🤖 AI Summary
This work addresses the inherent trade-off between high data rates and high concurrency in underwater acoustic networks, a challenge inadequately resolved by conventional approaches. The authors propose a cross-layer concurrent random access system that innovatively integrates equispaced Zadoff–Chu code-division multiplexing (EZCDM) waveforms with a cross-layer link adaptation mechanism, transforming destructive collisions into decodable concurrent signal streams. The design employs intra-symbol differential reception, beacon-based random access, user-level closed-loop power control, and overlap-aware common modulation set selection, enabling robust communication without explicit channel estimation. Experimental and simulation results demonstrate that the proposed scheme significantly outperforms existing physical-layer waveforms and MAC protocols in terms of both bit error rate and throughput, effectively achieving a flexible balance between spectral efficiency and reliability.
📝 Abstract
Underwater acoustic networks face a fundamental rate--concurrency tradeoff: high-rate waveforms (e.g., OFDM, OTFS) are designed for point-to-point links and rely on orthogonal MAC protocols (e.g., TDMA) to avoid collisions, sacrificing concurrency; conversely, collision-resilient waveforms (e.g., CDMA, ZCMod) support uncoordinated access but are inherently rate-limited by spreading or sparse index modulation. We present \system, a cross-layer concurrent random-access system that combines two new components: (i) \textbf{EZCDM}, an equidistant ZC division-multiplexing waveform that activates multiple cyclic shifts of a ZC root as parallel sub-channels with a tunable rate--robustness tradeoff, and an intra-symbol differential receiver that eliminates the shared multipath channel response without explicit CIR estimation; and (ii) a \textbf{cross-layer link adaptation (LA) framework} featuring beacon-framed random access, user-specific closed-loop power control, and overlap- and CIR-aware common-MS selection. Channel-trace- and signal-trace-driven physical-layer experiments combined with PHY-in-the-loop network simulations demonstrate that \system\ achieves significant BER and throughput gains over conventional waveforms and MAC protocols by converting traditionally destructive collisions into decodable concurrent streams.