Multistatic Integrated Sensing and Communication System Based on Macro–Micro Cooperation
Abstract
:1. Introduction
- (1)
- A multistatic ISAC system with macro–micro cooperation is proposed. The proposed system makes use of flexibly deployed microsites to perform multistatic sensing with the macrosite within the cell.
- (2)
- The deployment of microsites within the macrosite cell is investigated in terms of the channel gain for cooperative sensing.
- (3)
- An efficient approach with joint data optimization for estimating the position and velocity of sensing objects in three-dimensional (3D) environments is described.
- (4)
- The effectiveness of the proposed multistatic ISAC system is demonstrated by simulating the estimation errors for position and velocity. It is shown that the multistatic ISAC system using macro–micro cooperation can effectively improve object estimation accuracy compared to systems using macrosite cooperation alone. The microsite configuration with high-cost performance is also provided.
2. System Model
2.1. Multistatic ISAC System
2.2. Macro–Micro Cooperation
3. Microsite Deployment
3.1. Deployment in Distance Domain
3.2. Deployment in Angular Domain
3.3. Overall Algorithm
Algorithm 1 The overall algorithm for microsite deployment. |
Input: , , R, ; 1: Initialization: , , ; 2: Find by (10); 3: While (15) is not satisfied ; 4: Find by (14); 5: end While 6: Find by (16); 7: ; 8: for 9: ; 10: While (20) is not satisfied ; 11: Find by (19); 12: end While 14: end for Output: L, , , , for and ; |
4. Multistatic Sensing
4.1. Channel Parameter Estimation
4.2. Position and Velocity Estimation
4.2.1. Position Estimation
4.2.2. Velocity Estimation
Algorithm 2 The optimization method for position and velocity estimation. |
Input: , , , , ; 1: Find using (36); 2: Find , , and using and ; 3: Find using (33); 4: Find , , , , , and using in step 3; 6: Find using (41); Output: and ; |
5. Simulation Results
5.1. Microsite Deployment
5.2. Multistatic Sensing Performance
5.3. Comparison with Uniform Deployment
6. Discussion
6.1. Alternatives to Sensing Receivers
- (1)
- A CST is a passive sensing receiver that can be exclusively used for sensing. Therefore, it cannot act as a transmitter for communication functions when the sensing service is not activated, leading to wasted hardware resources. On the other hand, although the hardware cost of CSTs is lower than that of microsites, both CSTs and microsites require low-latency links, such as optical fiber, for connection to the macrosites [5]. Therefore, the construction cost for CSTs is close to that for microsites. To sum up, CSTs have the potential to take the place of microsites in multistatic ISAC systems by saving hardware costs at the expense of communication functions. This tradeoff needs to be considered in practical deployments, while the deployment analysis described in Section 3 can be directly applied to multistatic ISAC systems with CSTs.
- (2)
- UE is also an alternative to a sensing receiver. Mobile or UE-based sensing offers advantages in system extensibility, deployment cost, and implementation flexibility [43,44]. Specifically, the density of UE is much higher than that of microsites, making it more convenient to select UE closest to the targeted sensing area, while using UE as a sensing receiver almost eliminates the hardware cost for operators. However, some critical issues may arise when considering a multistatic ISAC system with UE. One issue is the synchronization between the macrosite and UE. It should be noted that a synchronization error of a few nanoseconds results in a positioning error of several meters. Therefore, difficult but stringent time and frequency offset calibrations are required. Another issue is that UE positions can drastically change, resulting in poor sensing performance. In addition, additional permission from users is needed to activate the sensing function, which may not be desired by operators. To conclude, although UE offers advantages in cost and density, some extra problems need to be addressed to improve the performance of the multistatic ISAC system.
6.2. Challenges
6.2.1. Interference
6.2.2. Practical Implementation
6.2.3. Power Consumption
7. Conclusions and Future Work
7.1. Conclusions
7.2. Future Work
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Wang, X.; Han, Z.; Jin, J.; Xi, R.; Wang, Y.; Han, L.; Ma, L.; Lou, M.; Gui, X.; Wang, Q.; et al. Multistatic Integrated Sensing and Communication System Based on Macro–Micro Cooperation. Sensors 2024, 24, 2498. https://doi.org/10.3390/s24082498
Wang X, Han Z, Jin J, Xi R, Wang Y, Han L, Ma L, Lou M, Gui X, Wang Q, et al. Multistatic Integrated Sensing and Communication System Based on Macro–Micro Cooperation. Sensors. 2024; 24(8):2498. https://doi.org/10.3390/s24082498
Chicago/Turabian StyleWang, Xiaoyun, Zixiang Han, Jing Jin, Rongyan Xi, Yajuan Wang, Lincong Han, Liang Ma, Mengting Lou, Xin Gui, Qixing Wang, and et al. 2024. "Multistatic Integrated Sensing and Communication System Based on Macro–Micro Cooperation" Sensors 24, no. 8: 2498. https://doi.org/10.3390/s24082498