Joint Modulation and Coding Scheme Optimization for Reliable IoT Communications in LEO Satellite Constellations

Abstract

The spread of Internet of Things (IoT) usage has kindled the inclusion of Low Earth Orbit (LEO) satellite constellation networks to deliver connectivity anywhere at a low-latency period. But the very dynamic channel nature, numerous handovers, or the tight power limitations of the LEO satellite systems are the challenges that become a major issue in the provision of reliable data transmission. This paper suggests a dual optimization problem of adaptive Modulation and Coding Scheme (MCS) selection, that is unique to IoT enabled IoT-enabled LEO satellite communications. The framework uses real-time link quality metrics, device mobility history, latency needs to dynamically choose the best MCS in a given channel. A dynamic trade-off between spectral efficiency, energy consumption, and error resilience is achieved by use of an adaptive algorithm on reinforcement learning. Simulation observations made under realistic orbital dynamics and Rician fading conditions demonstrate an improvement in the Bit Error Rate (BER) of 10 3, 10 5 with a corresponding improvement in energy per bit of 2.1 mJ/bit to 1.3 mJ/bit and a high Packet Delivery Ratio (PDR) and low latency over a variety of IoT traffic distributions. The scheme offers a up to 28 percent enhancement in spectral efficiency over either static or heuristic MCS approach and provides an advantage (in terms of communications reliability) without crossing the line and excessively increasing delays. These findings confirm the applicability of this framework on the provision of scalable and energetically light IoT implementations in future LEO networks.