Abstract:We present a novel cross-band modulation framework that combines 3D modulation in the RF domain with intensity modulation and direct detection in the optical domain, the first such integration to enhance communication reliability. By harnessing cross-band diversity, the framework optimizes symbol mapping across RF and optical links, significantly boosting mutual information (MI) and reducing symbol error probability (SEP). Two practical modulation schemes implement this framework, both using quadrature amplitude modulation in the RF subsystem. The first is a linear cross-band mapping scheme, where RF symbols are mapped to optical intensity values via an analytically tractable optimization that ensures O(1) detection complexity while minimizing SEP. The second employs a deep neural network-generated (DNN-Gen) 3D constellation with a custom loss function that adaptively optimizes symbol placement to maximize MI and minimize SEP. Although DNN-Gen incurs higher computational complexity than the linear approach, it adapts the 3D constellation to varying signal-to-noise ratios, yielding significant performance gains. Furthermore, we derive a theoretical MI benchmark for the linear scheme, offering insights into the fundamental limits of RF-optical cross-band communication. Extensive Monte Carlo simulations confirm that both schemes outperform SoA cross-band modulation techniques, including cross-band pulse amplitude modulation, with notable improvements. Additionally, DNN-Gen maintains high performance over a range of RF SNRs, lessening the need for exhaustive training at every operating condition. Overall, these results establish our cross-band modulation framework as a scalable, high-performance solution for next-generation hybrid RF-optical networks, balancing low complexity with optimized symbol mapping to maximize system reliability and efficiency.
Abstract:In the evolving landscape of sixth-generation (6G) wireless networks, which demand ultra high data rates, this study introduces the concept of super constellation communications. Also, we present super amplitude phase shift keying (SAPSK), an innovative modulation technique designed to achieve these ultra high data rate demands. SAPSK is complemented by the generalized polar distance detector (GPD-D), which approximates the optimal maximum likelihood detector in channels with Gaussian phase noise (GPN). By leveraging the decision regions formulated by GPD-D, a tight closed-form approximation for the symbol error probability (SEP) of SAPSK constellations is derived, while a detection algorithm with O(1) time complexity is developed to ensure fast and efficient SAPSK symbol detection. Finally, the theoretical performance of SAPSK and the efficiency of the proposed O(1) algorithm are validated by numerical simulations, highlighting both its superiority in terms of SEP compared to various constellations and its practical advantages in terms of fast and accurate symbol detection.