Predictive Scheduling in Rate-Adaptive Multi-user Relay Channels with Reconfiguration Delays

Opportunistic scheduling and rate-adaptation mechanisms exploit the variations in the channel states experienced by different users through the allocation of resources to users with better channel quality. Opportunistic scheduling has been considered in various contexts, typically with the assumption that rate adaptation and channel reassignment can be implemented with no delay, based on the instantaneous channel state information. This paper considers opportunistic predictive resource allocation in a multi-user rate-adaptive relay system with reconfiguration delays. Specifically, we consider a deterministic predictive scheduling problem in which any change in the channel rate or assignment induces an arbitrary reconfiguration penalty, Delta. We show that the off-line version of this problem is NP-hard, and then present an off-line approximation algorithm, which is shown to be Delta-competitive. We then provide a polynomial-complexity optimal solution for throughput maximization for the offline single-user rate adaptation problem. Finally, we present a family of online algorithms to solve the online version of the multi-user problem. These algorithms, which are amenable to distributed implementation, involve solving a set of small mixed-integer linear programs (MILPs) in parallel. We also discuss the impact of the reconfiguration penalty Delta and the look-ahead on the performance, where look-ahead is defined as the time horizon over which the channel state estimates are available.