Energy-Efficient and Radio Resource Control State Aware Resource Allocation with Fairness Guarantees

In the next-generation wireless networks, energy efficiency (EE) is a fundamental requirement due to the limited battery power and the deployment of various devices in hardly accessible areas. While a plethora of approaches have been proposed to increase users' EE, there are still many unresolved issues stemming mainly from the limited wireless resources. In this paper, we investigate the energy-efficient resource allocation, taking into account users' radio resource control (RRC) state. We aim to achieve max-min fairness among users in an uplink orthogonal frequency-division multiple access (OFDMA) system while fulfilling data rate requirements and transmit power constraints. In particular, we avoid waste of the energy through unnecessary state transitions when no network resources are available. We study the impact of the RRC Resume procedure on users' EE and propose allocating resources while users are in their current RRC Connected or RRC Inactive state. The solution is obtained from a constrained optimization problem, whose output is max-min fair and energy-efficient. To that end, we use generalized fractional programming and the Lagrangian dual decomposition approach to allocate the radio resources and transmission power iteratively. Using extensive realistic simulations with input parameters from measurement data, we compare the results of our approach against benchmark models and show the performance improvements RRC state awareness brings. Specifically, using our approach, the users' EE increases by at least 10% on average.