  The problem addressed is that of optimally controlling, in a decentralized
fashion, the download of mobile video, which is expected to comprise 75 % of
total mobile data traffic by 2020. The server can dynamically choose which
packets to download to clients, from among several packets which encode their
videos at different resolutions, as well as the power levels of their
transmissions. This allows it to control packet delivery probabilities, and
thereby, for example, avert imminent video outages at clients. It must however
respect the access point's constraints on bandwidth and average transmission
power. The goal is to maximize video "Quality of Experience" (QoE), which
depends on several factors such as (i) outage duration when the video playback
buffer is empty, (ii) number of outage periods, (iii) how many frames
downloaded are of lower resolution, (iv) temporal variations in resolution,
etc.
  It is shown that there exists an optimal decentralized solution where the AP
announces the price of energy, and each client distributedly and dynamically
maximizes its own QoE subject to the cost of energy. A distributed iterative
algorithm to solve for optimal decentralized policy is also presented. Further,
for the client-level QoE optimization, the optimal choice of video-resolution
and power-level of packet transmissions has a simple monotonicity and threshold
structure vis-a-vis video playback buffer level. When the number of orthogonal
channels is less than the number of clients, there is an index policy for
prioritizing packet transmissions. When the AP has to simply choose which
clients' packets to transmit, the index policy is asymptotically optimal as the
number of channels is scaled up with clients.
