Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Simulation-Based Power Allocation for Integrated Sensing and Communication Systems Balancing Communication Capacity and Target Detection. |
| Συγγραφείς: |
Zhao S; School of Traffic and Electrical Engineering, Dalian University of Science and Technology., Sheng H; School of Railway Intelligent Engineering, Dalian Jiaotong University; shenghu2026@outlook.com. |
| Πηγή: |
Journal of visualized experiments : JoVE [J Vis Exp] 2026 Sep 11 (235). Date of Electronic Publication: 2026 Sep 11. |
| Τύπος έκδοσης: |
Journal Article; Video-Audio Media; Research Support, Non-U.S. Gov't |
| Γλώσσα: |
English |
| Στοιχεία περιοδικού: |
Publisher: MYJoVE Corporation Country of Publication: United States NLM ID: 101313252 Publication Model: Electronic Cited Medium: Internet ISSN: 1940-087X (Electronic) Linking ISSN: 1940087X NLM ISO Abbreviation: J Vis Exp Subsets: MEDLINE |
| Imprint Name(s): |
Original Publication: [Boston, Mass. : MYJoVE Corporation, 2006]- |
| Ιατρικοί όροι (MeSH): |
Algorithms* , Computer Simulation* |
| Περίληψη: |
Integrated Sensing and Communication (ISAC) systems require efficient power allocation to balance communication quality and sensing performance while operating under limited spectrum and power resources. Conventional equal power allocation methods often fail to achieve an effective trade-off between communication channel capacity and target detection probability (PDP) because they do not adequately account for the different objectives of communication and sensing. This study proposes a simulation-based power allocation strategy for an Orthogonal Frequency Division Multiplexing (OFDM)-based ISAC system using a normalized multi-objective optimization framework. An improved Butterfly Optimization Algorithm (BOA), incorporating Dynamic Switching Probability and Dynamic Variance Gaussian Mutation strategies, is employed to enhance global search capability, convergence speed, and solution diversity. Numerical simulations were performed under different communication weighting factors, antenna configurations, subcarrier numbers, and signal-to-noise ratios to evaluate the proposed approach. The optimized strategy achieved improved convergence behavior while providing a balanced compromise between communication channel capacity and PDP across multiple simulation scenarios. These findings demonstrate that the proposed optimization framework can effectively support simulation-based resource allocation for OFDM-based ISAC systems while providing a reproducible methodology for evaluating communication-sensing trade-offs under different operating conditions. |
| Entry Date(s): |
Date Created: 20260912 Date Completed: 20260912 Latest Revision: 20260914 |
| Update Code: |
20260915 |
| DOI: |
10.3791/71261 |
| PMID: |
42730645 |
| Βάση Δεδομένων: |
MEDLINE |