{"title":"Cooperative Sensing in Uplink ISAC System: A Multi-User Waveform Optimization Approach","authors":"Yiheng Li;Zhiqing Wei;Yi Wang;Haoming Liu;Zhiyong Feng","doi":"10.1109/TVT.2025.3548138","DOIUrl":null,"url":null,"abstract":"Integrated sensing and communication (ISAC) is expected to become a crucial component of the sixth-generation (6G) networks owing to its outstanding spectrum management capability. However, improving the cooperative sensing capabilities of multiple ISAC user equipments (ISAC-UEs) in complex interference environment presents a significant research challenge. This paper focuses on the multi-user cooperative sensing in uplink orthogonal frequency division multiplexing (OFDM) ISAC system. By utilizing the stochastic geometry, we model the distribution of communication UEs (COM-UEs) as a one-dimensional Matern hard-core point process (1-D MHCP), and derive a closed-form expression for interference power. To further enhance cooperative sensing accuracy while maintaining quality of service (QoS) in communication, we perform waveform optimization by jointly optimizing the weighted range-velocity Cramer–Rao lower bound (CRLB) subject to communication data rate (CDR) and subcarrier power ratio (SPR) constraints. This approach involves selecting the optimal subcarriers for sensing and allocating the corresponding power on each subcarrier for communication and sensing subsystems. By employing the convex relaxation and the cyclic minimization algorithm (CMA), we decompose the complex optimization problem into three sub-problems, simplifying the original NP-hard problem into a solvable one via a cyclic optimization framework. The simulation results validate the effectiveness of our optimization strategy, and evaluate the influence of CDR and SPR constraints using the CRLB and root mean square error (RMSE).","PeriodicalId":13421,"journal":{"name":"IEEE Transactions on Vehicular Technology","volume":"74 7","pages":"10943-10957"},"PeriodicalIF":7.1000,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Vehicular Technology","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10912780/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Integrated sensing and communication (ISAC) is expected to become a crucial component of the sixth-generation (6G) networks owing to its outstanding spectrum management capability. However, improving the cooperative sensing capabilities of multiple ISAC user equipments (ISAC-UEs) in complex interference environment presents a significant research challenge. This paper focuses on the multi-user cooperative sensing in uplink orthogonal frequency division multiplexing (OFDM) ISAC system. By utilizing the stochastic geometry, we model the distribution of communication UEs (COM-UEs) as a one-dimensional Matern hard-core point process (1-D MHCP), and derive a closed-form expression for interference power. To further enhance cooperative sensing accuracy while maintaining quality of service (QoS) in communication, we perform waveform optimization by jointly optimizing the weighted range-velocity Cramer–Rao lower bound (CRLB) subject to communication data rate (CDR) and subcarrier power ratio (SPR) constraints. This approach involves selecting the optimal subcarriers for sensing and allocating the corresponding power on each subcarrier for communication and sensing subsystems. By employing the convex relaxation and the cyclic minimization algorithm (CMA), we decompose the complex optimization problem into three sub-problems, simplifying the original NP-hard problem into a solvable one via a cyclic optimization framework. The simulation results validate the effectiveness of our optimization strategy, and evaluate the influence of CDR and SPR constraints using the CRLB and root mean square error (RMSE).
期刊介绍:
The scope of the Transactions is threefold (which was approved by the IEEE Periodicals Committee in 1967) and is published on the journal website as follows: Communications: The use of mobile radio on land, sea, and air, including cellular radio, two-way radio, and one-way radio, with applications to dispatch and control vehicles, mobile radiotelephone, radio paging, and status monitoring and reporting. Related areas include spectrum usage, component radio equipment such as cavities and antennas, compute control for radio systems, digital modulation and transmission techniques, mobile radio circuit design, radio propagation for vehicular communications, effects of ignition noise and radio frequency interference, and consideration of the vehicle as part of the radio operating environment. Transportation Systems: The use of electronic technology for the control of ground transportation systems including, but not limited to, traffic aid systems; traffic control systems; automatic vehicle identification, location, and monitoring systems; automated transport systems, with single and multiple vehicle control; and moving walkways or people-movers. Vehicular Electronics: The use of electronic or electrical components and systems for control, propulsion, or auxiliary functions, including but not limited to, electronic controls for engineer, drive train, convenience, safety, and other vehicle systems; sensors, actuators, and microprocessors for onboard use; electronic fuel control systems; vehicle electrical components and systems collision avoidance systems; electromagnetic compatibility in the vehicle environment; and electric vehicles and controls.