Countering Eavesdroppers with Meta-learning-based Cooperative Ambient Backscatter Communications

This article introduces a novel lightweight framework using ambient backscattering communications to counter eavesdroppers. In particular, our framework divides an original message into two parts: (i) the active-transmit message transmitted by the transmitter using conventional RF signals and (ii) the backscatter message transmitted by an ambient backscatter tag that backscatters upon the active signals emitted by the transmitter. Notably, the backscatter tag does not generate its own signal, making it difficult for an eavesdropper to detect the backscattered signals unless they have prior knowledge of the system. Here, we assume that without decoding/knowing the backscatter message, the eavesdropper is unable to decode the original message. Even in scenarios where the eavesdropper can capture both messages, reconstructing the original message is a complex task without understanding the intricacies of the message-splitting mechanism. A challenge in our proposed framework is to effectively decode the backscattered signals at the receiver, often accomplished using the maximum likelihood (MLK) approach. However, such a method may require a complex mathematical model together with perfect channel state information (CSI). To address this issue, we develop a novel deep meta-learning-based signal detector that can not only effectively decode the weak backscattered signals without requiring perfect CSI but also quickly adapt to a new wireless environment with very little knowledge. Simulation results show that our proposed learning approach, without requiring perfect CSI and complex mathematical model, can achieve a bit error ratio close to that of the MLK-based approach. They also clearly show the efficiency of the proposed approach in dealing with eavesdropping attacks and the lack of training data for deep learning models in practical scenarios

Swarm of UAVs for Network Management in 6G: A Technical Review

Fifth-generation (5G) cellular networks have led to the implementation of beyond 5G (B5G) networks, which are capable of incorporating autonomous services to swarm of unmanned aerial vehicles (UAVs). They provide capacity expansion strategies to address massive connectivity issues and guarantee ultra-high throughput and low latency, especially in extreme or emergency situations where network density, bandwidth, and traffic patterns fluctuate. On the one hand, 6G technology integrates AI/ML, IoT, and blockchain to establish ultra-reliable, intelligent, secure, and ubiquitous UAV networks. 6G networks, on the other hand, rely on new enabling technologies such as air interface and transmission technologies, as well as a unique network design, posing new challenges for the swarm of UAVs. Keeping these challenges in mind, this article focuses on the security and privacy, intelligence, and energy-efficiency issues faced by swarms of UAVs operating in 6G mobile networks. In this state-of-the-art review, we integrated blockchain and AI/ML with UAV networks utilizing the 6G ecosystem. The key findings are then presented, and potential research challenges are identified. We conclude the review by shedding light on future research in this emerging field of research.Comment: 19,

On the Performance of Power Beacon-Assisted D2D Communications in the Presence of Multi-Jammers and Eavesdropper

In this work, we investigate the performance analysis of a device-to-device (D2D) communication network under an eavesdropper E attack. Besides, we assume that E is located in the proximal region where it can overhear the information from the source S. Specifically, S transmits information to the destination D, adopting the power beacon's energy to surmount the limited energy budget. Moreover, to reduce the quality of the eavesdropping link, the cooperative jamming technique can be used, where the multi-friendly jammers are employed to generate the artificial noises to E continuously. As considering the above presentation, we derive the quality of system analysis in terms of the outage probability (OP), intercept probability (IP), and secrecy outage probability (SOP) of the proposed system model. Finally, the Monte-Carlo simulations are performed to corroborate the exactness of the mathematical analysis.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited

Aeronautical engineering: A continuing bibliography with indexes (supplement 318)

This bibliography lists 217 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1995. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

