Search Results for author: Izzat Darwazeh

Found 5 papers, 0 papers with code

Dual band wireless transmission over 75-150GHz millimeter wave carriers using frequency-locked laser pairs

no code implementations27 Oct 2023 Zichuan Zhou, Amany Kassem, James Seddon, Eric Sillekens, Izzat Darwazeh, Polina Bayvel, Zhixin Liu

We generate and transmit 75-GHz-bandwidth OFDM signals over the air using three mutually frequency-locked lasers, achieving minimal frequency gap between the wireless W and D bands using optical-assisted approaches, resulting in 173. 5 Gb/s detected capacity.

Index Modulation Pattern Design for Non-Orthogonal Multicarrier Signal Waveforms

no code implementations18 Apr 2022 Yinglin Chen, Tongyang Xu, Izzat Darwazeh

Spectral efficiency improvement is a key focus in most wireless communication systems and achieved by various means such as using large antenna arrays and/or advanced modulation schemes and signal formats.

An Experimental Proof of Concept for Integrated Sensing and Communications Waveform Design

no code implementations9 Feb 2022 Tongyang Xu, Fan Liu, Christos Masouros, Izzat Darwazeh

This experimental work focuses on a dual-functional radar sensing and communication framework where a single radiation waveform, either omnidirectional or directional, can realize both radar sensing and communication functions.

Wavelet Classification for Over-the-Air Non-Orthogonal Waveforms

no code implementations21 Jun 2020 Tongyang Xu, Izzat Darwazeh

Composite statistical features are investigated and the wavelet enabled two-dimensional time-frequency feature grid is further simplified into a one-dimensional feature vector via proper statistical transform.

Classification General Classification

Deep Learning for Over-the-Air Non-Orthogonal Signal Classification

no code implementations14 Nov 2019 Tongyang Xu, Izzat Darwazeh

Experimental results indicate that transfer learning based CNN can efficiently distinguish different signal formats in both line-of-sight and non-line-of-sight scenarios with great accuracy improvement relative to the non-transfer-learning approaches.

General Classification Transfer Learning

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