Nonlinear and Inseparable Radar And Data (NIRAD) Transmission Framework for Pareto Efficient Spectrum Access in Future Wireless Networks

NSF Award Number: 2128368

Abstract

Communications and radar are two major applications of electromagnetic waves, which convey information to a destination and glean information from the environment, respectively. Historically, the two technologies were developed and operated independently, thus using different frequency spectrum bands and different hardware. Facing a scarcity of wireless spectrum resources due to the explosive growth in wireless applications, the integration of communications and radar enables sharing of spectrum and hardware, thus substantially reducing the cost and resource demands. Meanwhile, due to the lower amount of electromagnetic emissions, interference to other wireless services will also be substantially reduced. When bandwidth is saved due to the integration of communications and radar sensing, more bandwidth can be committed to each transceiver, thus achieving higher data transmission rates and finer sensing precision, or allowing more wireless devices to be able to access the spectrum. These advantages are of considerable value for applications such as Internet of Things (IoT) and cyber physical systems (CPSs), such as unmanned aerial vehicles (UAVs) and aerial access networks (AANs). The project also will fulfill an education role, including K-12 outreach, and undergraduate/graduate level course design. The findings of the proposed research will disseminated to academic and industrial communities.

This study devises a nonlinear and inseparable radar and data (NIRAD) transmission scheme, in which the functions of communications and radar sensing are integrated in the same waveform and use the same hardware. In contrast to linearly superimposed communications and radar sensing, the NIRAD scheme integrates both functions in an inseparable manner, thus allow each to fully exploit the resources of the other. When a waveform is transmitted, the electromagnetic wave brings information to the communication receiver; upon reflections, the wave brings back information for radar sensing, thus achieving both functions in the same round of transmission. When the different functions of communications and radar sensing are integrated in the same waveform and hardware, they have conflicting interests, due to their different purposes. This project discloses the trade-off between communications and radar sensing and characterizes it in an economics framework. The NIRAD technique is applicable to various practical systems, such as high-definition maps in autonomous driving, space-terrestrial communications, and reconfigurable intelligent surfaces, by improving the efficiencies of bandwidth, power and hardware. The proposed algorithms and protocols will be tested using software simulations and field experiments based on a 5G testbed.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Principal Investigators

Dr. Zhu Han

Dr. Husheng Li

Dr. H. Vincent Poor

Publications