Downlink Resource Allocation Under Time-Varying Interference: Fairness and Throughput Optimality

Abstract

We address the problem of downlink resource allocation in the presence of time-varying interference. We consider a scenario where users served by a base station face interference from a neighboring base station. We model the interference from the neighboring base station as an ON/OFF renewal process, that arises due to its idle and busy cycles. The users feedback their downlink signal to interference plus noise ratio (SINR) values to their base station, but these values are outdated. In this setting, we characterize how the resource allocation layer can optimally exploit the reported SINR values, which could be unreliable due to time-varying interference. In particular, we propose resource allocation policies in two well-known paradigms. First, we address the problem of $\alpha $ –fair scheduling, and propose a policy that ensures asymptotic convergence to the optimal $\alpha $ –fair throughput. Second, we propose a throughput optimal resource allocation policy, i.e., a policy that can stably support the largest possible set of traffic rates under the interference scenario considered. Estimating the outage probability from the outdated SINR values plays an important role in both scheduling paradigms, and we accomplish this using tool from renewal theory.