AI 中文总结
本文提出PDISAC框架，通过RDPDNet抑制ISAC波形的数据相关旁瓣与热噪声，实现感知-通信的可调节权衡，低SNR时RDPDNet可降低RMSE，高SNR时传统链路可达到偏差调整基准。
AI 中文摘要
本文提出概率去噪ISAC（PDISAC）框架，该框架构建于多时隙划分的ISAC波形之上：通过将每个最大长度序列划分为交替的导频与时隙，我们借助符号级扩频在每个序列中嵌入多比特，在每个码片保留确定性雷达码的同时，将数据速率提升了数倍。然而，增加的吞吐量会向距离-多普勒（RD）热图中引入与数据相关的非白色旁瓣，从而降低匹配滤波（MF）感知性能。我们并未对MF接收机进行修改，而是开发了轻量级概率去噪网络RDPDNet，将其插入RD图形成与恒虚警率检测之间；采用对抗频率混合机制对其进行训练，无需知晓嵌入符号即可抑制数据诱导旁瓣与热噪声。我们进一步表征了由几何决定的信道统计特性。随后通过分析下界、半解析误码率（BER）以及平均容量对设计的基本性能极限进行分析，这些指标将时隙分配与序列长度关联至感知-通信权衡。通过在真实城市几何上的分析与数值结果表明，RDPDNet可吸收大部分数据嵌入带来的感知性能损失，并在低信噪比（SNR）时显著降低均方根误差（RMSE），而传统无数据链路在高SNR时可达到偏差调整后的基准。此外，增加时隙分配会提高数据速率，但会以更高的BER为代价，这呈现出可调节的感知-通信权衡。
英文摘要
In this paper, we propose Probabilistic Denoising ISAC (PDISAC), a framework built on a multi-bit slot-partitioned ISAC waveform: by partitioning each maximal-length sequence into alternating pilot and data slots, we embed multiple bits per sequence through symbol-level spreading, multiplying the data rate while every chip retains the deterministic radar code. The added throughput, however, injects data-dependent, non-white sidelobes into the range-Doppler (RD) heatmap that degrade matched-filter (MF) sensing. Rather than modifying the MF receiver, we develop RDPDNet, a lightweight probabilistic denoising network inserted between RD-map formation and constant-false-alarm-rate detection; training it with an adversarial frequency-mixup mechanism, we suppress the data-induced sidelobes and thermal noise without knowledge of the embedded symbols. We further characterize the statistics of the geometry-determined channel. The fundamental performance limits of the design are then analyzed through an analytical lower bound, a semi-analytical bit error rate (BER), and an average capacity that tie the slot allocation and sequence length to the sensing-communication trade-off. Through analytical and numerical results over a realistic urban geometry, we show that RDPDNet absorbs most of the data-embedding sensing penalty and markedly lowers the RMSE at low SNR, while the conventional data-free chain attains the bias-adjusted benchmark at high SNR. Moreover, increasing the slot allocation raises the data rate at the expense of a higher BER, exposing a tunable sensing--communication trade-off.
