Mixed Time-Scale Generalized Fair Scheduling for Amplify-and-Forward Relay Networks

We devise an optimization framework for generalized proportional fairness (GPF) under different time scales for amplify-and-forward (AF) relay networks. In GPF scheduling, a single input parameter is used to change the fairness from throughput optimal, to proportionally fair and asymptotically to max-min fair. We extend the GPF scheduling to include a new input parameter, which determines the time-scale of fairness from short-term GPF to long-term GPF. We devise a low-complexity near-optimal algorithm to find schedules satisfying the given fairness criteria in a given time-scale. Simulations show that the proposed algorithm indeed allows the flexibility to change the fairness and its time- scale. To the best of our knowledge, this paper is the first to provide a multi-user scheduling framework for AF relays with both flexible fairness and flexible time-scales.