Video distortion reduction with instantly decodable network coding and Device-to-Device communications

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 modeling 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 with the existing IDNC algorithms.

Instantly decodable network coding (IDNC) reduces the completion delay of packet retransmission for multicast services in wireless point-to-multipoint (PMP) networks. Compared with multicast services, multiple unicast services may be more common in PMP networks. Reducing completion delay using IDNC for multiple unicast services is still an open problem. According to the construction features of IDNC, we find that if some unicast retransmissions are combined as a retransmission group, IDNC benefits from network coding (NC) considerably, which increases retransmission efficiency. Based on this observation, we study the total completion delay of all these unicast transmissions with intersession NC. In this paper, we provide an intersession insight into the IDNC method. Specifically, we propose a framework that contains 1) a general solution to this minimum completion delay (MCD) problem, which is modeled as a bin-packing problem, and 2) a lower bound of completion delay for the MCD solution. Additionally, we provide a high-efficiency greedy algorithm to solve the MCD problem with low computational complexity. Simulation results demonstrate that the proposed method saves almost 43% retransmissions in PMP networks and makes 87.5% retransmission packets benefit from the NC transmission.

The traditional instantly decodable network coding (IDNC) schemes discard the non-instantly decodable packets (NIDPs), which results in the loss of useful information. In this letter, we consider a network coding scheme named as buffered instantly decodable network coding (B-IDNC) where each receiving node can cache the NIDPs containing two unreceived packets for subsequent network decoding, and give a decoding algorithm by utilizing the maximum decoding clique. The maximum decoding clique is defined as a subset of vertices in the IDNC graph, which can be decoded together. We approximate the average packet decoding delay minimization problem as the maximum weight encoding clique problem, and a heuristic algorithm named as maximum decoding clique based maximum weight vertex (MDC-MWV) searching algorithm is proposed to solve the approximated problem. Simulation results show that our proposed algorithm can reduce the average packet decoding delay compared with the conventional IDNC schemes.

This paper considers a heterogeneous network architecture wherein devices use two wireless interfaces to receive packets from the base station and to transmit or receive packets from other devices concurrently. For such a network architecture, this paper focuses on time-critical and order-constrained applications that require quick and reliable in-order decoding of the packets. This paper first introduces the dual delivery delay as a measure of degradation compared with the optimal in-order packet delivery to the devices. It then addresses the minimum delivery delay problem using instantly decodable network coding (IDNC). In particular, the dual interface IDNC graph is constructed to represent all feasible coding opportunities and conflict-free transmissions. Subsequently, the minimum delivery delay problem is shown to be equivalent to a maximum weight independent set selection problem over the dual interface IDNC graph. Simulation results demonstrate that the proposed IDNC algorithm effectively reduces the delivery delay as compared with the existing network coding algorithms. Especially, for a layered video transmission, the proposed solution provides a sequential delivering of video layers to individual devices.

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.

Most of Wireless Sensor Networks (WSNs) are usually deployed in hostile environments where the communications conditions are not stable and not reliable. Hence, there is a need to design an effective distributed schemes to enable the sensors cooperating in order to recover the sensed data. In this paper, we establish a novel cooperative data exchange (CDE) scheme using instantly decodable network coding (IDNC) across the sensor nodes. We model the problem using the cooperative game theory in partition form. We develop also a distributed merge-and-split algorithm in order to form dynamically coalitions that maximize their utilities in terms of both energy consumption and IDNC delay experienced by all sensors. Indeed, the proposed algorithm enables these sensors to self-organize into stable clustered network structure where all sensors do not have incentives to change the cluster he is part of. Simulation results show that our cooperative scheme allows nodes not only to reduce the energy consumption, but also the IDNC completion time.

