Next-Generation Multiple Access for Integrated Sensing and Communications

Liu, Yaxi; Huang, Tianyao; Liu, Fan; Ma, Dingyou; Huangfu, Wei; Eldar, Yonina C.

doi:10.1109/jproc.2024.3449807

Proc. IEEE

2024

DOI: 10.1109/jproc.2024.3449807

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Next-Generation Multiple Access for Integrated Sensing and Communications

Yaxi Liu,

Tianyao Huang,

Fan Liu

et al.

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2024

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Cited by 2 publications

References 247 publications

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UAV-Enabled Diverse Data Collection via Integrated Sensing and Communication Functions Based on Deep Reinforcement Learning

Liu,

Li,

et al. 2024

Drones

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Unmanned aerial vehicles (UAVs) and drones are considered to represent a flexible mobile aerial platform to collect data in various applications. However, the existing data collection methods mainly consider uplink communication. The burgeoning development of integrated sensing and communication (ISAC) provides a new paradigm for data collection. A diverse data collection framework is established where the uplink communication and sensing functions are both considered, which can also be referred to as the uplink ISAC system. An optimization is formulated to minimize the data freshness indicator for communication and the detection freshness indicator for sensing by optimizing the UAV paths, the transmitted power of IoT devices and UAVs, and the transmission allocation indicators. Three state-of-the-art deep reinforcement learning (DRL) algorithms are utilized to solve this optimization. Experiments are conducted in both single-UAV and multi-UAV scenarios, and the results demonstrate the effectiveness of the proposed algorithms. In addition, the proposed algorithms outperform the benchmark in terms of accuracy and efficiency. Moreover, the effectiveness of the data collection mode with only communication or sensing functions is also verified. Also, the numerical Pareto front between communication and sensing performance is obtained by adjusting the importance parameter.

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UAV-Enabled Diverse Data Collection via Integrated Sensing and Communication Functions Based on Deep Reinforcement Learning

Liu,

Li,

et al. 2024

Drones

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Recent Trend of Rate-Splitting Multiple Access-Assisted Integrated Sensing and Communication Systems

Jang,

Kim,

Kim

et al. 2024

Electronics

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In the next-generation communication systems, multiple access (MA) will play a crucial role in achieving high throughput to support future-oriented services. Recently, rate-splitting multiple access (RSMA) has received much attention from both academia and industry due to its ability to flexibly mitigate inter-user interference in a broad range of interference regimes. Further, with the growing emphasis on spectrum resource utilization, integrated sensing and communication (ISAC) technology, which improves spectrum efficiency by merging communication and radar signals, is expected to be one of the key candidate technologies for the sixth-generation (6G) wireless networks. In this paper, we first investigate the evolution of existing MA techniques and basic principles of RSMA-assisted ISAC systems. Moreover, to make the future RSMA-assisted ISAC systems, we highlight prime technologies of 6G such as non-terrestrial networks (NTN), reconfigurable intelligent surfaces (RIS), millimeter wave (mmWave) and terahertz (THz) technologies, and vehicular-to-everything (V2X), along with the main technical challenges and potential benefits to pave the way for RSMA-assisted ISAC systems.

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Next-Generation Multiple Access for Integrated Sensing and Communications

Cited by 2 publications

References 247 publications

UAV-Enabled Diverse Data Collection via Integrated Sensing and Communication Functions Based on Deep Reinforcement Learning

UAV-Enabled Diverse Data Collection via Integrated Sensing and Communication Functions Based on Deep Reinforcement Learning

Recent Trend of Rate-Splitting Multiple Access-Assisted Integrated Sensing and Communication Systems

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