Sensing capability is one of the most highlighted new feature future 6G wireless networks. This paper addresses sensing potential Large Intelligent Surfaces (LIS) in an exemplary Industry 4.0 scenario. Besides attention received by LIS terms communication aspects, it can offer a high-resolution rendering propagation environment. because, indoor setting, be placed proximity to sensed phenomena, ...

We address the problem of detecting ‘‘anomalies’’ in the network traffic produced by a large population of end-users following a distribution-based change detection approach. In the considered scenario, different traffic variables are monitored at different levels of temporal aggregation (timescales), resulting in a grid of variable/timescale nodes. For every node, a set of per-user traffic cou...

This paper considers adaptive detection and steering estimation in the presence of useful signal and interference mismatches. We assume a homogeneous environment where the random disturbance components from the primary and secondary data share the same covariance matrix. Moreover the data under test contains a deterministic interference vector in addition to the possible useful signal. We focus...

This paper considers noncoherent communication over a frequency nonselective channel in which the time-varying channel gain is unknown a priori, but is approximately constant over a coherence interval. Unless the coherence interval is large, coherent communication, which requires explicit channel estimation and tracking prior to detection, incurs training overhead which may be excessive, especi...

In this study, the authors address the problem of multiple antenna spectrum sensing in cognitive radios by exploiting the prior information about unknown parameters. Specifically, under assumption that unknown parameters are random with the given proper distributions, the authors use a Bayesian generalised likelihood ratio test (B-GLRT) in order to derive the corresponding detectors for three d...