In this paper, we study the problem of distributing a real-time video sequence to a group of partially connected cooperative wireless devices using instantly decodable network coding (IDNC). In such a scenario, the coding conflicts occur to service multiple devices with an immediately decodable packet and the transmission conflicts occur from simultaneous transmissions of multiple devices. To avoid these conflicts, we introduce a novel IDNC graph that represents all feasible coding and transmission conflict-free decisions in one unified framework. Moreover, a real-time video sequence has a hard deadline and unequal importance of video packets. Using these video characteristics and the new IDNC graph, we formulate the problem of minimizing the mean video distortion before the deadline as a finite horizon Markov decision process (MDP) problem. However, the backward induction algorithm that finds the optimal policy of the MDP formulation has high modelling and computational complexities. To reduce these complexities, we further design a two-stage maximal independent set selection algorithm, which can efficiently reduce the mean video distortion before the deadline. Simulation results over a real video sequence show that our proposed IDNC algorithms improve the received video quality compared to the existing IDNC algorithms.
Several other works including @cite_13 @cite_15 @cite_26 @cite_29 considered video streaming applications with unequally important packets. The work in @cite_13 proposed an IDNC scheme that is asymptotically throughput optimal for the three-device system subject to sequential packet delivery deadline constraints. Moreover, the works in @cite_15 @cite_26 determined the importance of each video packet based on its contribution to the video quality and proposed IDNC schemes to maximize the overall video quality at the devices. The aforementioned works @cite_20 @cite_28 @cite_8 @cite_13 @cite_15 @cite_26 @cite_29 developed IDNC schemes for conventional PMP networks, which are fundamentally different from partially connected D2D networks considered in this paper.
@cite_26 @cite_8 @cite_28 @cite_29 @cite_15 @cite_13 @cite_20
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In this paper, we study video streaming over wireless networks with network coding capabilities. We build upon recent work, which demonstrated that network coding can increase throughput over a broadcast medium, by mixing packets from different flows into a single packet, thus increasing the information content per transmission. Our key insight is that, when the transmitted flows are video streams, network codes should be selected so as to maximize not only the network throughput but also the video quality. We propose video-aware opportunistic network coding schemes that take into account both the decodability of network codes by several receivers and the importance and deadlines of video packets. Simulation results show that our schemes significantly improve both video quality and throughput. This work is a first step towards content-aware network coding. In this paper, we consider the problem of minimizing the completion delay for instantly decodable network coding (IDNC) in wireless multicast and broadcast scenarios. We are interested in this class of network coding due to its numerous benefits, such as low decoding delay, low coding and decoding complexities, and simple receiver requirements. We first extend the IDNC graph, which represents all feasible IDNC coding opportunities, to efficiently operate in both multicast and broadcast scenarios. We then formulate the minimum completion delay problem for IDNC as a stochastic shortest path (SSP) problem. Although finding the optimal policy using SSP is intractable, we use this formulation to draw the theoretical guidelines for the policies that can minimize the completion delay in IDNC. Based on these guidelines, we design a maximum weight clique selection algorithm, which can efficiently reduce the IDNC completion delay in polynomial time. We also design a quadratic-time heuristic clique selection algorithm, which can operate in real-time applications. Simulation results show that our proposed algorithms significantly reduce the IDNC completion delay compared to the random and maximum-rate algorithms, and almost achieve the global optimal completion delay performance over all network codes in broadcast scenarios. We consider the scenario of broadcasting for realtime applications and loss recovery via instantly decodable network coding. Past work focused on minimizing the completion delay, which is not the right objective for real-time applications that have strict deadlines. In this work, we are interested in finding a code that is instantly decodable by the maximum number of users. First, we prove that this problem is NP-Hard in the general case. Then we consider the practical probabilistic scenario, where users have i.i.d. loss probability, and the number of packets is linear or polynomial in the number of users. In this case, we provide a polynomial-time (in the number of users) algorithm that finds the optimal coded packet. Simulation results show that the proposed coding scheme significantly outperforms an optimal repetition code and a COPE-like greedy scheme. This work aims at introducing two novel packet retransmission techniques for reliable multicast in the framework of Instantly Decodable Network Coding (IDNC). These methods are suitable for order- and delay-sensitive applications, where some information is of high importance for an earlier gain at the receiver's side. We introduce hence an Unequal Error Protection (UEP) scheme, showing by simulations that the Quality of Experience (QoE) for the end-users is improved even without complex encoding and decoding. In recent years, Wireless Local Area Networks (WLAN) have become the premier choice for many homes and enterprises. WiMAX (Worldwide Interoperability for Microwave Access) has also emerged as the wireless standard that aims to deliver data over long distances, and can potentially provide wireless broadband access as an alternative to the wired cable and DSL networks. Parallel with the surge of wireless networks is the explosive growth of multimedia applications. Therefore, it is important to explore efficient methods for delivering multimedia data in such wireless settings. In this paper, we propose a network coding based scheduling policy to be used at WLAN-like Access Point (AP) or at a WiMAX-like broadcast station that optimizes the multimedia transmission in both broadcast and unicast settings. In particular, the contributions of this paper include (a) a framework for increasing the bandwidth efficiency of broadcast and unicast sessions in a wireless network based on network coding techniques and (b) an optimized scheduling algorithm based on the Markov Decision Process (MDP) to maximize the quality of multimedia applications. Simulations and theoretical results demonstrate the advantages of our approach over the conventional techniques. Multimedia streaming applications have stringent Quality-of-Service (QoS) requirements. Typically, each packet is associated with a packet delivery deadline. This work models and considers streaming broadcast of stored video over the downlink of a single cell. We first generalize the existing class of immediately-decodable network coding (IDNC) schemes to take into account the deadline constraints. The performance analysis of IDNC schemes are significantly complicated by the packet deadline constraints (from the application layer) and the immediate-decodability requirement (from the network layer). Despite this difficulty, we prove that for independent channels, the IDNC schemes are asymptotically throughput-optimal subject to the deadline constraints when there are no more than three users and when the video file size is sufficiently large. The deadline-constrained throughput gain of IDNC schemes over non-coding scheme is also explicitly quantified. Numerical results show that IDNC schemes strictly outperform the non-coding scheme not only in the asymptotic regime of large files but also for small files. Our results show that the IDNC schemes do not suffer from the substantial decoding delay that is inherent to existing generation-based network coding protocols. Consider a source broadcasting M packets to N receivers over independent erasure channels, where perfect feedback is available from the receivers to the source, and the source is allowed to use coding. We investigate offline and online algorithms that optimize delay, both through theoretical analysis as well as simulation results.