Interference Shaping for Improved Quality of Experience for Real-Time Video Streaming
The unpredictability of the wireless medium poses a major challenge to delivering a high Quality of Experience (QoE) for real-time video services. Bursty co-channel interference is a prominent cause of wireless throughput variability, which leads to video QoE degradation, even for a fixed average channel quality. In this paper, the authors propose and analyze a network-level resource management algorithm termed interference shaping to smooth out the throughput variations (and hence improve the QoE) of video users by decreasing the peak rate of co-channel best effort users. Wireless link capacity variations are mapped to the real-time video packet loss rate, and the interference shaping QoE gain for video users is quantified by benchmarking against a modified Multi-Scale Structural SIMilarity (H-MS-SSIM) index.