46 research outputs found
Expanding Boundaries: Cross-Media Routing for Seamless Underwater and Aerial Communication
The colossal evolution of wireless communication technologies over the past
few years has driven increased interest in its integration in a variety of
less-explored environments, such as the underwater medium. In this magazine
paper, we present a comprehensive discussion on a novel concept of routing
protocol known as cross-media routing, incorporating the marine and aerial
interfaces. In this regard, we discuss the limitation of single-media routing
and advocate the need for cross-media routing along with the current status of
research development in this direction. To this end, we also propose a novel
cross-media routing protocol known as bubble routing for autonomous marine
systems where different sets of AUVs, USVs, and airborne nodes are considered
for the routing problem. We evaluate the performance of the proposed routing
protocol by using the two key performance metrics, i.e., packet delivery ratio
(PDR) and end-to-end delay. Moreover, we delve into the challenges encountered
in cross-media routing, unveiling exciting opportunities for future research
and innovation. As wireless communication expands its horizons to encompass the
underwater and aerial domains, understanding and addressing these challenges
will pave the way for enhanced cross-media communication and exploration.Comment: Submitted to IEEE Communications Magazin
On the Effective Capacity of IRS-assisted wireless communication
We consider futuristic, intelligent reflecting surfaces (IRS)-aided
communication between a base station (BS) and a user equipment (UE) for two
distinct scenarios: a single-input, single-output (SISO) system whereby the BS
has a single antenna, and a multi-input, single-output (MISO) system whereby
the BS has multiple antennas. For the considered IRS-assisted downlink, we
compute the effective capacity (EC), which is a quantitative measure of the
statistical quality-of-service (QoS) offered by a communication system
experiencing random fading. For our analysis, we consider the two widely-known
assumptions on channel state information (CSI) -- i.e., perfect CSI and no CSI,
at the BS. Thereafter, we first derive the distribution of the signal-to-noise
ratio (SNR) for both SISO and MISO scenarios, and subsequently derive
closed-form expressions for the EC under perfect CSI and no CSI cases, for both
SISO and MISO scenarios. Furthermore, for the SISO and MISO systems with no
CSI, it turns out that the EC could be maximized further by searching for an
optimal transmission rate , which is computed by exploiting the iterative
gradient-descent method. We provide extensive simulation results which
investigate the impact of the various system parameters, e.g., QoS exponent,
power budget, number of transmit antennas at the BS, number of reflective
elements at the IRS etc., on the EC of the system
Preventing Identity Attacks in RFID Backscatter Communication Systems: a Physical-Layer Approach
This work considers identity attack on a radio-frequency identification (RFID)-based backscatter communication system. Specifically, we consider a singlereader, single-tag RFID system whereby the reader and the tag undergo two-way signaling which enables the reader to extract the tag ID in order to authenticate the legitimate tag (L-tag). We then consider a scenario whereby a malicious tag (M-tag)—having the same ID as the Ltag programmed in its memory by a wizard—attempts to deceive the reader by pretending to be the L-tag. To this end, we counter the identity attack by exploiting the non-reciprocity of the end-to-end channel (i.e., the residual channel) between the reader and the tag as the fingerprint of the tag. The passive nature of the tag(s) (and thus, lack of any computational platform at the tag) implies that the proposed light-weight physical-layer authentication method is implemented at the reader. To be concrete, in our proposed scheme, the reader acquires the raw data via two-way (challenge-response) message exchange mechanism, does least-squares estimation to extract the fingerprint, and does binary hypothesis testing to do authentication. We also provide closed-form expressions for the two error probabilities of interest (i.e., false alarm and missed detection). Simulation results attest to the efficacy of the proposed method
Copyright protection of scalar and multimedia sensor network data using digital watermarking
This thesis records the research on watermarking techniques to address the issue of copyright protection of the scalar data in WSNs and image data in WMSNs, in order to ensure that the proprietary information remains safe between the sensor nodes in both. The first objective is to develop LKR watermarking technique for the copyright protection of scalar data in WSNs. The second objective is to develop GPKR watermarking technique for copyright protection of image data in WMSN
Smart Wireless Sensor Networks
The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks
Deep Learning in Mobile and Wireless Networking: A Survey
The rapid uptake of mobile devices and the rising popularity of mobile
applications and services pose unprecedented demands on mobile and wireless
networking infrastructure. Upcoming 5G systems are evolving to support
exploding mobile traffic volumes, agile management of network resource to
maximize user experience, and extraction of fine-grained real-time analytics.
Fulfilling these tasks is challenging, as mobile environments are increasingly
complex, heterogeneous, and evolving. One potential solution is to resort to
advanced machine learning techniques to help managing the rise in data volumes
and algorithm-driven applications. The recent success of deep learning
underpins new and powerful tools that tackle problems in this space.
In this paper we bridge the gap between deep learning and mobile and wireless
networking research, by presenting a comprehensive survey of the crossovers
between the two areas. We first briefly introduce essential background and
state-of-the-art in deep learning techniques with potential applications to
networking. We then discuss several techniques and platforms that facilitate
the efficient deployment of deep learning onto mobile systems. Subsequently, we
provide an encyclopedic review of mobile and wireless networking research based
on deep learning, which we categorize by different domains. Drawing from our
experience, we discuss how to tailor deep learning to mobile environments. We
complete this survey by pinpointing current challenges and open future
directions for research
Watching Androids Dream of Electric Sheep: Immersive Technology, Biometric Psychography, and the Law
Virtual reality and augmented reality present exceedingly complex privacy issues because of the enhanced user experience and reality-based models. Unlike the issues presented by traditional gaming and social media, immersive technology poses inherent risks, which our legal understanding of biometrics and online harassment is simply not prepared to address. This Article offers five important contributions to this emerging space. It begins by introducing a new area of legal and policy inquiry raised by immersive technology called “biometric psychography.” Second, it explains how immersive technology works to a legal audience and defines concepts that are essential to understanding the risks that the technology poses. Third, it analyzes the gaps in privacy law to address biometric psychography and other emerging challenges raised by immersive technology that most regulators and consumers incorrectly assume will be governed by existing law. Fourth, this Article sources firsthand interviews from early innovators and leading thinkers to highlight harassment and user experience risks posed by immersive technology. Finally, this Article compiles insights from each of these discussions to propose a framework that integrates privacy and human rights into the development of future immersive tech applications. It applies that framework to three specific scenarios and demonstrates how it can help navigate challenges, both old and new