Novel Radio Resource Allocation Scheme in 5G and Future Sharing Network via Multi-Dimensional Collaboration

Abstract

Radio resource allocation schemes are critical to enhance user experience and spectrum efficiency. In the context of fifth-generation (5G) and future networks, co-construction and sharing among multiple telecom operators, which effectively mitigate challenges stemming from resource scarcity, energy consumption, and network construction costs, also attract wide attention. Therefore, optimal resource allocation techniques in sharing networks should be explored. Current resource allocation schemes primarily optimize for load balancing, single-user throughput, and fairness of multi-user whole network throughput, with minimal consideration for network-level user experience. Moreover, existing approaches predominantly concentrate on specific resource domains, seldom considering holistic collaboration across all domains, which limits the user experience of the whole network. This paper introduces an innovative resource allocation method grounded in the Shannon theorem, incorporating time-frequency-spatial domain multi-dimensional collaboration. More importantly, by constructing an optimization model, we strive to attain optimal network-level user experience. Furthermore, we provide a smart grid technology based on the Artificial Intelligence (AI) method to predict inter-frequency information, including Received Signal Reference Power (RSRP), beam ID, and spectral efficiency, which are modeled as air interface utilization, channel bandwidth, and signal-to-noise ratio, respectively, providing input for the optimization algorithm, which seeks to achieve the optimal time-frequency-space resource allocation scheme. Extensive experimentation validates the effectiveness and superiority of our proposed methodology.