Artificial Intelligence for Scheduling Resource Blocks in LTE/5G Networks

Abstract.

Connected devices have wildly different traffic patterns, and with 5G these patterns are expected to become even more different due to better infrastructure allowing support of different latencies, throughput and other Quality of Service (QoS) requirements. In such a scenario, the already crowded spectrum will end up excessively populated as there will be far more devices competing for transmission spectrum, on those grounds resource allocation needs to guarantee a minimum level of service for users in crowded places.

Resource scheduling is a complicated problem due to multiple goal optimization that are mutually exclusive, including, but not limited to, latency, throughput, fairness and spectrum efficiency [1]. A lot of heuristics are already in use to solve and improve block allocation, one of the simplest and most naive solution is Round-Robin scheduler, and a bit more complex ones with Genetic Algorithms (GA) [2] or other techniques. […]

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