Optimal Precoder Design for MIMO-OFDM-based Joint Automotive Radar-Communication Networks
Large-scale deployment of connected vehicles with cooperative awareness technologies increases the demand for vehicle-to-everything (V2X) communication spectrum in 5.9 GHz that is mainly allocated for the exchange of safety messages. To supplement V2X communication and support the high data rates ne...
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| Veröffentlicht in: | 2021 19th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) S. 1 - 8 |
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| Sprache: | Englisch |
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18.10.2021
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| Abstract | Large-scale deployment of connected vehicles with cooperative awareness technologies increases the demand for vehicle-to-everything (V2X) communication spectrum in 5.9 GHz that is mainly allocated for the exchange of safety messages. To supplement V2X communication and support the high data rates needed by broadband applications, the millimeter-wave (mmWave) automotive radar spectrum at 76-81 GHz can be utilized. For this purpose, joint radar-communication systems have been proposed in the literature to perform both functions using the same waveform and hardware. While multiple-input and multiple-output (MIMO) communication with multiple users enables independent data streaming for high throughput, MIMO radar processing provides high-resolution imaging that is crucial for safety-critical systems. However, employing conventional precoding methods designed for communication generates directional beams that impair MIMO radar imaging and target tracking capabilities during data streaming. In this paper, we propose a MIMO joint automotive radar-communication (JARC) framework based on orthogonal frequency division multiplexing (OFDM) waveform. First, we show that the MIMO-OFDM preamble can be exploited for both MIMO radar processing and estimation of the communication channel. Then, we propose an optimal precoder design method that enables high accuracy target tracking while transmitting independent data streams to multiple receivers. The proposed methods provide high-resolution radar imaging and high throughput capabilities for MIMO JARC networks. Finally, we evaluate the efficacy of the proposed methods through numerical simulations. |
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| AbstractList | Large-scale deployment of connected vehicles with cooperative awareness technologies increases the demand for vehicle-to-everything (V2X) communication spectrum in 5.9 GHz that is mainly allocated for the exchange of safety messages. To supplement V2X communication and support the high data rates needed by broadband applications, the millimeter-wave (mmWave) automotive radar spectrum at 76-81 GHz can be utilized. For this purpose, joint radar-communication systems have been proposed in the literature to perform both functions using the same waveform and hardware. While multiple-input and multiple-output (MIMO) communication with multiple users enables independent data streaming for high throughput, MIMO radar processing provides high-resolution imaging that is crucial for safety-critical systems. However, employing conventional precoding methods designed for communication generates directional beams that impair MIMO radar imaging and target tracking capabilities during data streaming. In this paper, we propose a MIMO joint automotive radar-communication (JARC) framework based on orthogonal frequency division multiplexing (OFDM) waveform. First, we show that the MIMO-OFDM preamble can be exploited for both MIMO radar processing and estimation of the communication channel. Then, we propose an optimal precoder design method that enables high accuracy target tracking while transmitting independent data streams to multiple receivers. The proposed methods provide high-resolution radar imaging and high throughput capabilities for MIMO JARC networks. Finally, we evaluate the efficacy of the proposed methods through numerical simulations. |
| Author | Wang, Chang-Heng Altintas, Onur Ozkaptan, Ceyhun D. Ekici, Eylem |
| Author_xml | – sequence: 1 givenname: Ceyhun D. surname: Ozkaptan fullname: Ozkaptan, Ceyhun D. email: ozkaptan.1@osu.edu organization: The Ohio State University,Dept. of Electrical and Computer Engineering,Columbus,OH,USA – sequence: 2 givenname: Eylem surname: Ekici fullname: Ekici, Eylem email: ekici.2@osu.edu organization: The Ohio State University,Dept. of Electrical and Computer Engineering,Columbus,OH,USA – sequence: 3 givenname: Chang-Heng surname: Wang fullname: Wang, Chang-Heng email: chang-heng.wang@toyota.com organization: Toyota Motor North America,InfoTech Labs,Mountain View,CA,USA – sequence: 4 givenname: Onur surname: Altintas fullname: Altintas, Onur email: onur.altintas@toyota.com organization: Toyota Motor North America,InfoTech Labs,Mountain View,CA,USA |
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| SubjectTerms | Imaging Measurement MIMO radar OFDM Radar imaging Streaming media Target tracking |
| Title | Optimal Precoder Design for MIMO-OFDM-based Joint Automotive Radar-Communication Networks |
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