Joint Automotive MIMO-Radar-MIMO-Communications Signal Processing
Presenters
Kumar Vijay Mishra, ARL & Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg.
Bhavani Shankar M. R., Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg.
Relevant Publications
- Kumar Vijay Mishra, M. R. Bhavani Shankar, Visa Koivunen, Björn Ottersten and Sergiy A. Vorobyov, “Toward millimeter wave joint radar-communications: A signal processing perspective,” IEEE Signal Processing Magazine, vol. 36(5), pp. 100-114, 2019.
- Sayed Hossein Dokhanchi, M. R. Bhavani Shankar, Kumar Vijay Mishra and Björn Ottersten, “A mmWave automotive joint radar-communications system,” IEEE Transactions on Aerospace and Electronic Systems, vol. 55(3), pp. 1241-1260, 2019.
Abstract
Extreme crowding of the electromagnetic spectrum in recent years has led to the emergence of complex challenges in designing radar and communications systems. with the advent of novel technologies such as drone-based customer services, autonomous driving, radio-frequency identification, weather monitoring, radar systems are now deployed in urban environments and operate in bands that were earlier reserved for communications services. Similarly, with the rapid surge in mobile network operators, there is a growing concern that mobile data traffic poses a formidable challenge toward realizing future wireless networks.
Both radar and communications systems need wide bandwidth to provide a designated quality-of-service (QoS) thus resulting in competing interests in exploiting the spectrum. Hence, sharing spectral and hardware resources of communications and radar is imperative toward efficient spectrum utilization.
In particular, the automotive sector has witnessed concerted and intense efforts toward realizing these joint radar-communications (JRC) systems. A JRC model has advantages of low-cost, compact size, transportation safety due to enhanced mutual information sharing and performance optimization, spectrum sharing, and better management of inter-vehicular interference. Most of the modern automotive JRC systems operate at millimeter-wave (mm-Wave) which brings a new set of challenges and opportunities for the system engineers when compared with centimeter-wave JRC. This band is characterized by severe penetration losses, short coherence times, and availability of wide bandwidth. While wide bandwidth is useful in attaining high vehicular communications data rates and high-resolution automotive radar, the losses must be compensated by using massive multiple-input multiple-output (MIMO) processing which employs a large number of antennas at the transmitter and receiver. There is, therefore, a surge in research on joint MIMO-Radar-MIMO-Communications (MRMC) systems.
As one of the spectrum-efficient technologies, MIMO has proven to be advantageous in detection and estimation in both radars and communications. MIMO systems employ several antennas for transmission and reception. In wireless communications, MIMO configuration enhances the capacity, provides spatial diversity, and exploits multipath propagation. Further, recent developments in massive MIMO have demonstrated that uplink/downlink (UL/DL) channel reciprocity can be exploited by deploying a very large number of service antennas to serve a lower number of mobile users with the time-division-duplexing (TDD). Similarly, MIMO radars offer capabilities that outweigh an equivalent, standard phased array radar such as higher angular resolution, spatial diversity, adaptable antennas, and improved parameter identifiability. The angular resolution of MIMO radar is the same as a virtual uniform linear phased array (ULA) with the same antenna aperture but many more antennas than MIMO. However, unlike a phased array radar, each of the MIMO transmitters emits a different, mutually orthogonal – in time, frequency, or code – probing signal.
Apart from MIMO, several signal processing, and digital communication techniques are critical in the implementation of mm-Wave JRC. Major challenges are joint waveform design and performance criteria that would optimally trade-off between communications and radar functionalities. Constraints on the low-power consumption and implementation friendly designs are sought, while robust radar and communication receive processing to perform respective tasks need to be implemented. There are opportunities to exploit recent advances in cognition, compressed sensing, and machine learning to reduce required resources and dynamically allocate them with low overheads. In this tutorial, we give an overview of these challenges while focusing on mm-Wave JRC and MRMC.
Click on video to see the presentation!
