Joint Subcarrier and Power Allocation for Uplink Integrated Sensing and Communication System

Integrated sensing and communication (ISAC) supporting various emerging applications has become one of the leading technologies in sixth generation (6G) networks. This paper focuses on the uplink orthogonal frequency division multiplex (OFDM) ISAC system. With the help of multiple vehicles, the base...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE sensors journal Jg. 23; H. 24; S. 1
Hauptverfasser: Li, Yiheng, Wei, Zhiqing, Feng, Zhiyong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 15.12.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Communication
Communication Data Rate
Communications systems
Cramer-Rao Lower Bound
Cyclic Minimization Algorithm
Estimation
Integrated Sensing and Communication
Joint Subcarrier and Power Allocation
Lower bounds
Minimization
OFDM
Optimization
Orthogonal Frequency Division Multiplexing
Resource management
Sensors
Subcarriers
Subsystems
Uplink
Uplinking
ISSN:1530-437X, 1558-1748
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Integrated sensing and communication (ISAC) supporting various emerging applications has become one of the leading technologies in sixth generation (6G) networks. This paper focuses on the uplink orthogonal frequency division multiplex (OFDM) ISAC system. With the help of multiple vehicles, the base station (BS) can collect information about its surroundings through the uplink signals. Nevertheless, the rapid growth of the communication and sensing sectors has led to a growing scarcity of spectrum resources, resulting in a tradeoff between the performance of sensing and communication subsystems. To address this challenge, our paper introduces an efficient joint subcarrier and power allocation strategy for the uplink OFDM ISAC system. The critical issue is to minimize the Cramer-Rao lower bound (CRLB) by sparsely selecting the best possible sensing subcarriers and allocating the optimal transmit power to the corresponding subcarriers while satisfying the communication data rate (CDR) requirement. The resulting optimization problem is formulated as a nonconvex problem. After convex relaxation reformulation, we adopt the cyclic minimization algorithm (CMA) to iteratively solve the subcarrier selection and power allocation problems. Finally, numerical results suggest that the proposed joint optimization strategy is more effective than traditional methods.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2023.3330936