Enhancing Direct Position Determination in Distributed Base Station Systems through Time-Varying Quantization Design

In distributed base station (DBS) systems, the traditional direct position determination (DPD) methods entail the transmission of raw data to the fusion center (FC), straining transmission bandwidth and hardware resources. One-bit analog-to-digital converters (ADCs) have emerged as a promising solution. However, the conventional zero-thresholding quantization (ZQ) scheme exhibits significant performance degradation. In response, we introduce a one-bit time-varying quantization (TQ) strategy tailored for DBS systems, and develop a Rao-test-based method under the one-bit TQ scheme (TQ-one-bit Rao test, TQ-OBRT), enabling simultaneous target detection and localization. To evaluate the performance of the proposed method, the one-bit Cramér-Rao lower bound (CRLB) is derived. Finally, we obtain the optimal quantization (OQ) scheme by minimizing the one-bit CRLB, and introduce a simpler random quantization (RQ) scheme without iterative processing. Simulation results demonstrate the superior performance of the proposed OQ and RQ schemes compared to the ZQ scheme in terms of target detection and localization.