# Graph-Based Resource Allocation for Integrated Space and Terrestrial Communications
## 6 Graph-Based RA in CR Networks
### Lessons Learned and Trends in Development  
On the basis of the review in this section, the following observations and research directions can be denoted:  
* _The mutual influence between the PU network and that of the SUs (which, in a realistic scenario, may be significant) is rarely considered._ Usually, the CR network is described as a separate graph. The SUs' available channels are assumed to be fixed, and consequently, only the SUs' throughput is assessed. However, in this case, the interference originating both from the SUs to the PUs, and the other way around, as well as the spectrum utilization gain (The throughput increase related to the introduction of the CR network in the spectrum of the PU) is not accounted for. _The difficulty, then, comes from the graph and optimization algorithm designed to consider the RA of both networks, and (depending on the CR's mode of operation) coordinate the SSh and RA decisions to provide optimal spectrum utilization and protection of the PU communications. A suitable tool for this purpose is for them to be modeled via CSP._
* The assumption of perfect CSI/spectrum occupancy information is problematic, especially in CR networks, which are not licensed users of the spectrum. PU misdetections should be considered in graph-based RA for SUs. Their \(P_{MD}\) and \(P_{FA}\) (as functions of the measured SNR) may be used as valuable attributes in a graph. Respectively, mechanisms that reduce the influence of imperfect spectrum sensing are needed. As presented by [79], _high-accuracy CSS can be implemented as a GSP-based solution, and thus included in the procedure._
* Depending on the CR operation mode and the SUs' number, the overhead exchange for clustering and RA may be prohibitive. Moreover, the RA method should consider the variable number of channels for SUs, which are characteristic of interweave CR networks. _A disadvantage of graphs is that their number of vertices is fixed, and thus, their definition for modeling allocation of rapidly varying availability of channels (within the duration of the same simulation instance), may be significantly more difficult. Therefore, the graph-based solution may include ILI/DL decoupling on different modes (DL on interweave, featuring non-graph based optimization, ILI on underlay), with preliminary training of a GSP-based DRL method for specific deployment scenarios._
* The UA and RA of SUs/CAPs should be designed with consideration of whether the CR nodes are stationary, airborne (on UAVs), ground-based vehicular, marine, or carried/worn by humans [74]. They are situated in different locations/heights and diverse radio propagation conditions, so the complexity/capability of their functionalities for spectrum sensing, clustering, UA, and RA should reflect the environment's severity. Challenges and Design Aspects of the Holistic Graph-Based Resource Allocation for Integrated Space Terrestrial Networks  
A substantial number of recent works [1; 2; 3; 90; 91] have provided important visions for 6G ISTN architectures and their requirements in terms of applications, technologies, hardware, signal processing, and resource distribution. It is envisioned that 6G will not simply include different kinds (in terms of coverage, throughput requirements, and node density) of terrestrial (TNs) and non-terrestrial networks (NTNs), but will incorporate them into a global system. This will be driven by the mutual benefits of network convergence,for example, UAVs providing backhaul for densely deployed terrestrial APs, or low-orbit satellites broadcasting common data streams to groups of users that require the same content [92]. Consequently, a solid basis is established, for the development of algorithms for RA, multiple access, EE, and security, operating in the relevant application scenarios. They are diverse, incorporating marine, terrestrial, air, and space communications, as well as many types of devices (some of which support multiple RATs) with various capabilities and throughput/latency requirements.