Broadcast system source codes: a new paradigm for data compression

Broadcast systems play a central role in an enormous variety of network technologies in which one system node must simultaneously send either the same or different information to multiple nodes in the network. Systems incorporating broadcast components include such diverse technologies as wireless communications systems, web servers, distributed computing devices, and video conferencing systems. Currently, the compression algorithms (or source codes) employed in these devices fail to take advantage of the characteristics specific to broadcast systems. Instead, they treat a single node transmitting information to a collection of receivers as a collection of single-transmitter single-receiver communications problems and employ an independent source code on each. This approach is convenient, since it allows direct application of traditional compression techniques in a wide variety of broadcast system applications. Nonetheless, we here argue that the approach is inherently flawed. Our innovation in this paper is to treat the general broadcast system (with an arbitrary number of receivers and both specific and common information) as an inseparable whole and consider the resulting source coding ramifications. The result is a new paradigm for data compression on general broadcast systems. In this work, we describe this broadcast system source coding paradigm and examine the potential gains achievable by moving away from more conventional methods

Throughput-Optimal Multihop Broadcast on Directed Acyclic Wireless Networks

We study the problem of efficiently broadcasting packets in multi-hop wireless networks. At each time slot the network controller activates a set of non-interfering links and forwards selected copies of packets on each activated link. A packet is considered jointly received only when all nodes in the network have obtained a copy of it. The maximum rate of jointly received packets is referred to as the broadcast capacity of the network. Existing policies achieve the broadcast capacity by balancing traffic over a set of spanning trees, which are difficult to maintain in a large and time-varying wireless network. We propose a new dynamic algorithm that achieves the broadcast capacity when the underlying network topology is a directed acyclic graph (DAG). This algorithm is decentralized, utilizes local queue-length information only and does not require the use of global topological structures such as spanning trees. The principal technical challenge inherent in the problem is the absence of work-conservation principle due to the duplication of packets, which renders traditional queuing modelling inapplicable. We overcome this difficulty by studying relative packet deficits and imposing in-order delivery constraints to every node in the network. Although in-order packet delivery, in general, leads to degraded throughput in graphs with cycles, we show that it is throughput optimal in DAGs and can be exploited to simplify the design and analysis of optimal algorithms. Our characterization leads to a polynomial time algorithm for computing the broadcast capacity of any wireless DAG under the primary interference constraints. Additionally, we propose an extension of our algorithm which can be effectively used for broadcasting in any network with arbitrary topology

The Linear Information Coupling Problems

Many network information theory problems face the similar difficulty of single-letterization. We argue that this is due to the lack of a geometric structure on the space of probability distribution. In this paper, we develop such a structure by assuming that the distributions of interest are close to each other. Under this assumption, the K-L divergence is reduced to the squared Euclidean metric in an Euclidean space. In addition, we construct the notion of coordinate and inner product, which will facilitate solving communication problems. We will present the application of this approach to the point-to-point channel, general broadcast channel, and the multiple access channel (MAC) with the common source. It can be shown that with this approach, information theory problems, such as the single-letterization, can be reduced to some linear algebra problems. Moreover, we show that for the general broadcast channel, transmitting the common message to receivers can be formulated as the trade-off between linear systems. We also provide an example to visualize this trade-off in a geometric way. Finally, for the MAC with the common source, we observe a coherent combining gain due to the cooperation between transmitters, and this gain can be quantified by applying our technique.Comment: 27 pages, submitted to IEEE Transactions on Information Theor