurants, laundromats, airports, railways, community associations and municipal governments. Many organizations offer WiFi free of charge as a hospitality service, for example, restaurants. Cellular services offer ubiquitous, low data rate communications for mobile computing and commerce, whereas WiFi offers higher data rates, but less ubiquitous coverage, with limitations on mobility due to business as opposed to technology reasons. Emerging networks for mobile computing and commerce include WiMAX and WiMobile (Wright, 2006), which offer higher data rates, lower costs and city-wide coverage with handoff of calls among multiple base stations. These new technologies may be deployed by the organizations that currently deploy cellular and WiFi networks, and also may give rise to a new group of competitive wireless network operators. This article identifies the capabilities needed for mobile computing and commerce and assesses their technology and business implications. It identifies developments in the wireless networks that can be used for mobile computing and commerce, together with the services that can be provided over such networks. It provides a business analysis indicating which network operators can profitably deploy new networks, and which network operators need to establish business and technology links with each other so as to better serve their customers. The resulting range of next generation service, technologies and network operators available for mobile computing and commerce is identified.

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