Radio resource allocation for elastic traffic transmission with latency fairness in networks

Elastic resource management is anticipated to be prevalent in the forthcoming 6G, or 2030, networks. This approach entails not only adaptive allocation of resources but also the consideration of evolving service requirements, user behavior, and the dynamic state of the radio channel. One of the methods for distributing resources among network slices may not be equitable in terms of the required data transfer rates but aims for fairness concerning the data transmission delays. The paper formalizes the issue of resource allocation based on data transmission latency as a queuing system with a discriminatory processor-sharing discipline for classes of elastic traffic. The authors propose determining the discipline parameters — the weights for each class — according to the residual data transmission time. The fairness of resource allocation is evaluated using the Jain's fairness index which is based on average transmission times.