mmWave/THz ISAC
1. Radio SLAM
5G millimeter wave (mmWave) signals can enable accurate positioning in vehicular networks when the base station (BS) and vehicles are equipped with large antenna arrays. However, radio-based positioning suffers from multipath signals generated by different types of objects in the physical environment. Multipaths can be turned into a benefit by building up a radio map (comprising the number of objects, object type, and object state) and using this map to exploit all available signal paths for positioning. Mapping and positioning using 5G can be categorized as a simultaneous localization and mapping (SLAM) problem.
Fig. 1. 5G SLAM scenario with the propagation environment and two vehicles.
Fig. 1 shows the 5G SLAM scenario, where 5G communication links can be used to share measurements, map, or location information, leading to cooperative positioning and mapping. In 5G mmWave cooperative positioning and mapping (i.e., positioning and mapping based on measurements from 5G mmWave communication signals), there are three main tasks: (i) Vehicle positioning: determine the states (position, velocity, heading, clock bias) of the vehicles; (ii) Environment mapping: estimate the number of objects, as well as each object’s type and position; and (iii) Cooperation: in the BS fusing the collected the map information from the vehicles, and relay it to each vehicle. As shown in Fig. 2 below, the mapping of landmarks is achieved quickly by the cooperation between the BS and vehicles.
Fig. 2. Mapping accuracy of 5G SLAM without cooperation (left) and with cooperation (right).
<Video represents real-time 5G SLAM procedure>
One of Integrated sensing and communication's (ISAC's) most essential uses, SLAM, is gaining traction. SLAM is a technique that obtains environmental information of an environment without previous knowledge and simultaneously locates a user; as it needs a huge volume of various types of high-precision data measurement, it is necessary to implement ISAC based on mmWave and THz [1, 2]. As shown in Fig. 3, we propose a SLAM method that maps arbitrary-shaped objects using mmWave/THz-based radio SLAM and achieves high-precision user location. The proposed SLAM technique detects the types of a number of objects in the radio wave environment, classifies each object to perform environment mapping, and utilizes this mapping information to improve the positioning accuracy of the user.
Fig. 3. An illustration of the 6G SLAM
[Related publications]
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H. Kim, K. Granström, L. Gao, G. Battistelli, S. Kim and H. Wymeersch, “5G mmWave Cooperative Positioning and Mapping using Multi-Model PHD Filter and Map Fusion,” IEEE Trans. Wireless Commun., vol. 19, no. 6, pp. 3782-3795, Jun. 2020.
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J. Lee, H. Kim, H. Wymeersch and S. Kim, “Dirichlet Process Clustering-based Radio SLAM with Arbitrarily-Shaped Reflectors,” in Proc. 3rd IEEE Int. Symp. Joint Commun. Sens. (JC&S), Mar. 2023.
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J. Lee, H. Park and S. Kim “Leveraging Near-field Effect for Environment Mapping: Radio-SLAM on THz Communication Systems,” in Proc. 2023 The 8th IEEE Int. Conf. Network Intelligence and Digital Content (IC-NIDC), Beijing, China, Nov. 2023.
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J. Lee, H. Park, H. Chung and S. Kim, "Radio SLAM with Hybrid Sensing for Mixed Reflection Type Environments," in Proc. 2024 IEEE Int. Conf. Acoust, Speech, Signal Process. (ICASSP), Apr. 2024.
2. Sensing and Communication time optimization
Integrated sensing and communication (ISAC) is a new paradigm in which previously competing for sensing and communication tasks can be jointly optimized. In future 6G systems, higher-frequency(mmWave to THz), wider bandwidths, and denser large-scale antenna arrays provide an opportunity to integrate wireless signal sensing and communication into a single system and the entire communication system to act as a sensor. Context information (localization, imaging, environment reconstruction, etc) obtained from sense can help improve communication performance, such as high-precision beamforming and less overhead channel state information (CSI) acquisition.
In the ISAC system, reducing or optimizing bi-static sensing/channel estimation overhead is a critical challenge to improve the data rate in mmWave/THz communication [1]. As shown in Fig. 4, we propose a scheme optimizing the per-user channel sensing duration in multi-user multiple-input single-output (MU-MISO) systems. For each user, the BS predicts the effective rate to be achieved after pilot transmission. Then, the channel sensing duration of each user is optimized by ending the pilot transmission when the predicted rate is lower than the current rate.
Fig. 4. An illustration of the optimizing channel sensing duration in the ISAC system
[Related publication]
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J. Kang, H. Wymeersch, C. Fischione, G. Seco-Grandos, and S. Kim, “Optimized Switching Between Sensing and Communication for mmWave MU-MISO Systems,” accepted to 2022 IEEE Inter. Conf. Commun. Workshops (ICC Workshops), Mar. 2022.