Resource Allocation for Downlink Multiuser Video Transmission Over Wireless Lossy Networks

Abstract

The emergence of 3G and 4G wireless networks brings with it the possibility of streaming high quality video content on-demand to mobile users. Wireless video applications require appropriate scheduling techniques that make use of the specific characteristics of video content, as well as the well known gains from multiuser diversity. While fast and frequent channel feedback is available in the new generation of wireless networks, the channel estimates cannot be perfect, and channel losses should be taken into account in the packet scheduling and resource allocation. The proposed scheme is formulated as a joint optimization over the resource allocation and channel loss protection, in order to minimize the distortion of the received video sequences. The distortion is a function of the packets deliberately dropped at the transmission queue due to congestion, as well as of random channel losses. The scheme makes use of a packet prioritization strategy that orders video packets based on their contribution to reducing the expected distortion of the received video sequence. Simulation results show that the proposed technique significantly outperforms content-independent packet scheduling schemes.

Cross-Layer Framework for Multiuser Real Time H.264/AVC Video Encoding and Transmission over Block Fading MIMO Channels Using Outage Probability

“…In [4] the rate distortion (RD) modeling of the video is carried out on a frame by frame basis by modifying the approach in [7], the end-toend distortion is calculated based on [8] and the physical layer characterization is done in a similar manner as in [5] for an environment where capacity achieving channel codes are utilized. It should be noted that the work in [4] is an extension of our previous work [9,10] by replacing the H.263 source encoder with a single layer H.264/AVC and considering only the single input single output scenario without utilizing diversity.…”

“…The publications in this area, when considering the video encoding, can be categorized into those that consider transmission of scalable video [11][12][13][14], transmission of preencoded single layer video [5,6,[15][16][17][18][19][20][21], smoothing based [32,33], video trace based system level simulations [22][23][24], testbed oriented approach [31] (preencoded video is transmitted but the implementation issues are the main interest), and those that consider change of the parameter of the single layer video encoders immediately prior to transmission [26][27][28][29][30]. Only the work from the last category can be strongly correlated to our work, but the publications in this category use rate distortion models applicable only for long term rate adaptation, unsuitable for real time frame by frame adaptation due to their low precision and large complexity or do not explain how the adaptation is carried out.…”

“…When considering the channel coding it should be noted that most of the publications in the field of multiuser video transmission do not consider transmission errors or use convolutional codes. Here we investigate the video transmission in a communication system that utilizes capacity achieving channel codes [5,15,19] where the outage probability is the main cause of packet errors.…”

“…Here, we utilize the implementation of the cross-layer principle for real time H.264 single layer video encoding and transmission in systems that use capacity achieving codes presented in [4] and extend the concept to a multiuser MIMO TDMA system. It has been shown that the utilization of the multiuser principle can improve system performance in a video streaming scenario [5,6], but the joint cross-layer optimization for real time H.264/AVC single layer video encoding and transmission in a multiuser wireless system based on outage probability has not been addressed yet. The novelty of our work is in proposing a crosslayer framework for optimized real time transmission and encoding of video from multiple users in a TDMA wireless system using capacity achieving channel coding and single layer H.264/AVC video encoding in a MIMO block fading channel when channel distribution information is available at the transmitter.…”

Video Streaming Performance Under Well-Known Packet Scheduling Algorithms

“…Adapting the wireless networks that have dynamic radio propagation environment and limited radio resources to satisfy the QoS requirements of video users at acceptable levels remains a challenge that needs to be addressed when supporting the video streaming over the OFDMA based wireless IP networks [8][9][10][11]. A number of packet scheduling studies have been proposed in the literature to address this challenge.…”