Wireless Networking: Theory, Practice, and Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 4897

Special Issue Editor


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Guest Editor
Computer Science Department, Portland State University, Portland, OR 97201, USA
Interests: computer and network systems; particularly wireless systems; edge computing; machine learning; security and privacy; emerging Internet of Things applications such as wirelessly connected vehicles; aerial drones; virtual/augmented reality headsets

Special Issue Information

Dear Colleagues,

Mobile data traffic is expected to grow exponentially over the next decade, driven by video and emerging bandwidth-intensive applications such as mobile augmented reality. In parallel, there is a strong demand from every industry sector including utility companies, car and manufacturing companies, and the health and education sectors to exploit the benefits of wireless connectivity. Such evolution will result in the connection of billions of new Internet of Things (IoT) devices to the Internet over the next decade. Thus, future wireless networks must satisfy the throughput, delay, security, and energy consumption requirements of a diverse set of applications and connected devices at a low cost and high efficiency. These challenges require the invention of new technologies across the entire protocol stack including innovations at the physical layer, medium access, transport, and mobile applications, among others.

This Special Issue will focus on key theoretical and practical design issues for next-generation wireless networks and mobile applications. Prospective authors are cordially invited to submit their original manuscripts on topics related to theory, practice, and applications of wireless networks, including but not limited to:

5G and beyond wireless networks;

Edge/fog/mobile computing;

MIMO-based networking;

Mobile network architecture;

Mobile sensing and applications;

Mobile management and models;

mmWave/THz/VLC/full-duplex communication;

Machine learning for wireless networks;

Network economics and pricing;

Spectrum sharing;

Wireless applications such as drones/virtual reality/connected vehicles;

Wireless security;

Wireless measurements;

WLAN/WPAN/LPWAN/RFID/NFC.

Prof. Ehsan Aryafar
Guest Editor

Manuscript Submission Information

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Keywords

  • Internet of Things
  • wireless network protocols
  • models
  • measurements

Published Papers (2 papers)

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Research

18 pages, 466 KiB  
Article
Rate Maximization in a UAV Based Full-Duplex Multi-User Communication Network Using Multi-Objective Optimization
by Syed Muhammad Hashir, Sabyasachi Gupta, Gavin Megson, Ehsan Aryafar and Joseph Camp
Electronics 2022, 11(3), 401; https://doi.org/10.3390/electronics11030401 - 28 Jan 2022
Cited by 3 | Viewed by 2143
Abstract
In this paper, we study an unmanned-aerial-vehicle (UAV) based full-duplex (FD) multi-user communication network, where a UAV is deployed as a multiple-input–multiple-output (MIMO) FD base station (BS) to serve multiple FD users on the ground. We propose a multi-objective optimization framework which considers [...] Read more.
In this paper, we study an unmanned-aerial-vehicle (UAV) based full-duplex (FD) multi-user communication network, where a UAV is deployed as a multiple-input–multiple-output (MIMO) FD base station (BS) to serve multiple FD users on the ground. We propose a multi-objective optimization framework which considers two desirable objective functions, namely sum uplink (UL) rate maximization and sum downlink (DL) rate maximization while providing quality-of-service to all the users in the communication network. A novel resource allocation multi-objective-optimization-problem (MOOP) is designed which optimizes the downlink beamformer, the beamwidth angle, and the 3D position of the UAV, and also the UL power of the FD users. The formulated MOOP is a non-convex problem which is generally intractable. To handle the MOOP, a weighted Tchebycheff method is proposed, which converts the problem to the single-objective-optimization-problem (SOOP). Further, an alternative optimization approach is used, where SOOP is converted in to multiple sub-problems and optimization variables are operated alternatively. The numerical results show a trade-off region between sum UL and sum DL rate, and also validate that the considered FD system provides substantial improvement over traditional HD systems. Full article
(This article belongs to the Special Issue Wireless Networking: Theory, Practice, and Applications)
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14 pages, 12149 KiB  
Article
An Experiment-Based Comparison between Fully Digital and Hybrid Beamforming Radio Architectures for Many-Antenna Full-Duplex Wireless Communication
by Gavin Megson, Sabyasachi Gupta, Syed Muhammad Hashir, Ehsan Aryafar and Joseph Camp
Electronics 2022, 11(1), 59; https://doi.org/10.3390/electronics11010059 - 25 Dec 2021
Cited by 1 | Viewed by 2113
Abstract
Full-duplex (FD) communication in many-antenna base stations (BSs) is hampered by self-interference (SI). This is because a FD node’s transmitting signal generates significant interference to its own receiver. Recent works have shown that it is possible to reduce/eliminate this SI in fully digital [...] Read more.
Full-duplex (FD) communication in many-antenna base stations (BSs) is hampered by self-interference (SI). This is because a FD node’s transmitting signal generates significant interference to its own receiver. Recent works have shown that it is possible to reduce/eliminate this SI in fully digital many-antenna systems, e.g., through transmit beamforming by using some spatial degrees of freedom to reduce SI instead of increasing the beamforming gain. On a parallel front, hybrid beamforming has recently emerged as a radio architecture that uses multiple antennas per FR chain. This can significantly reduce the cost of the end device (e.g., BS) but may also reduce the capacity or SI reduction gains of a fully digital radio system. This is because a fully digital radio architecture can change both the amplitude and phase of the wireless signal and send different data streams from each antenna element. Our goal in this paper is to quantify the performance gap between these two radio architectures in terms of SI cancellation and system capacity, particularly in multi-user MIMO setups. To do so, we experimentally compare the performance of a state-of-the-art fully digital many antenna FD solution to a hybrid beamforming architecture and compare the corresponding performance metrics leveraging a fully programmable many-antenna testbed and collecting over-the-air wireless channel data. We show that SI cancellation through beam design on a hybrid beamforming radio architecture can achieve capacity within 16% of that of a fully digital architecture. The performance gap further shrinks with a higher number of quantization bits in the hybrid beamforming system. Full article
(This article belongs to the Special Issue Wireless Networking: Theory, Practice, and Applications)
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