面向宽带OFDM捏合天线集成感知与通信系统的色散感知定位网络
Dispersion-aware Localization Network for Wideband OFDM Pinching-Antenna Integrated Sensing and Communication Systems
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中文总结 AI 辅助
针对宽带OFDM捏合天线ISAC系统的波导色散导致定位性能下降的问题，提出两阶段ISAC框架及DiPL-Net网络，仿真显示其在保持通信速率的同时大幅提升定位性能。
中文摘要 AI 辅助
捏合天线系统（PASS）以较低的硬件成本提供了大的有效孔径和显著的路径损耗降低，因此在集成感知与通信（ISAC）领域具有吸引力。然而，在宽带OFDM工作模式下，每个波导上的天线会对同一基带信号施加与位置相关的非线性群延迟，从而产生波导色散，严重降低距离估计性能。为此，本文提出了一种两阶段ISAC框架，包括通信感知波束成形和天线放置，以及后续的色散感知目标定位阶段。分数规划波束成形器与逐元素坐标下降放置方法在感知方向图增益约束下共同最大化下行链路和速率，所得的优化波束成形器和放置方案确定了定位阶段使用的有效感知信道。所提出的色散感知定位网络（DiPL-Net）基于物理推导的距离字典构建色散感知得分图，从接收信号中检测目标。其卷积骨干网络采用双内核残差块，每个残差块将与OFDM主瓣匹配的短内核和与色散尾匹配的长内核配对，以解卷积色散并在每个真实目标处恢复清晰的目标峰值。仿真结果表明，与多种感知基准相比，该方法在保持可实现通信速率的同时，实现了显著的定位性能提升。
英文摘要
Pinching-antenna systems (PASS) provide a large effective aperture and substantial path-loss reduction at low hardware cost, making them attractive for integrated sensing and communication (ISAC). Under wideband OFDM operation, however, the antennas on each waveguide impose nonlinear, position-dependent group delays on the same baseband signal, giving rise to waveguide dispersion that severely degrades range estimation. To this end, this paper proposes a two-stage ISAC framework comprising communication-aware beamforming and antenna placement followed by a dispersion-aware target localization stage. A fractional-programming beamformer and an element-wise coordinate-descent placement jointly maximize the downlink sum rate under a sensing beampattern-gain constraint, and the resulting optimized beamformer and placement determine the effective sensing channel used by the localization stage. The proposed DisPersion-aware Localization Network (DiPL-Net) detects targets from the received signal via a dispersion-aware score map built on a physics-derived range dictionary. Its convolutional backbone employs dual-kernel residual blocks, each pairing a short kernel matched to the OFDM main lobe with a long kernel matched to the dispersion tail, so as to deconvolve the dispersion and restore a sharp target peak at each true target. Simulation results show substantial localization gains over various sensing baselines while preserving the achievable communication rate.
