Sparse vector coding (SVC) is emerging as a key enabler for short-packet ultrareliable and
low-latency communications (URLLCs), since it displays good block error rate (BLER) …

Sparse signal restoration is usually formulated as the minimization of a quadratic cost
function| y-Ax|| 2 2 where\mbi A is a dictionary and\mbi x is an unknown sparse vector. It is …

This chapter discusses several topics pertaining to ground truth data, the basis for computer
vision metric analysis. We look at examples to illustrate the importance of ground truth data …

For compressed sensing (CS) recovery, the reconstruction quality is highly dependent on
the sparsity level of the representation for the signal. Motivated by the observation that the …

These days, we are witnessing that numerous machine-type devices are connected to the
internet. Massive connectivity is one of the most important requirements for the next …

Sparse channel estimation is investigated for millimeter wave massive MIMO systems,
where a base station equipped with a uniform planar array serves several single-antenna …

In this paper, we introduce Hyper-Dimensional Modulation (HDM) for massive machine-type
communications (mMTC). HDM enables robust communication of short packets by …

This work presents an effective and robust methodology to achieve the joint estimation of
direction-of-arrival (DOA) and range. One or more near-field sources are the signals of …

This chapter describes the methods used to prepare images for further analysis, including
interest point and feature extraction. Some of these methods are also useful for global and …

A novel multiple-input and multiple-output (MIMO) transmission scheme termed as
generalized quadrature spatial modulation (G-QSM) is proposed. It amalgamates the …