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A performance of the pseudo-random method for the radar detection is analyzed. The radar sends a pseudo-random sequence of length $N$, and receives echo from $r$ targets. We assume the natural assumptions of uniformity on the channel and of…
We propose in this work a radar detection system for orthogonal-frequency division multiplexing (OFDM) transmission. We assume that the transmitting antenna Tx is colocated with a monostatic radar. The latter knows the transmitted signal…
In this paper we propose a new method for training neural networks (NNs) for frequency modulated continuous wave (FMCW) radar mutual interference mitigation. Instead of training NNs to regress from interfered to clean radar signals as in…
Future sixth-generation (6G) networks are envisioned to provide both sensing and communications functionalities by using densely deployed base stations (BSs) with massive antennas operating in millimeter wave (mmWave) and terahertz (THz).…
Neural networks are increasingly used to estimate parameters in quantitative MRI, in particular in magnetic resonance fingerprinting. Their advantages over the gold standard non-linear least square fitting are their superior speed and their…
Modern radar systems are designed to have high Doppler tolerance to detect fast-moving targets. This means range and Doppler estimations are inevitably coupled, opening pathways to concealing objects by imprinting artificial Doppler…
Both Noise Radar and Quantum Radar, with some alleged common features, exploit the randomness of the transmitted signal to enhance radar covertness and to reduce mutual interference. While Noise Radar has been prototypically developed and…
Quantum radar has emerged as a promising paradigm that utilizes entanglement and quantum correlations to overcome the limitations of classical detection in noisy and lossy environments. By exploiting microwave entanglement generated from…
In automotive applications, frequency modulated continuous wave (FMCW) radar is an established technology to determine the distance, velocity and angle of objects in the vicinity of the vehicle. The quality of predictions might be seriously…
With the rise of critical machine-to-machine applications, next generation wireless communication systems must be designed with strict constraints on the latency and reliability. A key question in this context relates to channel state…
In this paper, we introduce the Causal Cognitive Interference Channel With Delay (CC-IFC-WD) in which the cognitive user transmission can depend on $L$ future received symbols as well as the past ones. Taking the effect of the link delays…
As a widely used localization and sensing technique, radars will play an important role in future wireless networks. However, the wireless channels between the radar and the targets are passively adopted by traditional radars, which limits…
In this paper, cognitive transmission under quality of service (QoS) constraints is studied. In the cognitive radio channel model, it is assumed that the secondary transmitter sends the data at two different average power levels, depending…
Wideband spectrum sensing is becoming increasingly important to cognitive radio (CR) systems for exploiting spectral opportunities. This paper introduces a novel multi-rate sub-Nyquist spectrum sensing (MS3) system that implements…
In automotive systems, a radar is a key component of autonomous driving. Using transmit and reflected radar signal by a target, we can capture the target range and velocity. However, when interference signals exist, noise floor increases…
In this paper, we propose multi-input multi-output (MIMO) beamforming designs towards joint radar sensing and multi-user communications. We employ the Cram\'er-Rao bound (CRB) as a performance metric of target estimation, under both point…
Through spatial multiplexing and diversity, multi-input multi-output (MIMO) cognitive radio (CR) networks can markedly increase transmission rates and reliability, while controlling the interference inflicted to peer nodes and primary users…
In this article, a framework is presented for the joint optimization of the analog transmit and receive filter with respect to a parameter estimation problem. At the receiver, conventional signal processing systems restrict the two-sided…
Underwater Acoustic (UWA) networks are vital for remote sensing and ocean exploration but face inherent challenges such as limited bandwidth, long propagation delays, and highly dynamic channels. These constraints hinder real-time…
A radar system emits probing signals and records the reflections. Estimating the relative angles, delays, and Doppler shifts from the received signals allows to determine the locations and velocities of objects. However, due to practical…