This paper investigates the delay minimization problem for instantly decodable network coding (IDNC) based device-to-device (D2D) communications. In D2D enabled systems, users cooperate to recover all their missing packets. The paper proposes a game theoretic framework as a tool for improving the distributed solution by overcoming the need for a central controller or additional signaling in the system. The session is modeled by self-interested players in a non-cooperative potential game. The utility functions are designed so as increasing individual payoff results in a collective behavior which achieves both a desirable system performance in a shared network environment and the Nash equilibrium. Three games are developed whose first reduces the completion time, the second the maximum decoding delay and the third the sum decoding delay. The paper, further, improves the formulations by including a punishment policy upon collision occurrence so as to achieve the Nash bargaining solution. Learning algorithms are proposed for systems with complete and incomplete information, and for the imperfect feedback scenario. Numerical results suggest that the proposed game-theoretical formulation provides appreciable performance gain against the conventional point-to-multipoint (PMP), especially for reliable user-to-user channels.

We are concerned with designing feedback-based adaptive Instantly Decodable Network Coding (IDNC) schemes with the aim of minimizing retransmission times in wireless multicast and broadcast scenarios. In this paper, we first analyze the multiple factors influencing the transmission times and give the quantitative formula. Meantime, we introduce the concept of Cache-based Instantly Decodable Network Coding (C-IDNC) that the correctly received undecodable retransmission packets are waited in the cache for a future network decoding opportunity rather than delete. Then, we formulate the retransmission times minimization problem as an max-weight search problem and propose efficient algorithms for finding its optimal solution. Further, we propose a heuristic algorithms with worst case linear execution complexity based on sorting and iteration. Simulation results show that our proposed algorithms significantly reduce the IDNC retransmission times compared to previous works.

Network coding has recently been applied to wireless networks and has achieved some initial success. Researches in wireless network coding have been mostly focusing on utilizing the broadcast nature of the wireless networks. In this paper, we propose a novel network coding framework for wireless relay networks that also takes into consideration the fading and error prone nature of the wireless networks. First, we extend the traditional network coding in lossless networks which operates on 0-1 bits, to a new framework which defines network coding on the posterior probability of each bit. This new framework allows an imperfect decode-recode process at a relay node and avoids possible error propagation when a hard decision is made at the relay node. It implicitly integrates decode-and-forward and estimate-and-forward strategies for wireless network coding to address the technical issues of channel fading and transmission errors. The proposed approach is validated through both theoretical analysis and extensive simulations. Both analysis and simulation confirm that this new framework is able to achieve significant gain over traditional network coding. This new framework also enables the introduction of adaptive scheme into network coding. We demonstrate a basic adaptation scheme and present some preliminary experimental results. The proposed adaptive scheme will lay down an essential foundation in this emerging field of wireless network coding in order to address issues related to link heterogeneity.

This paper studies joint scheduling and network coding in wireless multicast networks with independent sources. Designing a network coding solution for wireless networks involves scheduling interference-free transmissions and optimizing a performance measure for the predetermined scheduling sets, followed by constructing network codes for the specific solution. In such a design process, the results of prior steps need to provide enough information to the subsequent steps. In this paper, we formulate a linear optimization problem whose results can be used to design a coding solution. We build our work on previous works and present statistics that show the importance of incorporating unequal timeshares in designing network codes. In particular, our statistics show a throughput improvement of about 35% in maximum flow problems and energy savings between 13% and 30%, depending on the network size, in minimum energy problems. We also present the requirements of code construction algorithms for wireless networks that capture the broadcast property of these networks and can design proper codes when timeshares are unequal. In particular, the adaptation of a centralized network coding scheme for wireless networks is discussed. Overall, the work reported here provides a three-step solution to derive network codes that optimize a performance criterion of interest while also solving the scheduling problem in multihop wireless networks.

In this paper, we investigate the use of instantly decodable network coding (IDNC) for improving two fundamental performance metrics, namely, the completion time (as a measure of throughput) and mean decoding delay, in multicast cooperative data exchange (CDE) systems, where a group of geographically close clients cooperate with each other to obtain their missing packets. Here, an IDNC scheme is used for the transmissions across these clients. We utilize the stochastic shortest path (SSP) technique to study the minimum mean completion time problem. However, since finding the optimum solution is intractable, we use the obtained formulation to draw some theoretical guidelines to heuristically find solutions that can efficiently reduce the completion time. Second, we formulate the minimum mean decoding delay problem as selecting the appropriate maximal clique over well-structured graphs at the clients, and in order to reduce its complexity, we propose a simple heuristic algorithm for it. The effectiveness of our proposed algorithms is verified through extensive simulations and comparisons with existing techniques.