RFID multiantenna systems for wireless communications and sensing

Many scientific, industrial and medical applications require the measurement of different physical parameters in order to collect information about the spatially distributed status of some process. Very often this information needs to be collected remotely, either due to the spatial dispersion of the measurement points or due to their inaccessibility. A wireless embedded self-powered sensor may be a convenient solution to be placed at these inaccessible locations. This thesis is devoted to study the analytical relation governing the electromagnetic coupling between a reader and a embeddable self-powered sensor, based on radio frequency identification (RFID) technology, which is capable of wirelessly retrieving the status of physical parameters at a remote and inaccessible location. The physical parameter to be sensed may be the electromagnetic (EM) field existing at that location (primary measurement) or the indirect measurement of other parameters such as the temperature, humidity, etc. (secondary measurement). Given the simplicity of the RFID solution (highly embeddable properties, scavenging capabilities, penetration and radio coverage characteristics, etc.) the measurement can be done at a single location, or it can be extended to a set of measuring locations (an array or grid of sensors). The analytical relation is based on a reciprocity formulation studying the modulation of the scattered field by the embedded sensor in relation with the incident field, and allows to define a set of quality parameters of interest for the optimum design of the sensors. Particular attention is given to the scavenging circuitry as well as to the antenna design relevant to the sensing objective. In RFID tags, the existence of an RF harvesting section is an improvement with respect to conventional scattering field probes since it removes the need of DC biasing lines or optical fibers to modulate the sensor. However, this harvesting section introduces non-linearities in the response of the sensor, which requires a proper correction to use them as EM-field probes, although the characterization of the non-linearities of the RFID tag cannot be directly done using a conventional vector network analyzer (VNA), due to the requirements of an RFID protocol excitation. Due to this, this thesis proposes an alternative measurement approach that allows to characterize the different scattering states used for the modulation, in particular its non-linear behavior. In addittion, and taking this characterization as the starting point, this thesis proposes a new measurement setup for EM-field measurements based on the use of multiple tones to enlarge the available dynamic range, which is experimentally demonstrated in the measurement of a radiation pattern, as well as in imaging applications. The RFID-based sensor response is electromagnetically sensitive to the dielectric properties of its close environment. However, the governing formulation for the response of the probe mixes together a set of different contributions, the path-loss, the antenna impedance, the loads impedance, etc. As a consequence, it is not possible to isolate each contribution from the others using the information available with a conventional RFID sensor. This thesis mathematically proposes and experimentally develops a modification of the modulation scheme to introduce a new set of multi-load scattering states that increases the information available in the response and properly isolate each term. Moreover, this thesis goes a step forward and introduces a new scattering state of the probe sensitive to temperature variations that do not depend on the environment characteristics. This new configuration enables robust environmental sensing in addition to EM-field measurements, and sensing variations of the dielectric properties of the environment

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

Future Wireless Networks: Towards Learning-driven Sixth-generation Wireless Communications

The evolution of wireless communication networks, from present to the emerging fifth-generation (5G) new radio (NR), and sixth-generation (6G) is inevitable, yet propitious. The thesis evolves around application of machine learning and optimization techniques to problems in spectrum management, internet-of-things (IoT), physical layer security, and intelligent reflecting surface (IRS). The first problem explores License Assisted Access (LAA), which leverages unlicensed resource sharing with the Wi-Fi network as a promising technique to address the spectrum scarcity issue in wireless networks. An optimal communication policy is devised which maximizes the throughput performance of LAA network while guaranteeing a proportionally fair performance among LAA stations and a fair share for Wi-Fi stations. The numerical results demonstrate more than 75 % improvement in the LAA throughput and a notable gain of 8-9 % in the fairness index. Next, we investigate the unlicensed spectrum sharing for bandwidth hungry diverse IoT networks in 5G NR. An efficient coexistence mechanism based on the idea of adaptive initial sensing duration (ISD) is proposed to enhance the diverse IoT-NR network performance while keeping the primary Wi-Fi network's performance to a bearable threshold. A Q-learning (QL) based algorithm is devised to maximize the normalized sum throughput of the coexistence Wi-Fi/IoT-NR network. The results confirm a maximum throughput gain of 51 % and ensure that the Wi-Fi network's performance remains intact. Finally, advanced levels of network security are critical to maintain due to severe signal attenuation at higher frequencies of 6G wireless communication. Thus, an IRS-based model is proposed to address the issue of network security under trusted-untrusted device diversity, where the untrusted devices may potentially eavesdrop on the trusted devices. A deep deterministic policy gradient (DDPG) algorithm is devised to jointly optimize the active and passive beamforming matrices. The results confirm a maximum gain of 2-2.5 times in the sum secrecy rate of trusted devices and ensure Quality-of-Service (QoS) for all the devices. In conclusion, the thesis has led towards efficient, secure, and smart communication and build foundation to address similar complex wireless networks

Multiantenna Quantum Backscatter Communications

Quantum illumination (QI) is a revolutionary photonic quantum sensing paradigm that enhances the sensitivity of photodetection in noisy and lossy environments. In this paper, we propose to use QI in a quantum backscatter communication (QBC), with the aim of increasing the receiver sensitivity beyond the limits of its classical counterpart. One of the practical challenges in microwave QI is the slow rate at which the entangled microwave modes can be generated. Here, we propose to mitigate this problem by using a multiple-input multiple-output antenna system to synthetically increase the number of efficiently- distinguishable modes in the QBC context.Peer reviewe