Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks

• We formulate a multi-objective problem for energy and distortion minimization.
• We propose energy efficient techniques leading to enhanced quality of service.
• Cooperative cluster formation is included in the proposed techniques.
• Single and multiple description coding, and scalable video coding are investigated.
• LTE resource allocation with both unicasting and multicasting is taken into account.

Real-time video streaming over long-term evolution (LTE) networks is investigated in the presence of mobile-to-mobile collaboration. A multi-objective problem for energy and distortion minimization is formulated and an energy-efficient, quality of service (QoS) aware suboptimal approach is presented for collaborative video transmission. In the proposed approach, mobiles are grouped into collaborative clusters using a low-complexity clustering algorithm. In each cluster, collaboration is implemented by having a cluster head send the content to other cluster members using a short-range wireless communications technology. The cluster heads receive the data on the long-range LTE links, either via unicasting or multicasting. LTE scheduling is taken into account on the long range transmissions. Videos with single description coding (SDC), multiple description coding (MDC), and scalable video coding (SVC) are considered. Results show that the proposed approach leads to significant energy savings and enhanced QoS compared to the non-collaborative scenario. Furthermore, MDC is shown to outperform SDC in terms of QoS, at the cost of a slight increase in energy consumption. The same conclusions were reached with respect to SVC compared to single layer coding.