具有 1 位 DAC 的 ISAC 系统性能分析
Performance Analysis for ISAC Systems with 1-bit DACs
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中文总结 AI 辅助
研究低分辨率量化对 ISAC 系统影响，提出分析与设计框架。推导感知信噪比表达式，给出两种设计满足通信和感知要求发射波形的方法，通过数值模拟验证方法性能，展现不同方法间复杂度 - 性能权衡。
中文摘要 AI 辅助
低分辨率量化限制了多输入多输出（MIMO）系统可实现的最大增益。虽然通信系统中低分辨率量化的不利影响和缓解策略已得到充分分析，但现有文献对其在综合感知与通信（ISAC）系统中的影响探索不足。本文提出一个分析与设计框架，用于研究和减轻 1 位数模转换器（DAC）对 ISAC 系统的影响。首先，利用布斯冈分解推导了感知信噪比（SNR）的解析表达式。此外，提出两种不同方法来设计同时满足通信和感知要求的发射波形。第一种方法使用单独的常数模（CM）感知信号，因为 CM 信号对非线性失真比正交频分复用（OFDM）调制信号更鲁棒。第二种方法采用无穷范数平方道格拉斯 - 拉赫福德分裂（SQUID）方法，通过非线性量化预编码构建发射波形。最后，通过数值模拟验证了所提方法的性能，以表明两种不同方法之间的复杂度 - 性能权衡。
英文摘要
Low-resolution quantization constrains the maximum achievable gains of multiple-input multiple-output (MIMO) systems. While the adverse effects and mitigation strategies have been thoroughly analyzed for communication systems, the impact of low-resolution quantization on integrated sensing and communication (ISAC) systems remains insufficiently explored in the existing literature. In this paper, we propose an analysis and design framework to investigate and mitigate the effects of 1-bit digital to analog converters (DACs) for ISAC systems. Firstly, an analytical sensing signal-to-noise ratio (SNR) expression is derived by using the Bussgang decomposition. Furthermore, two different methodologies are proposed to design a transmit waveform that satisfies both communication and sensing requirements simultaneously. The first method uses a separate constant modulus (CM) sensing signal since CM signals are known to be more robust to nonlinear distortion than orthogonal frequency division multiplexing (OFDM) modulated signals. The second method employs the squared-infinity norm Douglas-Rachford splitting (SQUID) approach to construct the transmit waveform using nonlinear quantized precoding. Finally, the performance of the proposed methods are validated via numerical simulations to indicate the complexity-performance tradeoff between two different methods.
