AI 中文总结
针对带限加性高斯白噪声信道的电平约束信号传输问题，采用概率时域成形推导新容量下界，最优成形密度满足可逆性要求，两种PTS方案分别实现1.94 dB和1.64 dB的高信噪比增益。
AI 中文摘要
电平约束对实字母连续时间信道上的1比特量化信号传输进行建模。本文采用概率时域成形（PTS）推导带限加性高斯白噪声信道在电平约束输入下容量的新下界。针对奈奎斯特速率采样下每个信号有一次数据相关符号变化的情况，推导最优成形密度，确保满足可逆性要求。计算表明，在高信噪比（SNR）下，PTS将现有最优下界至少提升1.94 dB；更简单的序贯PTS方案在高SNR下实现1.64 dB的增益。
英文摘要
Level-constraints model one-bit-quantized signaling over real-alphabet continuous-time channels. New lower bounds on the capacity of bandlimited, additive white Gaussian noise channels with level-constrained inputs are derived by using probabilistic temporal shaping (PTS). The optimal shaping density is derived for signals with one data-dependent sign change per Nyquist-rate sample, which ensures they satisfy an invertibility requirement. Calculations show that PTS improves the best existing lower bound by at least 1.94 dB at high signal-to-noise ratio (SNR). A simpler sequential PTS scheme achieves a gain of 1.64 dB at high SNR.
