A Study on Deep Learning Based Resource Allocation for Future Cellular Networks

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With the significantly improved transmission rate and network capacity for 5G and even the expected 6G in 2030, an increasing number of end terminals will be connected to the Internet to serve the users. And the emerging network services are expected to have user-aware or content-aware requirements for various metrics including delay, security, packet loss rate, and so on. To meet the stringent and diversified service requirements, the network resource needs to be allocated by more advanced methods than conventional mathematical models due to the extreme complexity and frequent dynamics. The Artificial Intelligence (AI) methods, especially the state-of-the-art deep learning technologies, have been regarded as the only method since it can tackle the extremely complex problems efficiently and flexibly. And AI-based network management has been regarded as the network paradigm toward 6G. The purpose of this project is to study the AI-based resource allocation for future cellular networks.In the first year of this project, the existing research has been widely surveyed and studied. And some mature results have been obtained and published on and submitted to the high impact factor IEEE journals/transactions. The AI techniques have been demonstrated to be effective for intelligently allocate the network resource for cellular networks.