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<p>This paper presents a novel modulation technique called Dynamic Frequency Shift Keying (Dynamic FSK), designed for modern Internet of Things (IoT) networks where devices are low-power, low-cost, and often deployed in dense environments. Unlike conventional Frequency Shift Keying (FSK) schemes with fixed frequency dictionaries, Dynamic FSK introduces a dynamic frequency generation mechanism, in which each transmitted frequency is derived within its dedicated tone from the data symbol, a scaling factor, and an auxiliary term for redundancy and validation. A greedy spectral partitioning algorithm is applied to maximize transmitted bits while minimizing frequency transitions, enabling per-symbol modulation with very low computational load, well suited for constrained IoT hardware. Dynamic FSK is evaluated against three widely used schemes–16-FSK, Chirp Spread Spectrum (CSS), and 64-Quadrature Amplitude Modulation (64-QAM)–under two representative channel models: ideal Additive White Gaussian Noise (AWGN) and degraded Rayleigh fading with interference and frequency drift. GNU Radio simulations demonstrate that Dynamic FSK achieves superior resilience in terms of throughput and latency under increasing network density, while maintaining low energy consumption. The evaluation also considers spectral efficiency and a point-to-point bit error rate (BER) analysis to assess bandwidth utilization and physical-layer robustness. To enable cross-metric comparison, a Global Efficiency Index (GEI) is introduced, combining energy, latency, and throughput. Dynamic FSK consistently outperforms the benchmark schemes in terms of GEI and shows high robustness under degraded conditions. These results highlight its potential as a practical and scalable modulation for future IoT deployments.</p>

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Dynamic Frequency Shift Keying: A Lightweight Modulation for Energy, Latency, and Throughput Optimization in IoT Networks

  • 期刊论文

  • 发表日期：

    2026年5月23日

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  • Abdelhak Goutal,
  • Mohand Moktefi,
  • Louiza Bouallouche-Medjkoune

摘要

This paper presents a novel modulation technique called Dynamic Frequency Shift Keying (Dynamic FSK), designed for modern Internet of Things (IoT) networks where devices are low-power, low-cost, and often deployed in dense environments. Unlike conventional Frequency Shift Keying (FSK) schemes with fixed frequency dictionaries, Dynamic FSK introduces a dynamic frequency generation mechanism, in which each transmitted frequency is derived within its dedicated tone from the data symbol, a scaling factor, and an auxiliary term for redundancy and validation. A greedy spectral partitioning algorithm is applied to maximize transmitted bits while minimizing frequency transitions, enabling per-symbol modulation with very low computational load, well suited for constrained IoT hardware. Dynamic FSK is evaluated against three widely used schemes–16-FSK, Chirp Spread Spectrum (CSS), and 64-Quadrature Amplitude Modulation (64-QAM)–under two representative channel models: ideal Additive White Gaussian Noise (AWGN) and degraded Rayleigh fading with interference and frequency drift. GNU Radio simulations demonstrate that Dynamic FSK achieves superior resilience in terms of throughput and latency under increasing network density, while maintaining low energy consumption. The evaluation also considers spectral efficiency and a point-to-point bit error rate (BER) analysis to assess bandwidth utilization and physical-layer robustness. To enable cross-metric comparison, a Global Efficiency Index (GEI) is introduced, combining energy, latency, and throughput. Dynamic FSK consistently outperforms the benchmark schemes in terms of GEI and shows high robustness under degraded conditions. These results highlight its potential as a practical and scalable modulation for future IoT deployments.