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Power Allocation for Massive MIMO-ISAC Systems
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AI
DOI：10.1109/TWC.2024.3410385.png)
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摘要
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Arrays with a large number of antennas can achieve outstanding performance for both communication and radar sensing. This motivates us to investigate the transmit beamforming design for massive multiple-input multiple-output integrated sensing and communications (mMIMO-ISAC) systems. Inspired by the facts that linear precoding methods can provide very good performance in mMIMO and that a dual-function ISAC transmit beamformer should be suitable for both communication and radar sensing, we propose an implementation-friendly mMIMO-ISAC transmit beamformer as a weighted combination of a linear precoder and a pre-designed array beamformer. The weights are selected and adjusted through the powers allocated to the beamformers, while the design problem is formulated as a total transmit power minimization, while satisfying the requirements for both sensing and communication. Leveraging the use-and-then-forget strategy, simplified performance metrics for communication and sensing under the proposed mMIMO-ISAC transmit model are derived, which yields linear programming (LP) problems for the design. It is shown that analytical solutions can be obtained and, hence, the proposed design is computationally very attractive. Simulations are carried out to demonstrate the effectiveness and performance of the proposed methods.
Keyword:
Array signal processing
Radar
Channel estimation
Signal to noise ratio
Wireless communication
Precoding
Interference
Integrated sensing and communications (ISAC)
massive multiple-input multiple-output (mMIMO)
power allocation
transmit beamforming
期刊
IF:
10.7
论文数:
1.3W
被引数:
5.3W
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