This paper addresses the Quality of Service (QoS) degradation problem of wireless relay node failures in multihop Worldwide interoperable Microwave Access (WiMAX) and Long Term Evolution (LTE) networks. In general, node protection in a communication network increases the reliability of the traffic flow from source to destination. For wireless networks, implementing the traditional 1+1 protection scheme increases the capital cost, as resources cannot be fully utilized. On the other hand, the design and implementation of the 1:N protection scheme in wireless networks for greater value of N (> 2) is very difficult, due to wireless network coverage and the physical layer design. To overcome the above drawbacks, a technique based on network coding is proposed for node protection in multihop wireless networks. In multihop wireless networks, few research efforts are concentrated on node protection schemes using network coding. Moreover, to best of our knowledge, no reports have been published on measuring the QoS performance for node protection in 4G wireless networks using network coding. In this paper, we first describe the node protection scheme using XOR network coding for multihop 4G wireless networks. Then, we measure the QoS performance, such as packet delivery ratio (PDR), latency and jitter, for different scenarios. The scenarios include a failure of a single relay node and failures of two relay nodes with and without our protection scheme and user's mobility. The simulation results show that the QoS performance with protection against a single relay node failure and failures of two relay nodes are very close to that of no failure scenario, while the network reliability increases due to the protection mechanism. Also, we report a decoding problem in multihop wireless networks using XOR network coding.

Network coding is a technology with great potentiality in improving wireless multi-hop network throughput. And some routings combined with network coding have been proposed for wireless multi-hop network. In the routings combined with network coding, network coding condition is used to find network coding opportunities, which is very important to the performance improving of routings combined with network coding. However, the network coding conditions defined by existing routings combined with network coding unilaterally focus on the growth of network coding opportunities, which results in the increasing of cost and delay in routing discovery. Moreover, the more flows participating network coding, the higher probability of decoding failure, which degrade the network coding gain. In this paper, low complexity network coding condition (LCNC) is proposed. LCNC only detects two-flows network coding opportunity, and ensures the destination make successful decoding. In addition, the actual network coding gain is designed through analysis of link quality. Network coding opportunity will be ignored in case the actual network coding gain is negative. Based on LCNC, a low complexity network coding aware routing (LNCR) is designed aiming wireless multi-hop network. Simulation results demonstrate that LNCR obtain a balance between network coding gain and routing discovery cost, and can obtain higher network throughput when the network load is high compared with the classical network coding aware routings.

In this paper, a joint network and channel coding (JNCC) strategy with retransmissions is proposed for two canonical network elements, broadcast channel with receiver side information (BC-SI) and orthogonal multiple access channel with correlated sources (MAC-CS). By extending the derived results for BC-SI and orthogonal MAC-CS to a multi-hop wireless network with multiple sources and multiple destinations (MS-MD), we propose a complete JNCC strategy. We also quantify the network throughput by applying the renewal-reward theorem. The results show that our proposed JNCC strategy outperforms conventional separate network and channel coding (SNCC) strategy with random linear network coding (RLNC), thus proving an instance where joint coding is better than separate coding in wireless networks.

In this paper, we consider a wireless multicast network with multiple sources, relays, and destinations. We adopt a multi-hop decode-and-forward relay protocol such that two canonical subnetworks are relevant, namely broadcast channel with receiver side information (BC-RSI) and orthogonal multiple access channel with correlated sources and receiver side information (MAC-CS-RSI). A joint network and channel coding (JNCC) strategy is proposed by exploiting ARQ, RSI, and correlated sources. The proposed JNCC strategy does not require the knowledge of RSI nor any transmit channel state information, such that each transmitter simply performs retransmissions until the intended receivers have accumulated enough mutual information to successfully decode all desired messages. This successful decoding is then conveyed from the receivers to the respective transmitters via an acknowledgement message. To measure the performance of the proposed JNCC strategy with ARQ, we derive closed-form expressions of network throughput by applying the renewal-reward theorem. Analytical results show that the proposed JNCC strategy outperforms, in terms of network throughput, the conventional separate network and channel coding strategy with random linear network coding.