  We investigate the impact of cooperative relaying on uplink and downlink
multi-user (MU) wireless video transmissions. The objective is to maximize the
long-term sum of utilities across the video terminals in a decentralized
fashion, by jointly optimizing the packet scheduling, the resource allocation,
and the cooperation decisions, under the assumption that some nodes are willing
to act as cooperative relays. A pricing-based distributed resource allocation
framework is adopted, where the price reflects the expected future congestion
in the network. Specifically, we formulate the wireless video transmission
problem as an MU Markov decision process (MDP) that explicitly considers the
cooperation at the physical layer and the medium access control sublayer, the
video users' heterogeneous traffic characteristics, the dynamically varying
network conditions, and the coupling among the users' transmission strategies
across time due to the shared wireless resource. Although MDPs notoriously
suffer from the curse of dimensionality, our study shows that, with appropriate
simplications and approximations, the complexity of the MU-MDP can be
significantly mitigated. Our simulation results demonstrate that integrating
cooperative decisions into the MU-MDP optimization can increase the resource
price in networks that only support low transmission rates and can decrease the
price in networks that support high transmission rates. Additionally, our
results show that cooperation allows users with feeble direct signals to
achieve improvements in video quality on the order of 5-10 dB peak
signal-to-noise ratio (PSNR), with less than 0.8 dB quality loss by users with
strong direct signals, and with a moderate increase in total network energy
consumption that is significantly less than the energy that a distant node
would require to achieve an equivalent PSNR without exploiting cooperative
diversity.
