Related papers: ULA Fitting for Sparse Array Design

We develop sparse array receive beamformer design methods achieving maximum signal-to-interference plus noise ratio (MaxSINR) for wideband sources and jammers. Both tapped delay line (TDL) filtering and the DFT realizations to wideband…

Direction of arrival (DOA) estimation in array processing using uniform/sparse linear arrays is concerned in this paper. While sparse methods via approximate parameter discretization have been popular in the past decade, the discretization…

Sparse principal component analysis (PCA) is a well-established dimensionality reduction technique that is often used for unsupervised feature selection (UFS). However, determining the regularization parameters is rather challenging, and…

Future wireless networks, deploying thousands of antenna elements, may operate in the radiative near-field (NF), enabling spatial multiplexing across both angle and range domains. Sparse arrays have the potential to achieve comparable…

The design of sub-arrayed phased arrays (PAs) with sub-array-only amplitude and phase controls that afford arbitrary-shaped power patterns matching reference ones is addressed. Such a synthesis problem is formulated in the power pattern…

Ultrasound imaging faces a trade-off between image quality and hardware complexity caused by dense transducers. Sparse arrays are one popular solution to mitigate this challenge. This work proposes an end-to-end optimization framework that…

As the field of sparse arrays progressed, numerous array designs have been introduced with a focus on larger apertures and higher degrees of freedom (DOFs), resulting in maximally economic sparse arrays (MESAs) that operate with the least…

We briefly consider some design aspects of aperture arrays for use in radio astronomy, particularly contrasting the performance of dense and sparse aperture arrays. Recent insights have emerged in the final design phase of LOFAR which…

Collaborative Filtering (CF) remains the cornerstone of modern recommender systems, with dense embedding--based methods dominating current practice. However, these approaches suffer from a critical limitation: our theoretical analysis…

Recent advancements in Deep Learning (DL) for Direction of Arrival (DOA) estimation have highlighted its superiority over traditional methods, offering faster inference, enhanced super-resolution, and robust performance in low…

Locating arrays (LAs) can be used to detect and identify interaction faults among factors in a component-based system. The optimality and constructions of LAs with a single fault have been investigated extensively under the assumption that…

Satellite communications (SatComs) are anticipated to deliver global Internet access. Low Earth orbit (LEO) satellites (SATs) offer the advantage of higher downlink capacity due to their reduced link budget compared to medium Earth orbit…

Fused Lasso was proposed to characterize the sparsity of the coefficients and the sparsity of their successive differences for the linear regression. Due to its wide applications, there are many existing algorithms to solve fused Lasso.…

In the second part of the series papers, we set out to study the algorithmic efficiency of sparse sensing. Stemmed from co-prime sensing, we propose a generalized framework, termed Diophantine sensing, which utilizes generic Diophantine…

With increasing diversity in Deep Neural Network(DNN) models in terms of layer shapes and sizes, the research community has been investigating flexible/reconfigurable accelerator substrates. This line of research has opened up two…

This paper studies spatial smoothing using sparse arrays in single-snapshot Direction of Arrival (DOA) estimation. We consider the application of automotive MIMO radar, which traditionally synthesizes a large uniform virtual array by…

It was recently shown that low rank matrix completion theory can be employed for designing new sampling schemes in the context of MIMO radars, which can lead to the reduction of the high volume of data typically required for accurate target…

Sparse arrays have attracted a lot of interests recently for their capability of providing more degrees of freedom than traditional uniform linear arrays. For a mixture of circular and noncircular signals, most of the existing direction of…

This paper considers the problem of designing sparse linear tripole arrays. In such arrays at each antenna location there are three orthogonal dipoles, allowing full measurement of both the horizontal and vertical components of the received…

Extremely large-scale multi-input multi-output (XL-MIMO) is a promising technology for the sixth generation (6G) wireless networks, thanks to its superior spatial resolution and beamforming gains. In order to realize XL-MIMO…