Symbiotic communication systems in the Internet of Things: A framework for double adaptive performance analysis

Abstract

This letter studies the performance enhancement of symbiotic systems, which begins by formulating a closed-form adaptive mutualism symbiotic strategy for the backscatter coefficient to achieve minimal decoding errors for both primary and secondary signals. Then, we analyze two scenarios: First, the primary source adapts the modulation scheme based on the channel conditions of the primary signal to meet the target bit error rate (BER), evaluating metrics: mode selection probability, outage mode probability (OMP), BER, and spectral efficiency. Second, the primary source adapts its transmission rate and/or power according to three channel policies: constant power with optimal rate adaptation, optimal simultaneous power and rate adaptation, and truncated channel inversion with a fixed rate. Results show that for the first scenario, our proposed approach significantly improves the OMP and BER of the adaptive symbiotic system in the moderate and high signal-to-noise ratio (SNR) regimes compared to the fixed one, while the second scenario shows a promising choice for balancing capacity between backscatter and cellular rates in the low SNR regime.