The rapid population growth in large urban cities has led to an unprecedented increase in both the number and the diversity of wireless devices and applications with varying quality of service requirements in terms of latency and data rates. LinkNYC is an example of an urban communication network infrastructure, which...
In recent years, RF (Radio Frequency) device fingerprinting using deep learning has emerged as a method of identifying devices solely by their RF transmissions. Conventional approaches to this type of device fingerprinting are not portable to different domains. That is, if a model for this purpose is trained on data...
RF data-driven device fingerprinting through the use of deep learning has recently surfaced as a possible method for secure device identification and authentication. Traditional approaches are commonly susceptible to the domain adaptation problem where a model trained on data from one domain performs badly when tested on data from a...
The meteoric rise and prevalent usage of wireless networking technologies for mobile
communication applications have captured the attention of media and imagination of
public in the recent decade. One such proliferation is experienced in Wireless Sensor
Networks (WSNs), where multimedia enabled elements are fused with integrated
sensors to empower tightly...
The proliferation of mobile users and internet content has advanced a plethora of research areas. Among these areas include mobile networks, transport layer protocols, and smart cities. Research shows that global mobile data traffic will increase sevenfold reaching 49 exabytes per month by 2021, most of which will be mobile...
Most of today’s Internet of Things (IoT) applications assume that data will be moved offdevices into centralized cloud platforms. While existing IoT systems leverage cloud-based analytics for meaningful data reasoning, the assumption that data should always be moved off the devices is problematic. The amount of data to be moved...
Cognitive Radio Networks (CRNs) enable opportunistic access to the licensed channel resources by allowing unlicensed users to exploit vacant channel opportunities. One effective technique through which unlicensed users, often referred to as Secondary Users (SUs), acquire whether a channel is vacant is cooperative spectrum sensing. Despite its effectiveness in enabling...
The scarcity of wireless spectrum resources and the overwhelming demand for wireless broadband resources have prompted industry, government agencies and academia within the wireless communities to develop and come up with effective solutions that can make additional spectrum available for broadband data. As part of these ongoing efforts, cognitive radio...
The widespread use of wireless devices that we have recently been witnessing, such as smartphones, tablets, laptops, and wirelessly accessible devices in general, is causing an unprecedented growth in the required amount of the wireless radio spectrum. On the other hand, the spectrum resource has, for the last several decades,...
Cognitive radio technology emerges as a promising solution for overcoming shortage and inefficient use of spectrum resources. In cognitive radio networks, secondary users, which are users equipped with cognitive radios, can opportunistically access spectrum assigned to primary users, the spectrum license holders. Although it improves spectrum utilization efficiency, this opportunistic...