The linear inverse problem is fundamental to the development of various scientific areas.
Innumerable attempts have been carried out to solve different variants of the linear inverse …

This paper attempts to identify the requirement and the development of machine learning‐
based mobile big data (MBD) analysis through discussing the insights of challenges in the …

Due to the booming of various devices in Internet-of-Things (IoT) networks, more data
should be transmitted over the networks, which will thereby consume more transmission …

In this paper, we consider the problem of hybrid precoding and combining for wideband
millimeter wave (mmWave) and sub-terahertz (THz) MIMO-OFDM systems with beam squint …

The great success of deep learning (DL) has inspired researchers to develop more accurate
and efficient symbol detectors for multi-input multi-output (MIMO) systems. Existing DL …

Wireless communication systems to date primarily rely on the orthogonality of resources to
facilitate the design and implementation, from user access to data transmission. Emerging …

To support massive connectivity for sporadically active devices is a challenging task, as the
randomness of the channel and the large number of users lead to enormous increase of …

Many real-world problems involve the recovery of a matrix from linear measurements, where
the matrix lies close to some low-dimensional structure. This paper considers the problem of …

Nowadays, the rapid development of artificial intelligence (AI) provides a fresh perspective
in designing future wireless communication systems. Innumerable attempts exploiting AI …

Wideband spectrum sensing is regarded as one of the key functional blocks in cognitive
radio systems, where compressive sensing (CS) has become one of the promising …