# A Spectrum Management Platform Architecture to Enable a Sharing Economy in 6G
## 6 Conclusions  
Current spectrum allocation models for 5G are still based on relatively static frequency band allocation and centralised licencing, with the only alternative provided by unlicensed bands. In either case, unnecessary congestion is observed when the demand is high, due to the suboptimal spectrum management that these models allow for. In this article, we proposed a new vision for spectrum sharing in wireless and mobile networks, based on the recent developments in economic models around sharing of common goods. This vision of trading and allocating spectrum as part of a sharing economy in 6G centres around  
Figure 4: Measured SINR under both access models for different numbers of IoT devices: (**a**) SINR in case of 1000 IoT devices; (**b**) SINR in case of 2000 IoT devices; (**c**) SINR in case of 3000 IoT devices. Figure 5: Probability of denying connectivity for different numbers of IoT devices. the ability to automate the matching of locally offered and demanded spectral resources, incentivising stakeholders to share their resources and, therefore, help in easing the demand for this scarce resource. We also introduced the system architecture of HODNET, an open platform that is capable of realising this new sharing model. HODNET is based on spectrum trading between operators to optimise efficiency and scalability on a high level and builds on the concept of spectrum programming down to the individual radio primitives to enforce fine-grained protocol control. To demonstrate the benefits of this novel spectrum-sharing paradigm, we considered the use case of massive IoT on a local scale. We simulated a large IoT deployment and evaluated the spectral efficiency of the system when managed using HODNET and compared the results with a standard 5G deployment. We only looked at a very simple trading scheme, in which each IoT device's demand is matched by having it connected to the RAN that has the smallest number of connections, and which provides a sufficient RSSI based on the data rate requirements. Even with such an uncomplicated scheme, a significant improvement in resource utilisation was observed. Significant aspects to explore further include the wider application of the platform to optimise other metrics, such as efficiency, security, and quality of service. Other important areas to investigate are the upper planes of the platform and the inter-operator spectrum broking system. Key questions include how the good to be traded should be mathematically defined (i.e., the utility function), how dynamic the trading can be executed (we expect in the order of minutes or maybe faster), how deals can be secured, verified, and validated, how the platform can be implemented in a distributed fashion, how participation in the trading can remain voluntary but still effective, and how this concept can be extended to other types of network resources. We, therefore, conclude that the concept of enabling a sharing economy in the 6G spectrum has sufficient merit to warrant further investigation and it represents a fascinating step forward for research in this relatively new area of massive automated heterogeneous spectrum trading and allocation. Conceptualisation, F.B. and F.d.H. ; methodology, F.B., M.M., A.R. and F.d.H. ; software, A.R. ; validation, A.R. ; formal analysis, F.B., M.M., A.R. and F.d.H. ; investigation, F.B., M.M., A.R. and F.d.H. ; writing--original draft preparation, F.B., A.R. and M.M. ; writing--review and editing, F.d.H. ; visualisation, A.R  
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