LAUSR

In this paper, we consider a multi-user interference network where a central controller allocates power resources to multiple base stations for maximizing the entire network utility under a long-term power budget constraint. The optimal power allocation strategy depends on accurate and instant channel state information (CSI). However, due to users’ mobility and the existence of channel fading and interference, timely channel estimation is unavailable. To overcome the difficulty of unknown channel states, we resort to the Lyapunov drift analysis framework and design an online power allocation algorithm based on historical observations. The algorithm can be proven to achieve sub-linear performance for both cumulative regret and power budget violation. The sub-linear regret indicates the proposed algorithm can asymptotically achieve the optimal static power allocation performance in hindsight. Moreover, we use a general doubling trick to construct a parameter-free algorithm based on the aforementioned online algorithm without the knowledge of time horizon $T$, which can be proven to preserve the order of the regret and violation upper bound. Simulation results are provided to validate the performance of the proposed online algorithms compared with the offline cave-filling algorithms, as well as its robustness in the presence of adversarial interference.