Mutualistic Backscatter NOMA Method for Coordinated Direct and Relay Transmission System

Objective The exponential growth in data traffic necessitates that cellular Internet of Things (IoT) systems achieve both ultra-high spectral efficiency and wide-area coverage to meet the stringent service requirements of vertical applications such as industrial automation and smart cities. Non-Orthogonal Multiple Access-based Coordinated Direct and Relay Transmission (NOMA-CDRT) method can enhance both spectral efficiency and coverage by leveraging power-domain multiplexing and cooperative relaying, making it a promising approach to address these challenges. However, existing NOMA-CDRT frameworks are primarily designed for cellular communications and do not effectively support spectrum sharing or the deep integration of cellular and IoT transmissions. To overcome these limitations, this study proposes a Mutualistic Backscatter NOMA-CDRT (MB-NOMA-CDRT) method. This approach facilitates spectrum sharing and mutualistic coexistence between cellular users and IoT devices, while improving the system’s Ergodic Sum Rate (ESR). Methods The proposed MB-NOMA-CDRT method integrates backscatter modulation and power-domain superposition coding to develop a bidirectional communication strategy that unifies information transmission and cooperative assistance, enabling spectrum sharing and mutualistic coexistence between cellular users and IoT devices. Specifically, the base station uses downlink NOMA to serve the cellular center user directly and the cellular edge user via a relaying user. Simultaneously, IoT devices utilize cellular radio frequency signals and backscatter modulation to transmit their data to the base station, thereby achieving spectrum sharing. The backscattered IoT signals act as multipath gains, contributing to improved cellular communication quality. To rigorously characterize the system performance, the squared generalized-K distribution and Meijer-G functions are adopted to derive closed-form expressions for the ESR under both perfect and imperfect Successive Interference Cancellation (SIC). Building on this analytical foundation, a power allocation optimization scheme is developed using an enhanced Particle Swarm Optimization (PSO) algorithm to maximize system ESR. Finally, extensive Monte Carlo simulations are conducted to verify the ESR gains of the proposed method, confirm the theoretical analysis, and demonstrate the efficacy of the optimization scheme. Results and Discussions The performance advantage of the proposed MB-NOMA-CDRT method is demonstrated through comparisons of ESR with conventional NOMA-CDRT and Orthogonal Multiple Access (OMA) schemes (Fig. 2 and Fig. 3). The theoretical ESR results closely match the simulation data, confirming the validity of the analytical derivations. Under both perfect and imperfect SIC, the proposed method consistently achieves the highest ESR. This improvement arises from spectrum sharing between cellular users and IoT devices, where the IoT link contributes multipath gain to the cellular link, thereby enhancing overall system performance. To investigate the influence of power allocation, simulation results illustrate the three-dimensional relationship between ESR and power allocation coefficients (Fig. 4). A maximum ESR is observed under specific coefficient combinations, indicating that optimized power allocation can significantly improve system throughput. Furthermore, the proposed optimization scheme demonstrates rapid convergence, with ESR values stabilizing within a few iterations (Fig. 5), supporting its computational efficiency. Finally, ESR performance is compared among the proposed optimization scheme, exhaustive search, and fixed power allocation strategies (Fig. 6). The proposed scheme consistently yields higher ESR across both perfect and imperfect SIC scenarios, demonstrating its superiority in enhancing spectral efficiency while maintaining low computational complexity. Conclusions This study proposes a MB-NOMA-CDRT method that enables spectrum sharing between IoT devices and cellular users while improving cellular communication quality through the backscatter-assisted reflection link. To evaluate system performance, closed-form expressions for the ESR are derived under both perfect and imperfect SIC. Building on this analytical foundation, a power allocation optimization scheme based on PSO is developed to maximize the system ESR. Simulation results demonstrate that the proposed method consistently outperforms conventional NOMA-CDRT and OMA schemes in terms of ESR, under both perfect and imperfect SIC conditions. The optimization scheme also exhibits favorable convergence behavior and effectively improves system performance. Given its advantages in spectral efficiency and computational efficiency, the proposed MB-NOMA-CDRT method is well suited to cellular IoT scenarios. Future work will focus on exploring the mathematical conditions necessary to fully characterize and exploit the mutualistic transmission mechanism.