  We consider a discrete-time multi-channel network where the destination
collects time-sensitive packets from multiple sources with sided channel
information. The popular metric, Age of Information (AoI), is applied to
measure the data freshness at the destination. Due to the interference
constraint, only disjoint source-channel pairs can be chosen for transmission
in each time slot, and the decision maker should choose the optimal scheduling
pairs to minimize the average AoI at the destination. To learn the optimal
channel selection, we apply the linear contextual bandit (LCB) framework by
utilizing the sided information provided by pilots. Concretely, we establish
the relationship between AoI regret and sub-optimal channel selection times and
propose both age-independent and age-dependent algorithms. The former method is
proven to achieve the sub-linear AoI regret but is outperformed by the latter
algorithm both in the linear and non-linear contextual model in simulation.
