This paper reviews the state-of-the art technologies and techniques for integrating satellite and terrestrial networks within a 5G and Beyond Networks (5GBYNs). It highlights key limitations in existing architectures, particularly in addressing interoperability, resilience, and Quality of Service (QoS) for real-time applications. In response, this work proposes a novel Software-Defined Networking (SDN)-based framework for reliable satellite–terrestrial integration. The proposed framework leverages intelligent traffic steering and dynamic access network selection to optimise real-time communications. By addressing gaps in the literature with a distributed SDN control approach spanning terrestrial and space domains, the framework enhances resilience against disruptions, such as natural disasters, while maintaining low latency and jitter. Future research directions are outlined to refine the design and explore its application in 6G systems.

The integration of wireless power transfer (WPT) with massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks can provide operational capabilities to energy-constrained Internet of Things (IoT) devices in cyber-physical systems such as smart autonomous vehicles. However, during downlink WPT, co-channel interference (CCI) can limit the energy efficiency (EE) gains in such systems. This paper proposes a user equipment (UE)–base station (BS) connection model to assign each UE to a single BS for WPT to mitigate CCI. An energy-efficient resource allocation scheme is developed that integrates the UE–BS connection approach with joint optimization of power control, time allocation, antenna selection, and subcarrier assignment. The proposed scheme improves EE by 24.72% and 33.76% under perfect and imperfect CSI conditions, respectively, compared to a benchmark scheme without UE–BS connections. The scheme requires fewer BS antennas to maximize EE and the distributed algorithm exhibits fast convergence. Furthermore, UE–BS connections’ impact on EE provided significant gains. Dedicated links improve EE by 24.72% (perfect CSI) and 33.76% (imperfect CSI) over standard connections. Imperfect CSI reduces EE, with the proposed scheme outperforming by 6.97% to 12.75% across error rates. More antennas enhance EE, with improvements of up to 123.12% (conventional MIMO) and 38.14% (massive MIMO) over standard setups. Larger convergence parameters improve convergence, achieving EE gains of 7.09% to 11.31% over the baseline with different convergence rates. The findings validate the effectiveness of the proposed techniques in improving WPT efficiency and EE in wireless-powered MIMO–NOMA networks.

The convergence of Satellite Mobile Networks (SMNs) with Terrestrial Wireless Networks (TWNs) has emerged as a significant area of research. Such integration is crucial for overcoming the current challenges of static spectrum assignment faced by earlier wireless network generations, including inefficient energy utilisation, insufficient bandwidth, increased latency, reduced reliability, limited connectivity, and restricted capacity. To address these issues, the potential of Cognitive Radio Networks (CRNs) has been exploited in Fifth Generation (5G), facilitating seamless interoperability among networks to sustain wireless communications. This paper presents a novel Vertical Hypothesis Uncertainty (VHU) method for optimising system throughput in CRN, leveraging the spectrum sensing false alarm, Pfa and null detection, Pnd hypotheses. This approach integrates the Filtered Orthogonal Frequency Division Multiplexing (F-OFDM) with Spectrum Sensing (SS) within a Satellite-Terrestrial Network (STN) domain. The performance of the proposed VHU was tested against the Hybrid Filter Detection with Inverse Covariance (HFDIC) and traditional spectrum sensing concepts. Results at –10 dB Signal-to-Noise Ratio (SNR) show that the VHU method remarkably outperforms HFDIC, achieving a 7.9% improvement in a fixed channel and a 15.84% improvement in a dynamic channel under perfect channel conditions.