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.
The works in @cite_22 @cite_37 adopted IDNC for a partially connected D2D network and addressed the problem of servicing a large number of devices with any new packet in each time slot. However, these works are not readily compatible with the real-time video sequence that has a hard deadline and unequally important video packets. In contrast to @cite_22 @cite_37 , we introduce a novel IDNC graph that represents all feasible coding and transmission conflict-free decisions in one unified framework and develop an efficient IDNC framework that prioritizes the distribution of high importance video packets to all devices before the deadline.
@cite_37 @cite_22
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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. 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. 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. This paper considers the problem of reducing the broadcast delay of wireless networks using instantly decodable network coding (IDNC) based device-to-device (D2D) communications. In D2D-enabled networks, devices help hasten the recovery of the lost packets of devices in their transmission range by sending network coded packets. To solve the problem, the different events occurring at each device are identified so as to derive an expression for the probability distribution of the decoding delay. The joint optimization problem over the set of transmitting devices and the packet combinations of each is formulated. Due to the high complexity of finding the optimal solution, this paper focuses on cooperation without interference between the transmitting users. The optimal solution, in such interference-less scenario, is expressed using a graph theory approach by introducing the cooperation graph. Extensive simulations compare the decoding delay experienced in the Point to Multi-Point (PMP), the fully connected D2D (FC-D2D) and the more practical partially connected D2D (PC-D2D) configurations and suggest that the PC-D2D outperforms the FC-D2D in all situations and provides an enormous gain for poorly connected networks.