7 accepted papers
Federated learning (FL) has attracted great attention lately due to many advantages it provides. The community has noted that FL performance can be greatly degraded by heterogeneous data or any data that is unsuitable for the learning problem under consideration. Here we focus on the gradient descen…
Target velocity estimation is investigated for a cooperative multiple-input multiple-output (MIMO) integrated radar and communications (IRC) system employing quantized measurements. To reduce the communications burden, the local receivers quantize the local measurements, and then transmit the quanti…
In this work, we study coexisting MIMO radar and MIMO communication systems, where the two systems work cooperatively. The radar shares its antenna positions and transmitted signals with the communication system. The communication system informs the radar about the antenna locations, as well as the…
This paper studies reduced complexity target detection using multiple-input-multiple-output (MIMO) radar with lower complexity. To reduce either hardware or software complexity, some parts of the test statistic are eliminated in the proposed method. For the general case where clutter-plus-noise and…
Estimation of an unknown deterministic vector from quantized sensor data is considered in the presence of spoofing and man-in-the-middle attacks. First, asymptotically optimum processing, which identifies and categorizes the attacked sensors into different groups according to distinct types of attac…
In modern heterogeneous sensor networks huge volumes of information rapidly flow across the system, and it is often too difficult or costly to associate data to the sensors that produced them. Then, the set of observations appears to be unlabeled: What comes from whom? We study the classical problem…
State estimation of a power grid under undetected power injection attacks is considered. With a known prior probabilistic description of the state variables, the maximum a posteriori probability (MAP) estimator is adopted. Undetected attacks lead to model mismatch, which may greatly degrade the esti…