Delay reduction in multi-hop device-to-device communication using network coding

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.

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.

In this paper, we propose a scheme of wireless multimedia network coded broadcast retransmission, based on Device-to-Device (D2D) communications, in which there are network coding conflicts and transmission conflicts between multiple terminal devices. For this reason, a novel instantly decodable network coding (IDNC) graph is constructed, where all the feasible coding and non-transmission collision cases are shown in the graph. Based on the constructed IDNC graph, we design the optimal broadcast strategy for batch transmission and sliding window transmission, and propose a heuristic maximum weight network coding selection algorithm (MWSA-NC) to reduce the complexity of the optimal search algorithm. The simulation results show that compared to the traditional scheme, the proposed algorithm can greatly improve the throughput of the system, reduce decoding latency and reduce video stream distortion.

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 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.

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.

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.

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.

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.

In this paper, we investigate the problem of network coding and media scheduling in wireless multihop networks. Unique characteristics of the wireless media, such as omnidirectional transmissions and destructive interference, as well as having one transceiver per wireless node, imply new code design constraints for wireless networks. Here, we formulate a linear program to solve the joint scheduling and network coding problem. Using our formulation, we demonstrate that for a large percentage of randomly generated wireless networks, the optimal scheduling time shares are unequal. All the existing network code design algorithms are based on equal scheduling time shares or the considered joint optimization problems do not have sufficient information for scheduling flows during unequal time shares. Therefore, we provide these statistics to emphasize the importance of enabling the code design algorithms to include unequal time shares. Our simulations further show that the network throughput can be significantly improved if the network code is properly designed to incorporate unequal time shares.

Chapter 1 - An Introduction to Network Coding

Physical-layer network coding (PNC) promises a significant gain In overall network throughput for multi-user cooperative communications. In a multi-unicast scenario, one drawback associated with PNC is an additional noise term, coined as network coding (NC) noise, which severely degrades the system data rate. In this paper, our contribution to address this challenging problem is source and relay power control with the objective of maximization of the minimum average achievable rate among all the source-destination pairs subject to a given total power constraint. We further develop a joint power allocation and relay selection scheme, which only rely on long-term channel statistics, to extend our results to general network topologies. We show that the joint optimization problem can be divided into two problems: optimal power allocation and optimal relay selection where the former is scalable and leads to a power assignment algorithm that exhibits the same optimization complexity for any number of sources in the network and the latter can be performed in a decentralized manner. By means of simulations, we validate our theoretical developments and verify the efficiency of our algorithm in improving the average achievable rate compared to a multi-unicast system with no power control or relay selection. We conclude that the proposed algorithm largely combats the adverse effects of NC noise while achieving near optimal fairness.

Network Coding (NC) has been shown to improve current and upcoming communication systems in terms of throughput, energy consumption and delay reduction. However, today's evaluations on network coding solutions rely on homegrown simulators that might not accurately model realistic systems. In this work, we present for the first time the steps to use Kodo, a C++11 network coding library into the ns-3 simulator and show its potential with basic examples. Our purpose is to allow ns-3 users to use a flexible and reliable set of network coding functionalities together with the technologies simulated in ns-3. Therefore, in this paper we (i) show how to set up the Kodo library with ns-3, (ii) present the underlying design of the library examples, and (iii) verify the performance of key examples with known theoretical results.

We consider a group of n wireless clients and a set of k messages. Each client initially holds a subset of messages and is interested in an arbitrary subset of messages. Each client cooperates with other clients to obtain the set of messages it wants by exchanging instantly decodable network coded (IDNC) packets. This problem setting is known as the cooperative index coding problem. Clients are assumed to be connected through an arbitrary topology. In the absence of any known algorithm to complete the exchange of packets for general network topologies, we propose a greedy algorithm to satisfy the demands of all the clients with the aim of reducing the mean completion time. Our algorithm, in a completely distributed fashion, decides which subset of clients should transmit at each round of transmission and which messages should be coded together by each transmitting client to generate an IDNC packet. The algorithm encourages transmissions which are decodable for a larger number of clients and attempts to avoid collisions. We evaluate the performance of our algorithm via numerical experiments.

Our demonstration showcases a network-coding (NC)– enabled reliability architecture for next generation wireless networks. Our NC architecture uses a flexible thread-based design, applying systematic intra-session random linear network coding as a packet erasure code at the IP layer. Using GENI WiMAX platforms, a series of point-to-point transmission experiments are conducted to compare NC with Automatic Repeated reQuest (ARQ) and Hybrid ARQ (HARQ). At the application layer, Iperf and UFTP are used to measure throughput, packet loss and file transfer delay. In our selected scenarios, NC offers up to 5.9 times gain in throughput and 5.5 times reduction in file transfer delay, compared to HARQ and joint HARQ/ARQ. Our demonstration hence illustrates that lower-layer redundancy mechanisms such as HARQ and ARQ incur high cost since they operate at the packet-level. Conversely, running NC at higher layers (e.g., IP) amortizes the cost of redundancy over several packets, thus leading to higher efficiency.