Algorithmic Aspects of Energy-Delay Tradeoff in Multihop Cooperative Wireless Networks

We consider the problem of energy-efficient transmission in delay constrained cooperative multihop wireless networks. The combinatorial nature of cooperative multihop schemes makes it difficult to design efficient polynomial-time algorithms for deciding which nodes should take part in cooperation, and when and with what power they should transmit. In this work, we tackle this problem in memoryless networks with or without delay constraints, i.e., quality of service guarantee. We analyze a wide class of setups, including unicast, multicast, and broadcast, and two main cooperative approaches, namely: energy accumulation (EA) and mutual information accumulation (MIA). We provide a generalized algorithmic formulation of the problem that encompasses all those cases. We investigate the similarities and differences of EA and MIA in our generalized formulation. We prove that the broadcast and multicast problems are, in general, not only NP hard but also o(log(n)) inapproximable. We break these problems into three parts: ordering, scheduling and power control, and propose a novel algorithm that, given an ordering, can optimally solve the joint power allocation and scheduling problems simultaneously in polynomial time. We further show empirically that this algorithm used in conjunction with an ordering derived heuristically using the Dijkstra's shortest path algorithm yields near-optimal performance in typical settings. For the unicast case, we prove that although the problem remains NP hard with MIA, it can be solved optimally and in polynomial time when EA is used. We further use our algorithm to study numerically the trade-off between delay and power-efficiency in cooperative broadcast and compare the performance of EA vs MIA as well as the performance of our cooperative algorithm with a smart noncooperative algorithm in a broadcast setting.Comment: 12 pages, 9 figure

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

Enhanced Rateless Coding and Compressive Sensing for Efficient Data/multimedia Transmission and Storage in Ad-hoc and Sensor Networks

In this dissertation, we investigate the theory and applications of the novel class of FEC codes called rateless or fountain codes in video transmission and wireless sensor networks (WSN). First, we investigate the rateless codes in intermediate region where the number of received encoded symbols is less that minimum required for full datablock decoding. We devise techniques to improve the input symbol recovery rate when the erasure rate is unknown, and also for the case where an estimate of the channel erasure rate is available. Further, we design unequal error protection (UEP) rateless codes for distributed data collection of data blocks of unequal lengths, where two encoders send their rateless coded output symbols to a destination through a common relay. We design such distributed rateless codes, and jointly optimize rateless coding parameters at each nodes and relaying parameters. Moreover, we investigate the performance of rateless codes with finite block length in the presence of feedback channel. We propose a smart feedback generation technique that greatly improves the performance of rateless codes when data block is finite. Moreover, we investigate the applications of UEP-rateless codes in video transmission systems. Next, we study the optimal cross-layer design of a video transmission system with rateless coding at application layer and fixed-rate coding (RCPC coding) at physical layer. Finally, we review the emerging compressive sensing (CS) techniques that have close connections to FEC coding theory, and designed an efficient data storage algorithm for WSNs employing CS referred to by CStorage. First, we propose to employ probabilistic broadcasting (PB) to form one CS measurement at each node and design CStorage- P. Later, we can query any arbitrary small subset of nodes and recover all sensors reading. Next, we design a novel parameterless and more efficient data dissemination algorithm that uses two-hop neighbor information referred to alternating branches (AB).We replace PB with AB and design CStorage-B, which results in a lower number of transmissions compared to CStorage-P.Electrical Engineerin