Instantly decodable network coding for real-time scalable video broadcast over wireless networks

Karim et al. EURASIP Journal on Advances in Signal Processing (2016) 2016:3 DOI 10.1186/s13634-015-0299-6 RESEARCH Open Access Instantly decodable network coding for real-time scalable video broadcast over wireless networks Mohammad S. Karim1* , Parastoo Sadeghi1 , Sameh Sorour2 and Neda Aboutorab1 Abstract In this paper, we study real-time scalable video broadcast over wireless networks using instantly decodable network coding (IDNC). Such real-time scalable videos have hard deadline and impose a decoding order on the video layers. We first derive the upper bound on the probability that the individual completion times of all receivers meet the deadline. Using this probability, we design two prioritized IDNC algorithms, namely the expanding window IDNC (EW-IDNC) algorithm and the non-overlapping window IDNC (NOW-IDNC) algorithm. These algorithms provide a high level of protection to the most important video layer, namely the base layer, before considering additional video layers, namely the enhancement layers, in coding decisions. Moreover, in these algorithms, we select an appropriate packet combination over a given number of video layers so that these video layers are decoded by the maximum number of receivers before the deadline. We formulate this packet selection problem as a two-stage maximal clique selection problem over an IDNC graph. Simulation results over a real scalable video sequence show that our proposed EW-IDNC and NOW-IDNC algorithms improve the received video quality compared to the existing IDNC algorithms. Keywords: Wireless broadcast, Real-time scalable video, Individual completion time, Instantly decodable network coding 1 Introduction Network coding has shown great potential to improve throughput, delay, and quality of services in wireless networks [1–10]. These merits of network coding make it an attractive candidate for multimedia applications [7–9]. In this paper, we are interested in utilizing network coding in real-time scalable video applications [11, 12], which compress video frames in the form of one base layer and several enhancement layers. The base layer provides the basic video quality, and the enhancement layers provide successive improved video qualities. Using such a scalable video stream, the sender adapts the video bit rate compatible to the available network bandwidth by sending the base layer and as many enhancement layers as possible. Moreover, the real-time scalable video has two distinct characteristics. First, it has a hard deadline before which the video layers need to be decoded to be usable *Correspondence: 1 The Australian National University, Canberra, Australia Full list of author information is available at the end of the article at the application. Second, the video layers exhibit a hierarchical order such that a video layer can be decoded only if this layer and all its lower layers are received. Even though scalable video can tolerate the loss of one or more enhancement layers, this adversely affects the video quality experienced by viewers. Therefore, it is desirable to design network coding schemes so that the received packets before the deadline contribute to decoding the maximum number of video layers. Fountain codes such as random linear network codes (RLNC) [13–18], raptor codes [19], and LT codes [20–22] have been studied extensively for efficient data delivery in wireless networks. These codes offer significant performance gains compared to conventional channel codes since channel protection is not pre-determined [21–25]. In case of scalable video transmission, combining the layered approach with fountain codes has shown to further improve the quality of video streaming in [26–30] as it provides unequal error protection to different importance layers. In particular, scalable video delivery from multiple servers to a set of receivers was studied in [26], © 2016 Karim et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Karim et al. EURASIP Journal on Advances in Signal Processing (2016) 2016:3 where each video layer is independently protected by raptor codes. Another work in [27] also studied unequal error protection raptor codes for increasing error robustness of scalable video transmission. The authors in [28] studied expanding window fountain codes for scalable video multicast and illustrated the benefits of using expanding window approaches. Random linear network coding (RLNC) and instantly decodable network coding (IDNC) have been adopted over LT and raptor codes in many applications and systems [5, 13, 15–18, 31, 32] due to their abilities of simple extension to general networks and providing better tradeoffs among bandwidth efficiency, complexity, and delay [7]. The works in [13, 17, 18, 33] designed expanding window-based RLNC strategies for scalable video transmission such that coded packets are formed across different numbers of video layers. In particular, the authors in [17] used a probabilistic approach for selecting coding windows and included the packets in the lower video layers into all coded packets to obtain high decoding probabilities for the lower layers. Moreover, the authors in [18] considered a scalable video transmission with a hard deadline and used a deterministic approach for selecting coding windows over all transmissions before the deadline. Another work in [33] continued the work in [17] and addressed the problem of jointly determining the coding strategy and the scheduling decisions when receivers obtain layered video data from multiple servers. Moreover, a resource-allocation framework for network-coded scalable video multicast services was proposed in [13] that minimizes the number of broadcast packets on each downlink channel while providing service guarantees to a predetermined fraction of receivers. Our work is inspired by the recent works on scalable video transmission using RLNC in [13, 17, 18, 33]. In this work, we adopt XOR-based instantly decodable network coding (IDNC) to investigate its performance for scalable video transmission. Despite the superior throughput performance of RLNC, IDNC has drawn significant attention due to the following attractive properties. IDNC aims to provide instant packet decodability upon successful packet reception at the receivers. This instant decodability property allows a progressive recovery of the video layers as the receivers decode more packets. Furthermore, the encoding process of IDNC is performed using simple XOR operations compared to the more complicated operations over large Galois fields performed in RLNC. The decoding process of IDNC is also performed using (...truncated)