SPS Newsletter Article

In past decades, conventional communication primarily focused on how to accurately and effectively transmit symbols, which is categorized as the first level of communications by Shannon and Weaver. With the developments of cellular communication systems, the achieved transmission rate is gradually approaching to the Shannon limit. 

As the standardization of 5G gradually solidifies, researchers are speculating what 6G will be. One common theme is that radio sensing functionality would be integrated into 6G networks in a low-cost and fast manner. 

Practically anyone can now generate a realistic-looking deepfake video. Many methods to detect deepfakes were recently proposed by the research community. However, it is still unclear how realistic deepfake videos are for an average person and whether the algorithms are significantly better than humans at detecting them.

Neuro-imaging is safe and non-invasive, which is widely used in the early diagnosis and prediction of Alzheimer's disease, Parkinson's disease, Autism and other brain diseases. With the rapid development of intelligent computing technology, it is possible to use neuro-imaging data for intelligent diagnosis of brain diseases.

Over the past fifteen years, “cognition” has emerged as an enabling technology for incorporating learning and adaptivity on both transmit and receive to optimize or make more robust the radar performance in dynamic environments.The term ‘cognitive radar’ was introduced for the first time by Dr. Simon Haykin in 2006, but the foundations of the cognitive systems date back several decades to research on knowledge-aided signal processing, and adaptive radar design.

Substantial progress has been made recently on developing provably accurate and efficient algorithms for low-rank matrix factorization via nonconvex optimization. While conventional wisdom often takes a dim view of nonconvex optimization algorithms due to their susceptibility to spurious local minima, simple iterative methods such as gradient descent have been remarkably successful in practice. 

This webinar, part of the new IEEE JSTSP webinar series on recent special issues (Sis), will overview the Joint Communication and Radar Sensing (JCR) for Emerging Applications. The webinar will start with a brief motivation of the area of JCR, followed by a summary of the technical papers that appear in the SI.

Elisa Konofagou is the Robert and Margaret Hariri Professor of Biomedical Engineering and Professor Radiology as well as Director of the Ultrasound and Elasticity Imaging Laboratory at Columbia. Her main interests are in the development of novel elasticity imaging techniques and therapeutic ultrasound methods.

MIMO communication remains an important technology for wireless communication systems. In this tutorial, we revisit classical signal processing models for MIMO wireless communications. We consider how those models may be updated as MIMO systems go to higher carrier frequencies, broader bandwidths and new kinds of array architectures.

In this talk, we investigate the model-driven deep learning for multiple input-multiple output (MIMO) detection. In particular, the MIMO detector is specially designed by unfolding an iterative algorithm and adding some trainable parameters.