Quality-driven resource allocation for wireless video transmissions under energy efficiency and delay constraints

In this paper, wireless video transmissions are studied under total bandwidth and energy efficiency (EE) constraints. In order to provide the desired performance levels to the end-users in real-time video transmissions, quality of service requirements such as statistical delay constraints are also considered. Effective capacity is used as the throughput metric in the presence of such statistical delay constraints since deterministic delay bounds are difficult to guarantee due to the time-varying nature of wireless fading channels. A multiuser setup where different users have different delay guarantees is addressed. Following characterizations from the rate-distortion theory, a logarithmic model of the quality-rate relation is used for predicting the quality of the reconstructed video in terms of the peak signal-to-noise ratio at the receiver side. The optimal bandwidth allocation and the optimal power allocation/power control policies that maximize the sum video quality subject to total bandwidth and minimum EE constraints are derived. Five different resource allocation strategies are investigated, and simulation results show that the joint optimization of the bandwidth allocation and power control provides the best performance. The tradeoff between EE and video quality is also demonstrated since higher EE results in lower quality of received video sequence.