Growth Codes: Intermediate Performance Analysis and Application to Video

Growth codes are a subclass of Rateless codes that have found interesting applications in data dissemination problems. Compared to other Rateless and conventional channel codes, Growth codes show improved intermediate performance which is particularly useful in applications where partial data presents some utility. In this paper, we investigate the asymptotic performance of Growth codes using the Wormald method, which was proposed for studying the Peeling Decoder of LDPC and LDGM codes. Compared to previous works, the Wormald differential equations are set on nodes' perspective which enables a numerical solution to the computation of the expected asymptotic decoding performance of Growth codes. Our framework is appropriate for any class of Rateless codes that does not include a precoding step. We further study the performance of Growth codes with moderate and large size codeblocks through simulations and we use the generalized logistic function to model the decoding probability. We then exploit the decoding probability model in an illustrative application of Growth codes to error resilient video transmission. The video transmission problem is cast as a joint source and channel rate allocation problem that is shown to be convex with respect to the channel rate. This illustrative application permits to highlight the main advantage of Growth codes, namely improved performance in the intermediate loss region. © 1972-2012 IEEE

Decoding Delay Minimization in Inter-Session Network Coding

Intra-session network coding has been shown to offer significant gains in terms of achievable throughput and delay in settings where one source multicasts data to several clients. In this paper, we consider a more general scenario where multiple sources transmit data to sets of clients over a wireline overlay network. We propose a novel framework for efficient rate allocation in networks where intermediate network nodes have the opportunity to combine packets from different sources using randomized network coding. We formulate the problem as the minimization of the average decoding delay in the client population and solve it with a gradient-based stochastic algorithm. Our optimized inter-session network coding solution is evaluated in different network topologies and is compared with basic intra-session network coding solutions. Our results show the benefits of proper coding decisions and effective rate allocation for lowering the decoding delay when the network is used by concurrent multicast sessions

Rate Maximization in Vehicular uRLLC with Optical Camera Communications

Optical camera communication (OCC) has emerged as a key enabling technology for the seamless operation of future autonomous vehicles. By leveraging the supreme performance of OCC, we can meet the stringent requirements of ultra-reliable and low-latency communication (uRLLC) in vehicular OCC. In this paper, we introduce a rate optimization approach in vehicular OCC through optimal power allocation while respecting uRLLC requirements. We first formulate a discrete-rate optimization problem as a mixed-integer programming (MIP) subject to average transmit power and uRLLC constraints for a given set of modulation schemes. To reduce the complexity in solving the MIP problem, we convert the discrete-rate problem into a continuous-rate optimization scheme. Then, we present an algorithm based on Lagrangian relaxation and Bisection method to solve the optimization problem. Considering the proposed algorithm, we drive the rate optimization and power allocation scheme for both discrete-rate and continuous-rate optimization schemes while satisfying uRLLC constraints. We first analyze the performance of the proposed system model through simulations. We then investigate the impact of proposed power allocation and rate optimization schemes on average rate and latency for different target bit error rates. The results show that increasing the transmit power allocation improves the average rate and latency performance.Comment: 30 Pages, 13 Figure

Selection of network coding nodes for minimal playback delay in streaming overlays

Network coding permits to deploy distributed packet delivery algorithms that locally adapt to the network availability in media streaming applications. However, it may also increase delay and computational complexity if it is not implemented efficiently. We address here the effective placement of nodes that implement randomized network coding in overlay networks, so that the goodput is kept high while the delay for decoding stays small in streaming applications. We first estimate the decoding delay at each client, which depends on the innovative rate in the network. This estimation permits to identify the nodes that have to perform coding for a reduced decoding delay. We then propose two iterative algorithms for selecting the nodes that should perform network coding. The first algorithm relies on the knowledge of the full network statistics. The second algorithm uses only local network statistics at each node. Simulation results show that large performance gains can be achieved with the selection of only a few network coding nodes. Moreover, the second algorithm performs very closely to the central estimation strategy, which demonstrates that the network coding nodes can be selected efficiently in a distributed manner. Our scheme shows large gains in terms of achieved throughput, delay and video quality in realistic overlay networks when compared to methods that employ traditional streaming strategies as well as random network nodes selection algorithms.Comment: submitted to IEEE Transactions on Multimedia, January 18th 201

Distributed Rate Allocation in Inter-Session Network Coding

In this work, we propose a distributed rate allocation algorithm that minimizes the average decoding delay for multimedia clients in inter-session network coding systems. We consider a scenario where the users are organized in a mesh network and each user requests the content of one of the available sources. We propose a novel distributed algorithm where network users determine the coding operations and the packet rates to be requested from the parent nodes, such that the decoding delay is minimized for all clients. A rate allocation problem is solved by every user, which seeks the rates that minimize the average decoding delay for its children and for itself. Since this optimization problem is a priori non-convex, we introduce the concept of equivalent packet flows, which permits to estimate the expected number of packets that every user needs to collect for decoding. We then decompose our original rate allocation problem into a set of convex subproblems, which are eventually combined to obtain an effective approximate solution to the delay minimization problem. The results demonstrate that the proposed scheme eliminates the bottlenecks and reduces the decoding delay experienced by users with limited bandwidth resources. We validate the performance of our distributed rate allocation algorithm in different video streaming scenarios using the NS-3 network simulator. We show that our system is able to take benefit of inter-session network coding for simultaneous delivery of video sessions in networks with path diversity

Performance Analysis of Vehicular Optical Camera Communications: Roadmap to uRLLC

In this paper, we analyze the performance of vehicular optical camera communication (OCC) towards ultra-reliable and low latency communications (uRLLC). The employed vehicular OCC model uses light-emitting diodes (LED) as transmitter and camera as receiver. In particular, we investigate the performance of the proposed system in terms of bit error rate (BER), spectral efficiency, and transmission latency at different inter-vehicular distances and angle of incidences (AoI). Further, we investigate the use of adaptive modulation to improve the spectral efficiency. From our analysis, we note that by satisfying a given target BER, higher spectral efficiency and lower latency can be achieved through adjusting the AoI towards the smaller degrees and switching into the suitable modulation order. Finally, we verify the results through simulations, which show that OCC can ensure ultra-low latency as well as satisfy the reliability requirements in automotive vehicles

Randomized Network Coding for UEP Video Delivery in Overlay Networks

This paper presents a receiver-driven video delivery algorithm that exploits a novel Randomized Network Coding (RNC) scheme for unequal error protection (UEP). The main idea of our approach is to account for the unequal importance of media packets in the network coding algorithm for efficient stream delivery in lossy overlay networks. Based on the requests from their neighbours, the network nodes properly combine packets and forward them to their children nodes. The network coding operations at every node are formulated as a log-concave optimization problem, which is solved with a greedy algorithm in only a few iterations. Our experimental results demonstrate that the proposed scheme permits to respect the priorities between the different packet classes. It further outperforms baseline network coding techniques for video streaming in overlay networks. Index Terms — Network coding, rate allocation, unequal error protection, overlay networks 1