Cross-Domain Dual-Functional OFDM Waveform Design for Accurate Sensing/Positioning

被引:1
|
作者
Zhang, Fan [1 ]
Mao, Tianqi [2 ,3 ]
Liu, Ruiqi [4 ,5 ]
Han, Zhu [6 ,7 ]
Chen, Sheng [8 ]
Wang, Zhaocheng [1 ]
机构
[1] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China
[2] Beijing Inst Technol Zhuhai, Zhuhai 519088, Peoples R China
[3] Beijing Inst Technol, MIIT Key Lab Complex FieldIntelligent Sensing, Beijing 100081, Peoples R China
[4] ZTE Corp, Wireless & Comp Res Inst, Beijing 100029, Peoples R China
[5] State Key Lab Mobile Network & Mobile Multimedia, Shenzhen 518055, Peoples R China
[6] Univ Houston, Dept Elect & Comp Engn, Houston, TX 77004 USA
[7] Kyung Hee Univ, Dept Comp Sci & Engn, Seoul 446701, South Korea
[8] Univ Southampton, Sch Elect & Comp Sci, Southampton SO17 1BJ, England
基金
中国国家自然科学基金; 日本科学技术振兴机构;
关键词
Sensors; OFDM; Radar; Resource management; Symbols; Antenna arrays; Time-frequency analysis; Positioning and sensing; dual-functional radar and communication (DFRC); integrated sensing and communication (ISAC); orthogonal frequency division multiplexing (OFDM); cross-domain waveform design; ambiguity function; JOINT RADAR; POWER ALLOCATION; COMMUNICATION; CONVERGENCE; SUBCARRIER; SEQUENCES;
D O I
10.1109/JSAC.2024.3414001
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Orthogonal frequency division multiplexing (OFDM) has been widely recognized as the representative waveform for 5G wireless networks, which can directly support sensing/positioning with existing infrastructure. To guarantee superior sensing/positioning accuracy while supporting high-speed communication simultaneously, the dual functions tend to be assigned with different resource elements (REs) due to their diverse design requirements. This motivates optimization of resource allocation/waveform design across time, frequency, power and delay-Doppler domains. Therefore, this article proposes two cross-domain waveform optimization strategies for effective convergence of OFDM-based communication and sensing/positioning, following communication- and sensing-centric criteria, respectively. For the communication-centric design, to maximize the achievable data rate, a fraction of REs are optimally allocated for communication according to prior knowledge of the communication channel. The remaining REs are then employed for sensing/positioning, where the sidelobe level and peak-to-average power ratio are suppressed by optimizing its power-frequency and phase-frequency characteristics for sensing performance improvement. For the sensing-centric design, a 'locally' perfect auto-correlation property is ensured for accurate sensing and positioning by adjusting the unit cells of the ambiguity function within its region of interest (RoI). Afterwards, the irrelevant cells beyond RoI, which can readily determine the sensing power allocation, are optimized with the communication power allocation to enhance the achievable data rate. Numerical results demonstrate the superiority of the proposed waveform designs.
引用
收藏
页码:2259 / 2274
页数:16
相关论文
共 50 条
  • [31] A Receiver Architecture For Dual-Functional Massive MIMO OFDM RadCom Systems
    Temiz, Murat
    Alsusa, Emad
    Danoon, Laith
    2020 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS), 2020,
  • [32] DenseSENet: more accurate and robust cross-domain iris recognition
    Chen, Ying
    Zeng, Zhuang
    Zeng, Yugang
    Gan, Huimin
    Chen, Huiling
    JOURNAL OF ELECTRONIC IMAGING, 2021, 30 (06)
  • [33] A Dual-Functional Massive MIMO OFDM Communication and Radar Transmitter Architecture
    Temiz, Murat
    Alsusa, Emad
    Baidas, Mohammed W.
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (12) : 14974 - 14988
  • [34] Dual geometric perception for cross-domain road segmentation
    Zou, Wenbin
    Long, Ruijing
    Zhang, Yuhang
    Liao, Muxin
    Zhou, Zhi
    Tian, Shishun
    DISPLAYS, 2023, 76
  • [35] Dual-Target Cross-Domain Bundle Recommendation
    Zhang, Tao
    Han, Yani
    Dong, Xuewen
    Xu, Yang
    Shen, Yulong
    2021 IEEE INTERNATIONAL CONFERENCE ON SERVICES COMPUTING (SCC 2021), 2021, : 183 - 192
  • [36] Cross-domain Recommendation via Dual Adversarial Adaptation
    Su, Hongzu
    Li, Jingjing
    Du, Zhekai
    Zhu, Lei
    Lu, Ke
    Shen, Heng Tao
    ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2024, 42 (03)
  • [37] Bridging cross-domain terminology for biomimetic design
    Chiu, I.
    Shu, L. H.
    PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, VOL 5, 2005, : 93 - 101
  • [38] Design and implementation of cross-domain cooperative firewall
    Cheng, Jerry
    Yang, Hao
    Wong, Starsky H. Y.
    Zerfos, Petros
    Lu, Songwu
    2007 IEEE INTERNATIONAL CONFERENCE ON NETWORK PROTOCOLS, 2007, : 284 - +
  • [39] Design and implementation of a gliding cross-domain vehicle
    Zou, Yucheng
    You, Chenxi
    Tan, Xiangkui
    Wang, Yiwei
    Wang, Jingzhu
    Li, Chaohui
    He, Ming
    Lv, Kai
    Zou, Yong
    Song, Huaitong
    Lv, Pengyu
    Li, Hongyuan
    OCEAN ENGINEERING, 2023, 280
  • [40] A Deep Dual Adversarial Network for Cross-Domain Recommendation
    Zhang, Qian
    Liao, Wenhui
    Zhang, Guangquan
    Yuan, Bo
    Lu, Jie
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2023, 35 (04) : 3266 - 3278