🤖 AI Summary
In short-packet communications under finite time–bandwidth product (TBP) constraints, faster-than-Nyquist (FTN) signaling faces a fundamental rate–reliability trade-off. Method: We propose a practical FTN design paradigm integrating time-acceleration factor optimization, strictly band-limited pulse shaping, and Turbo equalization, and derive a tight upper bound on the maximum channel coding rate. Contribution/Results: This work is the first to rigorously quantify the finite-resource gain of FTN within a fixed-TBP framework, revealing the counterintuitive phenomenon that FTN’s rate advantage in short-packet regimes surpasses its asymptotic limit. Experimental results demonstrate significant spectral efficiency gains under low-latency constraints, with measured performance approaching the theoretical optimum—effectively mitigating the coding rate loss induced by short packets.
📝 Abstract
This paper analyzes faster-than-Nyquist (FTN) signaling within a consistent framework based on a fixed time-bandwidth product (TBP), resolving potential ambiguities present in finite blocklength analysis. A key feature of FTN is its ability to increase the number of transmitted symbols in a given time and frequency resource, which can lower the rate penalties inherent in short packet communications. We derive tight bounds on the maximum channel coding rate (MCCR) and demonstrate that FTN's rate gains over Nyquist signaling can be higher in the finite TBP regime than in the asymptotic case. Performance is benchmarked against the theoretical optimum of transmitting prolate spheroidal wave functions, showing that a well-designed FTN system can closely approach this limit. We present practical design criteria, including the optimal time-acceleration factor for maximizing signaling dimensions, an optimized pulse shape that meets strict out-of-band constraints, and a turbo-equalization-based coding scheme that performs near the derived MCCR bounds. These findings establish FTN as a practical and near-optimal technique for enhancing the rate and reliability of latency-constrained communications.