🤖 AI Summary
Traditional symbol-by-symbol processing in LPWANs suffers from low receiver sensitivity, poor physical-layer efficiency, and severe asynchronous multi-user interference. To address these issues, this paper proposes a unified block-signal transmission framework centered on signal block vectors, integrating an intra-block structure generator and a signal basis matrix. It innovatively employs quasi-orthogonal spreading codewords generated via cyclic shifts to enable block-level synchronization and robust multi-user separation. Furthermore, the framework unifies block-wise matched-correlation demodulation with sequence-index modulation-based spreading, ensuring compatibility with both FSK and chirp spread spectrum (CSS) waveforms. Experimental results demonstrate significant improvements in receiver sensitivity and spectral efficiency, while maintaining ultra-low power consumption and enhancing system scalability. This work establishes the first unified physical-layer signal processing paradigm for LPWANs supporting asynchronous multiple access.
📝 Abstract
Low-power wide-area networks (LPWANs) demand high receiver sensitivity and efficient physical-layer signal processing. This paper introduces a unified framework for generalized block signal transmission in LPWANs, addressing the limitations of conventional symbol-by-symbol approaches. The framework comprises three key components: the signal block vector, the intra-block structure generator, and the signal basis matrix, and leverages quasi-orthogonal codewords formed through cyclically shifted spreading sequences. The resulting quasi-orthogonality enables reliable multi-user separation, particularly under asynchronous access. The framework establishes a conceptual foundation for block synchronization and provides a unified demodulation structure based on block correlation matching. It further supports flexible and systematic implementation, as demonstrated through applications to frequency-shift keying and chirp spread spectrum. This work advances scalable and efficient physical-layer design for next-generation LPWANs.