# Coexistence in Wireless Networks: Challenges and Opportunities
## 4 Spectrum Sharing and Coexistence
### Coexistence in Terrestrial Communication  
The deployment of the fifth generation of mobile radio communication by 2020 was projected to face several challenges, including a rise in service demand with low latency, in order to service billions of end customers known as satellite mobile users ([PERSON] and [PERSON], 2020). Terrestrial communication systems will most likely meet a thick network of countless small cells at any time and anywhere. As a result, services from terrestrial systems are unavailable to some of the world's most remote locations ([PERSON] and [PERSON], 2020). Moreover, effective interference control is necessary to share the spectrum between satellite systems and terrestrial equipment because of the limited supply of spectral resources. Two channel assignment algorithms for maximizing multicast coverage in terrestrial networks are analyzed in ([PERSON] and [PERSON], 2020). The study investigates the interactions and coexistence of different channel assignment systems operating within the same area and spectrum. Multiple base stations within a common service area are considered, and network performance is evaluated based on the coverage area and the signal-to-interference-plus-noise ratio (SINR). It has been demonstrated that combining different schemes can be beneficial, since blended systems can benefit from the best aspects of each plan. A coexistence test scenario was established across multiple channels with randomly positioned terrestrial base stations to simplify the analysis. Figure 8 represents a base station (BS) coverage and coexistence model, illustrating the overlapping service areas of multiple base stations. Each colored region represents the coverage area of a different BS (BS1, BS2, BS3, BS5, etc. ), highlightinghow multiple base stations coexist within an 8 km radius. Larger coverage areas, such as BS 5\(\ldots\)BS i, indicate extended network service regions, while smaller zones represent localized base stations that provide targeted connectivity. The overlapping areas suggest potential interference zones, where multiple BS signals interact, requiring efficient frequency management and interference mitigation techniques to maintain seamless communication. A framework for intelligent spectrum management based on artificial intelligence and software-defined networks (SDN) is presented in [76]. An integrated satellite and terrestrial network (ISTN) with interoperability and the capacity to reprogram is created by combining heterogeneous satellite and terrestrial networks using SDN. AI is also used to set up networks for optimal resource distribution and forecast environmental conditions. The framework, in short, suggests a novel method for utilizing and combining the spectrum of terrestrial and satellite networks. The influence of interference between satellite and terrestrial systems sharing a spectrum is examined in [77]. A realistic coexistence model was developed to derive a closed-form expression for the satellite link outage probability in the presence of terrestrial interference. Both terrestrial and satellite links are modeled with Nakagami fading, while the satellite link additionally considers shadowing Rician fading. Numerical simulations demonstrate that unmanaged terrestrial interference substantially degrades the satellite link outage performance. The formulas acquired are useful for forecasting and mitigating harmful interference while creating coexistence strategies for terrestrial and satellite systems. This study focuses on designing robust beamforming for satellite-based IoT systems coexisting with terrestrial networks. It addresses the challenges posed by phase errors in channel estimation and formulates an optimization problem to maximize system performance under outage and power constraints. A two-level iterative algorithm is proposed to efficiently solve this complex problem [78]. To evaluate coexisting radar, satellite, and terrestrial communication systems, researchers used simulations, testbeds, and field trials to assess key metrics.