Wireless | NYU Tandon School of Engineering


We make major leaps in wireless

wireless tower

We make millimeter waves as ubiquitous as microwaves

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Electrical engineer Ernst Weber’s work with electromagnetic waves in the microwave region of the radio spectrum was vital to U.S. radar systems during World War II, and in 1945 he founded our school’s highly regarded Microwave Research Institute. A few decades later, microwave ovens could be found in almost every home.

Ted Rappaport
David Lee/Ernst Weber Professor Theodore “Ted” Rappaport 

In 2013, Theodore “Ted” Rappaport — David Lee/Ernst Weber Professor of Electrical Engineering, Founding Director of NYU WIRELESS, Professor of Computer Science at NYU Courant, Professor of Radiology at NYU School of Medicine — published a seminal article on the possibilities of the millimeter-wave (mmwave) spectrum, paving the way for the powerful cell phones and other wireless devices most of us use today.

Now, Rappaport, who was elected to the National Academy of Engineering (NAE) this year, and his colleagues are exploring what comes next.

We make 6G a not-so-distant reality

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There’s no question: the fundamental research that made 5G possible involves massive MIMO (multiple-input multiple-output) and mmWave technologies. Without them, there would be no 5G network as we now know it.

Thomas Marzetta
Distinguished Industry Professor Thomas Marzetta

Rappaport served as the key thought leader for 5G by planting the flag in the ground nearly a decade ago, arguing that mmWave would be a key enabling technology for the next generation of wireless. Distinguished Industry Professor Thomas Marzetta, the current director of NYU Wireless, was the scientist who led the development of massive MIMO while he was at Bell Labs and has championed its use since. (Marzetta was elected to the NAE in 2020.)

These two researchers, who were so instrumental in developing the technologies that have enabled 5G, are now turning their attention to the next generation of mobile communications — 6G and beyond.

The world is taking notice: Rappaport and Marzetta recently appeared on the Clarivate Analytics Highly Cited Researcher list, which recognizes true pioneers in their fields over the last decade, demonstrated by the production of papers that rank in the top 1% by citations for field and year. Of the world’s scientists, Clarivate™ Highly Cited Researchers are truly one in 1,000.

We take a deep dive into deep learning

Wireless, Data Science/AI/Robotics, Sustainability

Increasing amounts of data are now being collected on mobile and internet-of-things (IoT) devices. Researchers are interested in analyzing this data to extract actionable information for such purposes as identifying objects of interest from high-resolution mobile phone pictures. The state-of-the-art technique for that data analysis employs deep learning, which makes use of sophisticated software algorithms modeled on the functioning of the human brain. Deep learning algorithms are, however, too complex to run on small, battery-constrained mobile devices, and the alternative — transmitting data to the mobile base station where the deep learning algorithm can be executed on a powerful server — consumes too much bandwidth.

Now, Professor Yao Wang and Institute Professor Elza Erkip of Tandon’s Department of Electrical and Computer Engineering and NYU WIRELESS, along with Institute Associate Professor of Electrical and Computer Engineering Siddarth Garg, are seeking to devise new methods to compress data before transmission, thus reducing bandwidth costs while still allowing for the data to be analyzed at the base station. Departing from existing data compression methods optimized for reproducing the original images, the team is developing a means of using deep learning itself to compress the data in a fashion that only keeps the critical parts of data necessary for subsequent analysis. The resulting deep learning-based compression algorithms will be simple enough to run on mobile devices while drastically reducing the amount of data that needs to be transmitted to mobile base stations for analysis, without significantly compromising the analysis performance. The research will provide greater capability and functionality to mobile device users, enable extended battery lifetimes, and promote more efficient sharing of the wireless spectrum for analytics tasks. It’s a wireless win for all.

We make waves in the world of 6G

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A layperson might not fully understand the title of Shihao Ju’s latest paper, “Millimeter Wave and Sub-Terahertz Spatial Statistical Channel Model for an Indoor Office Building,” (published in the IEEE Journal on Selected Areas in Communications special issue on Terahertz Communications and Networking), but it’s easy to understand the promise his work holds for the development of 6G wireless communications and the drive and determination that propelled him to NYU Tandon.


The most important factor in my choosing to come to Tandon is that it’s home to the NYU WIRELESS research center, which is known all over the world. Professor Ted Rappaport, who launched the center in 2012, is among the most highly respected figures in the field. He is the author of the paper “Millimeter Wave Mobile Communications for 5G Cellular: It Will Work,” which pioneered the idea of tapping the underutilized spectrum between 30 to 300 Gigahertz for 5G radio and beyond, at a time when few other experts were even considering the possibility. I admired him so much as a scientific pioneer that I wrote to him, and he encouraged me to apply to Tandon.

My most recent paper was written in collaboration with fellow graduate students Yunchou Xing and Ojas Kanhere, under the direction of Professor Rappaport. In it, we discuss the fact that sixth-generation (6G) wireless systems will need to offer unprecedented high data rate and system throughput, which can be achieved in part by deploying systems transmitting and receiving at millimeter-wave (mmWave) and Terahertz (THz) frequencies (30 GHz - 3 THz). These regions of the electromagnetic spectrum are capable of massive data throughput at near zero latency, which is key to future data traffic demand created by wireless applications like augmented/virtual reality (AR/VR), autonomous driving, and remote medicine.

Importantly, the linchpin for the successful deployment of mmWave and THz systems for 6G wireless communications will be their performance in indoor scenarios, so accurate THz channel characterization for indoor environments is essential in designing transceivers, air interface, and protocols for 6G, and even beyond. We propose a unified indoor channel model across mmWave and sub-THz bands based on our measurements, and we hope this can serve as a reference for future standards development above 100 GHz.”

Ju is now planning to conduct channel measurements at mmWave and sub-THz frequencies in indoor factories next, making him just one of the Tandon researchers seeking to transform manufacturing. He explains that factories in the manufacturing industry are becoming the hottest and most significant application scenario for 5G and beyond. With advanced wireless technologies, smart factories will one day be enabled to reduce the cost and dramatically improve productivity