Abstract
This paper presents a two-level scheduling scheme for video transmission over downlink orthogonal frequency-division multiple access (OFDMA) networks. It aims to maximize the aggregate quality of the video users subject to the playback delay and resource constraints, by exploiting the multiuser diversity and the video characteristics. The upper level schedules the transmission of video packets among multiple users based on an overall target bit-error-rate (BER), the importance level of packet and resource consumption efficiency factor. Instead, the lower level renders unequal error protection (UEP) in terms of target BER among the scheduled packets by solving a weighted sum distortion minimization problem, where each user weight reflects the total importance level of the packets that has been scheduled for that user. Frequency-selective power is then water-filled over all the assigned subcarriers in order to leverage the potential channel coding gain. Realistic simulation results demonstrate that the proposed scheme significantly outperforms the state-of-the-art scheduling scheme by up to 6.8 dB in terms of peak-signal-to-noise-ratio (PSNR). Further test evaluates the suitability of equal power allocation which is the common assumption in the literature.
Highlights
With the rapid growth of video traffic over wireless networks, mobile operators are expected to support a large number of video subscribers simultaneously
The video sequences are encoded in H.264 (JVT reference software, JM 18.4 [26]), with the baseline profile, a frame rate of 25 fps and an encoding rate of 350 kbps
Random I MBs are inserted into each frame, and constrained intra-prediction is activated
Summary
With the rapid growth of video traffic over wireless networks, mobile operators are expected to support a large number of video subscribers simultaneously. The quality-of-service (QoS) provisioning of these services confronts two major technical hurdles. Video communication is bandwidth intensive and delay sensitive while the inherent limited wireless resources are shared by multiple users. Loss of different video packets induces different amounts of distortion in the received video. When transmitting video over error-prone wireless channels, the impact of channel errors on the video can be extremely severe. To optimize the received video quality, it is essential to allocate radio resources to video packets in an efficient and robust way by taking into account the channel conditions and the video characteristics
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