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_33 @cite_41 @cite_19 adopted IDNC for D2D communications. In @cite_33 @cite_41 , the authors selected a transmitting device and its XOR packet combination to service a large number of devices with any new packet in each time slot. Moreover, the authors in @cite_19 prioritized packets based on their contributions to the video quality as in @cite_15 @cite_26 and proposed a joint device and packet selection algorithm that maximizes the overall video quality after the current time slot. The aforementioned works @cite_21 @cite_14 @cite_4 @cite_33 @cite_41 @cite_19 developed network coding schemes for a fully connected D2D network. This fully connected D2D network is not always practical due to the limited transmission range of devices. Consequently, in this paper, we consider a partially connected D2D network, which is more general and includes the fully connected D2D network as a special case. Unlike a single transmitting device in a fully connected D2D network, multiple devices can transmit simultaneously in a partially connected D2D network without causing transmission conflicts.
@cite_26 @cite_14 @cite_33 @cite_4 @cite_41 @cite_21 @cite_19 @cite_15
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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. We consider scenarios where wireless clients are missing some packets, but they collectively know every packet. The clients collaborate to exchange missing packets over an error-free broadcast channel with capacity of one packet per channel use. First, we present an algorithm that allows each client to obtain missing packets, with minimum number of transmissions. The algorithm employs random linear coding over a sufficiently large field. Next, we show that the field size can be reduced while maintaining the same number of transmissions. Finally, we establish lower and upper bounds on the minimum number of transmissions that are easily computable and often tight as demonstrated by numerical simulations. This paper investigates the use of instantly decodable network coding (IDNC) for minimizing the mean decoding delay in multicast cooperative data exchange systems, where the clients cooperate with each other to obtain their missing packets. Here, IDNC is used to reduce the decoding delay of each transmission across all clients. We first introduce a new framework to find the optimum client and coded packet that result in the minimum mean decoding delay. However, since finding the optimum solution of the proposed framework is NP-hard, we further propose a heuristic algorithm that aims to minimize the lower bound on the expected decoding delay in each transmission. The effectiveness of the proposed algorithm is assessed through simulations. In this paper we study the problem of data exchange, where each node in the system has a number of linear combinations of the data packets. Communicating over a public channel, the goal is for all nodes to reconstruct the entire set of the data packets in minimal total number of bits exchanged over the channel. We present a novel divide and conquer based architecture that determines the number of bits each node should transmit. This along with the well known fact, that it is sufficient for the nodes to broadcast linear combinations of their local information, provides a polynomial time deterministic algorithm for reconstructing the entire set of the data packets at all nodes in minimal amount of total communication. We consider the problem of data exchange by a group of closely-located wireless nodes. In this problem each node holds a set of packets and needs to obtain all the packets held by other nodes. Each of the nodes can broadcast the packets in its possession (or a combination thereof) via a noiseless broadcast channel of capacity one packet per channel use. The goal is to minimize the total number of transmissions needed to satisfy the demands of all the nodes, assuming that they can cooperate with each other and are fully aware of the packet sets available to other nodes. This problem arises in several practical settings, such as peer-to-peer systems and wireless data broadcast. In this paper, we establish upper and lower bounds on the optimal number of transmissions and present an efficient algorithm with provable performance guarantees. The effectiveness of our algorithms is established through numerical simulations. Consider a scenario of broadcasting a common content to a group of cooperating wireless nodes that are within proximity of each other. Nodes in this group may receive partial content from the source due to packet losses over wireless broadcast links. We further consider that packet losses are different for different nodes. The remaining missing content at each node can then be recovered, thanks to cooperation among the nodes. In this context, the minimum amount of time that can guarantee a complete acquisition of the common content at every node is referred to as the completion time. It has been shown that instantly decodable network coding (IDNC) reduces the completion time as compared to no network coding in this scenario. Yet, for applications such as video streaming, not all packets have the same importance and not all users are interested in the same quality of content. This problem is even more interesting when additional, but realistic constraints, such as strict deadline, bandwidth, or limited energy are added to the problem formulation. We assert that direct application of IDNC in such a scenario yields poor performance in terms of content quality and completion time. In this paper, we propose a novel Content-Aware IDNC scheme that improves content quality and network coding opportunities jointly by taking into account significance of each packet towards the desired quality of service (QoS). Our proposed Content-Aware IDNC maximizes the quality under the completion time constraint, and minimizes the completion time under the quality constraint.We demonstrate the benefits of Content-Aware IDNC through simulations. 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.