Short-packet Transmission via Variable-Length Codes in the Presence of Noisy Stop Feedback

We present an upper bound on the error probability achievable using variable-length stop feedback codes, for a fixed size of the information payload and a given constraint on the maximum latency and the average service time. Differently from the bound proposed in Polyanskiy et al. (2011), which pertains to the scenario in which the stop signal is sent over a noiseless feedback channel, our bound applies to the practically relevant setup in which the feedback link is noisy. By numerically evaluating our bound, we illustrate that, for fixed latency and reliability constraints, noise in the feedback link can cause a significant increase in the minimum average service time, to the extent that fixed-length codes without feedback may be preferable in some scenarios.Comment: Submitted to a Transactions on Wireless Communication

PERFORMANCE LIMITS FOR ENERGY-CONSTRAINED COMMUNICATION SYSTEMS

Ph.DDOCTOR OF PHILOSOPH

On the role of feedback in network coding

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 143-149).Network coding has emerged as a new approach to operating communication networks, with a promise of improved efficiency in the form of higher throughput, especially in lossy conditions. In order to realize this promise in practice, the interfacing of network coding with existing network protocols must be understood well. Most current protocols make use of feedback in the form of acknowledgments (ACKs) for reliability, rate control and/or delay control. In this work, we propose a way to incorporate network coding within such a feedback-based framework, and study the various benefits of using feedback in a network coded system. More specifically, we propose a mechanism that provides a clean interface between network coding and TCP with only minor changes to the protocol stack, thereby allowing incremental deployment. In our scheme, the source transmits random linear combinations of packets currently in the TCP congestion window. At the heart of our scheme is a new interpretation of ACKs - the receiver acknowledges every degree of freedom (i.e., a linear combination that reveals one unit of new information) even if it does not reveal an original packet immediately. Such ACKs enable a TCP-compatible sliding-window implementation of network coding. Thus, with feedback, network coding can be performed in a completely online manner, without the need for batches or generations. Our scheme has the nice feature that packet losses on the link can be essentially masked from the congestion control algorithm by adding enough redundancy in the encoding process.(cont.) This results in a novel and effective approach for congestion control over networks involving lossy links such as wireless links. Our scheme also allows intermediate nodes to perform re-encoding of the data packets. This in turn leads to a natural way of running TCP flows over networks that use multipath opportunistic routing along with network coding. We use the new type of ACKs to develop queue management algorithms for coded networks, which allow the queue size at nodes to track the true backlog in information with respect to the destination. We also propose feedback-based adaptive coding techniques that are aimed at reducing the decoding delay at the receivers. Different notions of decoding delay are considered, including an order-sensitive notion which assumes that packets are useful only when delivered in order. We study the asymptotic behavior of the expected queue size and delay, in the limit of heavy traffic.by Jay Kumar Sundararajan.Ph.D

Delay-sensitive Communications Code-Rates, Strategies, and Distributed Control

An ever increasing demand for instant and reliable information on modern communication networks forces codewords to operate in a non-asymptotic regime. To achieve reliability for imperfect channels in this regime, codewords need to be retransmitted from receiver to the transmit buffer, aided by a fast feedback mechanism. Large occupancy of this buffer results in longer communication delays. Therefore, codewords need to be designed carefully to reduce transmit queue-length and thus the delay experienced in this buffer. We first study the consequences of physical layer decisions on the transmit buffer occupancy. We develop an analytical framework to relate physical layer channel to the transmit buffer occupancy. We compute the optimal code-rate for finite-length codewords operating over a correlated channel, under certain communication service guarantees. We show that channel memory has a significant impact on this optimal code-rate. Next, we study the delay in small ad-hoc networks. In particular, we find out what rates can be supported on a small network, when each flow has a certain end-to-end service guarantee. To this end, service guarantee at each intermediate link is characterized. These results are applied to study the potential benefits of setting up a network suitable for network coding in multicast. In particular, we quantify the gains of network coding over classic routing for service provisioned multicast communication over butterfly networks. In the wireless setting, we study the trade-off between communications gains achieved by network coding and the cost to set-up a network enabling network coding. In particular, we show existence of scenarios where one should not attempt to create a network suitable for coding. Insights obtained from these studies are applied to design a distributed rate control algorithm in a large network. This algorithm maximizes sum-utility of all flows, while satisfying per-flow end-to-end service guarantees. We introduce a notion of effective-capacity per communication link that captures the service requirements of flows sharing this link. Each link maintains a price and effective-capacity, and each flow maintains rate and dissatisfaction. Flows and links update their respective variables locally, and we show that their decisions drive the system to an optimal point. We implemented our algorithm on a network simulator and studied its convergence behavior on few networks of practical interest

