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Blind separation of partially overlapping data packets
Affiliation:1. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China;2. Yibin Institute of UESTC, Yibin, Sichuan, China
Abstract:The paper discusses the separation of partially overlapping data packets by an antenna array in narrowband communication systems. This problem occurs in asynchronous communication systems and several transponder systems such as Radio Frequency Identification (RFID) for wireless tags, Automatic Identification System (AIS) for ships, and Secondary Surveillance Radar (SSR) and Automatic Dependent Surveillance—Broadcast (ADS—B) for aircraft. Partially overlapping data packages also occur as inter-cell interference in mutually unsynchronized communication systems. Arbitrary arrival times of the overlapping packets cause nonstationary scenarios and makes it difficult to identify the signals using standard blind beamforming techniques. After selecting an observation interval, we propose subspace-based algorithms to suppress partially present (interfering) packets, as a preprocessing step for existing blind beamforming algorithms that assume stationary (fully overlapping) sources. The proposed algorithms are based on a subspace intersection, computed using a generalized singular value decomposition (GSVD) or a generalized eigenvalue decomposition (GEVD). In the second part of the paper, the algorithm is refined using a recently developed subspace estimation tool, the Signed URV algorithm, which is closely related to the GSVD but can be computed non-iteratively and allows for efficient subspace tracking. Simulation results show that the proposed algorithms significantly improve the performance of classical algorithms designed for block stationary scenarios in cases where asynchronous co-channel interference is present. An example on experimental data from the AIS ship transponder system confirms the effectiveness of the proposed algorithms in a real application.
Keywords:Generalized singular value decomposition  Blind source separation  Subspace intersection  Signed URV decomposition  Automatic Identification of Ships (AIS)
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