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We consider the problem of simultaneous on-demand streaming of stored videoto multiple users in a multi-cell wireless network where multiple unicaststreaming sessions are run in parallel and share the same frequency band. Eachstreaming session is formed by the sequential transmission of video "chunks,"such that each chunk arrives into the corresponding user playback buffer withinits playback deadline. We formulate the problem as a Network UtilityMaximization (NUM) where the objective is to fairly maximize users' videostreaming Quality of Experience (QoE) and then derive an iterative controlpolicy using Lyapunov Optimization, which solves the NUM problem up to anylevel of accuracy and yields an online protocol with control actions at everyiteration decomposing into two layers interconnected by the users' requestqueues : i) a video streaming adaptation layer reminiscent of DASH, implementedat each user node; ii) a transmission scheduling layer where a max-weightscheduler is implemented at each base station. The proposed chunk requestscheme is a pull strategy where every user opportunistically requests videochunks from the neighboring base stations and dynamically adapts the quality ofits requests based on the current size of the request queue. For thetransmission scheduling component, we first describe the general max-weightscheduler and then particularize it to a wireless network where the basestations have multiuser MIMO (MU-MIMO) beamforming capabilities. We exploit thechannel hardening effect of large-dimensional MIMO channels (massive MIMO) anddevise a low complexity user selection scheme to solve the underlyingcombinatorial problem of selecting user subsets for downlink beamforming, whichcan be easily implemented and run independently at each base station.

WiFlix: Adaptive Video Streaming in Massive MU-MIMO Wireless Networks