Related papers: Measuring Hardware Impairments with Software-Defin…
A Software-Defined Radio (SDR) platform is a communication system that implements as software functions that are typically implemented in dedicated hardware. One of its main advantages is the flexibility to test and deploy radio…
As developments of electromagnetic weapons, Electronic Warfare (EW) has been rising as the future form of war. Especially in wireless communications, the high security defense systems, such as Low Probability of Detection (LPD), Low…
The proliferation of wireless devices and their ever increasing influence on our day-to-day life is very evident and seems irreplaceable. This exponential growth in demand, both in terms of the number of devices and Quality of Service (QoS)…
In this paper, we introduce AERIQ: a software-defined radio (SDR) based I/Q measurement and analysis framework for wireless signals for aerial experimentation. AERIQ is integrated into controllable aerial vehicles, it is flexible,…
Of late, Software Defined Radio (SDR) approach has become an effective means to design high data rate wireless systems for a range of applications. There are methods with which low cost SDR based 4th generation (4G) or long term evolution…
Software-defined radios (SDRs) are often used in the experimental evaluation of next-generation wireless technologies. While crowd-sourced spectrum monitoring is an important component of future spectrum-agile technologies, there is no…
High-quality radio frequency (RF) components are imperative for efficient wireless communication. However, these components can degrade over time and need to be identified so that either they can be replaced or their effects can be…
Due to the Internet of Things (IoT) proliferation, Radio Frequency (RF) channels are increasingly congested with new kinds of devices, which carry unique and diverse communication needs. This poses complex challenges in modern digital…
Radio frequency (RF)-based indoor localization offers significant promise for applications such as indoor navigation, augmented reality, and pervasive computing. While deep learning has greatly enhanced localization accuracy and robustness,…
In this paper, we investigate the performance analysis of dual hop relaying system consisting of asymmetric Radio Frequency (RF)/Free Optical Space (FSO) links. The RF channels follow a Rayleigh distribution and the optical links are…
In this paper, we propose a dual-hop RF (Radio-Frequency)/FSO (Free-Space Optical) system with multiple relays employing the Decode-and-Forward (DF) and Amplify-and-Forward (AF) with a Fixed Gain (FG) relaying scheme. The RF channels are…
Radio frequency (RF) signal recognition plays a critical role in modern wireless communication and security applications. Deep learning-based approaches have achieved strong performance but typically rely heavily on extensive training data…
RF electronics deals with the generation, acquisition and manipulation of high-frequency signals. In particle accelerators signals of this kind are abundant, especially in the RF and beam diagnostics systems. In modern machines the…
Edge intelligence has emerged as a promising strategy to deliver low-latency and ubiquitous services for mobile devices. Recent advances in fine-tuning mechanisms of foundation models have enabled edge intelligence by integrating low-rank…
Radio Frequency Identification (RFID) and implantable biomedical devices need efficient power and data transfer with very low profile antennas. We propose a low profile electrically small antenna for near-field wireless power and data…
The stepped-frequency (SF) waveform is an effective way to achieve high range resolution (HRR) in modern radars. In this paper, we determine some fundamental limits of SF waveforms on ambiguity, stability and accuracy of stable targets…
The aim of this paper is to present an implementation of a functional IEEE 802.15.7 real-time testbed based on the Software Defined Radio (SDR) concept. This implementation is built with low cost commercial off-the-shelf (COTS) analog…
As the scale and complexity of integrated circuits continue to increase, traditional modeling methods are struggling to address the nonlinear challenges in radio frequency (RF) chips. Deep learning has been increasingly applied to RF device…
Modern edge devices increasingly rely on neural networks for intelligent applications. However, conventional digital computing-based edge inference requires substantial memory and energy consumption. In analog radio frequency (RF)…
Carrier Frequency Offset (CFO) estimation in Orthogonal Frequency Division Multiplexing (OFDM) systems faces significant performance degradation across heterogeneous software-defined radio (SDR) platforms due to uncalibrated hardware…