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User dissatisfaction due to buffering pauses during streaming is asignificant cost to the system, which we model as a non-decreasing function ofthe frequency of buffering pause. Minimization of total user dissatisfaction ina multi-channel cellular network leads to a non-convex problem. Utilizing acombinatorial structure in this problem, we first propose a polynomial timejoint admission control and channel allocation algorithm which is provably(almost) optimal. This scheme assumes that the base station (BS) knows theframe statistics of the streams. In a more practical setting, where thesestatistics are not available a priori at the BS, a learning based scheme withprovable guarantees is developed. This learning based scheme has relation toregret minimization in multi-armed bandits with non-i.i.d. and delayed reward(cost). All these algorithms require none to minimal feedback from the userequipment to the base station regarding the states of the media player bufferat the application layer, and hence, are of practical interest.

Multi-channel Resource Allocation for Smooth Streaming: Non-convexity and Bandits