Dynamic Resource Allocation for MGS H.264/AVC Video Transmission Over Link-Adaptive Networks

Abstract

Abstract-In this paper, we address the problem of efficiently allocating network resources to support multiple scalable video streams over a constrained wireless channel. We present a resource allocation framework that jointly optimizes the operation of the link adaptation scheme in the physical layer (PHY), and that of a traffic control module in the network or medium access control (MAC) layer in multi-rate wireless networks, while satisfying bandwidth/capacity constraints. Multi-rate networks, such as IEEE 802.16 or IEEE 802.11, adjust the PHY coding and modulation schemes to maintain the reliability of transmission under varying channel conditions. Higher reliability is achieved at the cost of reduced PHY bit-rate which in turn necessitates a reduction in video stream bit-rates. The rate reduction for scalable video is implemented using a traffic control module. Conventional solutions operate unaware of the importance and loss tolerance of data and drop the higher layers of scalable video altogether. In this paper, we consider Medium Grain Scalable (MGS) extension of H.264/AVC video and develop new rate and distortion models that characterize the coded bitstream. Performance evaluations show that our proposed framework results in significant gains over existing schemes in terms of average video PSNR that can reach 3dB in some cases for different channel SNRs and different bandwidth budgets.

Modulation level allocation for MGS streaming over a multihop wireless channel

“…The proposed method is designed to find the optimal set of transmitted packets, and the modulation level of each transmitted packet, for a transmission path configured with multiple links. Therefore, if the proposed method is applied to a single link, it operates similarly to the method in [12], which is designed to determine the optimal set of transmitted packets and transmission modes. In the rest of this article, the two methods are termed Single Link Optimization (SLO) and Multi-Link Optimization (MLO).…”

“…For example, a priority index was developed in [3,4] to indicate the priority that can be used for UEP. UEP has been considered in video transmission systems, as in [5][6][7][8][9][10][11][12][13][14][15]. In [5][6][7], an application layer resource type, such as parity data, was considered.…”

“…In [5][6][7], an application layer resource type, such as parity data, was considered. In contrast, the studies [8][9][10][11][12][13][14][15] considered physical layer (PHY) optimization for SVC or MGS video streams, as in the proposed method. In [8], multiple code division multiple access (CDMA) channels were proposed, with a different processing gain for the SVC quality layers.…”

“…In [9,10], frequency diversity was utilized by orthogonal frequency division multiple access systems. Modulation and channel coding was designed to guarantee the same target bit error rate (BER) in [9,10], whereas [11,12] considered a flexible packet error rate (PER) according to the RD attribute of the video packets. The algorithms were designed to find the transmission modes of multi-rate transmitters, which minimize the expected video distortion.…”

“…The algorithms were designed to find the transmission modes of multi-rate transmitters, which minimize the expected video distortion. In other words, studies [11,12] jointly addressed UEP by only transmitting video packets with a higher priority, and by allocating more transmission time to higher priority packets. This article considers the same approach for a wireless transmission path consisting of multiple links.…”