The advancement in wireless communication applications encourages the use of effective
and efficient channel estimation (CE) techniques because of the varying behaviour of the …

Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems typically
employ hybrid mixed signal processing to avoid expensive hardware and high training …

It is challenging to acquire accurate channel knowledge for sufficient beamforming gain
because of the large number of antennas. In this paper, a deep learning aided channel …

Random stepped frequency (RSF) radar, which transmits random-frequency pulses, can
suppress the range ambiguity, improve convert detection, and possess excellent electronic …

With the adoption of arbitrary and increasingly wideband signals, the design of modern
radar systems continues to be limited by analog-to-digital converter technology and data …

Compressive radar receiver can keep a good balance between sub-Nyquist sampling and
high resolution. To evaluate the performance of compressive time delay estimators, Cramér …

In this paper, we analyze the impact of compression with complex random matrices on
Fisher information and the Cramér-Rao Bound (CRB) for estimating unknown parameters in …

In this paper, we derive Hybrid, Bayesian and Marginalized Cramér-Rao lower bounds
(HCRB, BCRB and MCRB) for the single and multiple measurement vector Sparse Bayesian …

In this paper, we propose a sparse signal estimation algorithm that is suitable for many
wireless communication systems, especially for the future millimeter wave and underwater …

Compressed sensing (CS) is a promising emerging domain that outperforms the classical
limit of the Shannon sampling theory if the measurement vector can be approximated as the …