Efficient operation of coded packet networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. [109]-122).A fundamental problem faced in the design of almost all packet networks is that of efficient operation -- of reliably communicating given messages among nodes at minimum cost in resource usage. We present a solution to the efficient operation problem for coded packet networks, i.e., packet networks where the contents of outgoing packets are arbitrary, causal functions of the contents of received packets. Such networks are in contrast to conventional, routed packet networks, where outgoing packets are restricted to being copies of received packets and where reliability is provided by the use of retransmissions. This thesis introduces four considerations to coded packet networks: 1. efficiency, 2. the lack of synchronization in packet networks, 3. the possibility of broadcast links, and 4. packet loss. We take these considerations and give a prescription for operation that is novel and general, yet simple, useful, and extensible. We separate the efficient operation problem into two smaller problems, which we call network coding -- the problem of deciding what coding operation each node should perform given the rates at which packets are injected on each link -- and subgraph selection -- the problem of deciding those rates.(cont.) Our main contribution for the network coding problem is to give a scheme that achieves the maximum rate of a multicast connection under the given injection rates. As a consequence, the separation of network coding and subgraph selection results in no loss of optimality provided that we are constrained to only coding packets within a single connection. Our main contribution for the subgraph selection problem is to give distributed algorithms that optimally solve the single-connection problem under certain assumptions. Since the scheme we propose for network coding can easily be implemented in a distributed manner, we obtain, by combining the solutions for each of the smaller problems, a distributed approach to the efficient operation problem. We assess the performance of our solution for three problems: minimum-transmission wireless unicast, minimum-weight wireline multicast, and minimum-energy wireless multicast. We find that our solution has the potential to offer significant efficiency improvements over existing techniques in routed packet networks, particularly for multi-hop wireless networks.by Desmond S. Lun.Ph.D

Applications of graph-based codes in networks: analysis of capacity and design of improved algorithms

The conception of turbo codes by Berrou et al. has created a renewed interest in modern graph-based codes. Several encouraging results that have come to light since then have fortified the role these codes shall play as potential solutions for present and future communication problems. This work focuses on both practical and theoretical aspects of graph-based codes. The thesis can be broadly categorized into three parts. The first part of the thesis focuses on the design of practical graph-based codes of short lengths. While both low-density parity-check codes and rateless codes have been shown to be asymptotically optimal under the message-passing (MP) decoder, the performance of short-length codes from these families under MP decoding is starkly sub-optimal. This work first addresses the structural characterization of stopping sets to understand this sub-optimality. Using this characterization, a novel improved decoder that offers several orders of magnitude improvement in bit-error rates is introduced. Next, a novel scheme for the design of a good rate-compatible family of punctured codes is proposed. The second part of the thesis aims at establishing these codes as a good tool to develop reliable, energy-efficient and low-latency data dissemination schemes in networks. The problems of broadcasting in wireless multihop networks and that of unicast in delay-tolerant networks are investigated. In both cases, rateless coding is seen to offer an elegant means of achieving the goals of the chosen communication protocols. It was noticed that the ratelessness and the randomness in encoding process make this scheme specifically suited to such network applications. The final part of the thesis investigates an application of a specific class of codes called network codes to finite-buffer wired networks. This part of the work aims at establishing a framework for the theoretical study and understanding of finite-buffer networks. The proposed Markov chain-based method extends existing results to develop an iterative Markov chain-based technique for general acyclic wired networks. The framework not only estimates the capacity of such networks, but also provides a means to monitor network traffic and packet drop rates on various links of the network.Ph.D.Committee Chair: Fekri, Faramarz; Committee Member: Li, Ye; Committee Member: McLaughlin, Steven; Committee Member: Sivakumar, Raghupathy; Committee Member: Tetali, Prasa

Proceedings of the 35th WIC Symposium on Information Theory in the Benelux and the 4th joint WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux, Eindhoven, the Netherlands May 12-13, 2014

Compressive sensing (CS) as an approach for data acquisition has recently received much attention. In CS, the signal recovery problem from the observed data requires the solution of a sparse vector from an underdetermined system of equations. The underlying sparse signal recovery problem is quite general with many applications and is the focus of this talk. The main emphasis will be on Bayesian approaches for sparse signal recovery. We will examine sparse priors such as the super-Gaussian and student-t priors and appropriate MAP estimation methods. In particular, re-weighted l2 and re-weighted l1 methods developed to solve the optimization problem will be discussed. The talk will also examine a hierarchical Bayesian framework and then study in detail an empirical Bayesian method, the Sparse Bayesian Learning (SBL) method. If time permits, we will also discuss Bayesian methods for sparse recovery problems with structure; Intra-vector correlation in the context of the block sparse model and inter-vector correlation in the context of the multiple measurement vector problem