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Transmitting Important Bits and Sailing High Radio Waves: A Decentralized Cross-Layer Approach to Cooperative Video Transmission
- IEEE J. on Selected Areas in Commun
, 2012
"... Abstract We investigate the impact of cooperative relaying on uplink and downlink multi-user (MU) wireless video transmissions. The objective is to maximize the long-term sum of utilities across the video terminals in a decentralized fashion, by jointly optimizing the packet scheduling, the resourc ..."
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Abstract We investigate the impact of cooperative relaying on uplink and downlink multi-user (MU) wireless video transmissions. The objective is to maximize the long-term sum of utilities across the video terminals in a decentralized fashion, by jointly optimizing the packet scheduling, the resource allocation, and the cooperation decisions, under the assumption that some nodes are willing to act as cooperative relays. A pricing-based distributed resource allocation framework is adopted, where the price reflects the expected future congestion in the network. Specifically, we formulate the wireless video transmission problem as an MU Markov decision process (MDP) that explicitly considers the cooperation at the physical layer and the medium access control sublayer, the video users' heterogeneous traffic characteristics, the dynamically varying network conditions, and the coupling among the users' transmission strategies across time due to the shared wireless resource. Although MDPs notoriously suffer from the curse of dimensionality, our study shows that, with appropriate simplications and approximations, the complexity of the MU-MDP can be significantly mitigated. Our simulation results demonstrate that integrating cooperative decisions into the MU-MDP optimization can increase the resource price in networks that only support low transmission rates and can decrease the price in networks that support high transmission rates. Additionally, our results show that cooperation allows users with feeble direct signals to achieve improvements in video quality on the order of 5 − 10 dB peak signal-to-noise ratio (PSNR), with less than 0.8 dB quality loss by users with strong direct signals, and with a moderate increase in total network energy consumption that is significantly less than the energy that a distant node would require to achieve an equivalent PSNR without exploiting cooperative diversity. Index Terms Cooperative communications, cross-layer optimization, decode-and-forward relaying, Markov decision process (MDP), multi-user scheduling, resource allocation, wireless video transmission.
IEEE TRANSACTIONS ON COMMUNICATIONS, ACCEPTED FOR PUBLICATION 1 Multicast Throughput Order of Network Coding in Wireless Ad-hoc Networks
"... Abstract—We consider a network with n nodes distributed uniformly in a unit square. We show that, under the protocol model, when ns = Ω ( log(n) 1+α) out of the n nodes, each act as source of independent information for a multicast group consisting of m randomly chosen destinations, the per-session ..."
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Abstract—We consider a network with n nodes distributed uniformly in a unit square. We show that, under the protocol model, when ns = Ω ( log(n) 1+α) out of the n nodes, each act as source of independent information for a multicast group consisting of m randomly chosen destinations, the per-session capacity in the ( presence) of network coding (NC) has a tight n bound of Θ √ when m = O( ns mlog(n)
Sanjay ShakkottaiMean-Variability-Fairness Tradeoffs in Resource Allocation with Applications to Video Delivery
"... August 2013This thesis is dedicated to my parents. Acknowledgments I thank God for all the blessings gifted to me and, in particular, for all the opportunities to pursue education. I am especially grateful for my family, the most important blessing of all. I am greatly indebted to my parents, brothe ..."
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August 2013This thesis is dedicated to my parents. Acknowledgments I thank God for all the blessings gifted to me and, in particular, for all the opportunities to pursue education. I am especially grateful for my family, the most important blessing of all. I am greatly indebted to my parents, brother, grandparents and the rest of my family for their love, sacrifice and constant support. I am fortunate to have had an exceptional researcher/teacher/mentor like Prof. Gustavo de Veciana as my PhD advisor. I firstly thank him for the generous amount of time and effort that he has spent over the past four years on numerous discussions and documentation related to this thesis. These discussions, filled with valuable insightful comments from my advisor, form the core of this thesis. I am especially grateful for his tremendous patience during the numerous times we got stuck in our work, and for all the flexibility provided in steering the direction of my research. The patience and flexibility played a vital role in turning my PhD work into one of the most enjoyable and intellectually satisfying endeavors of my life. I thank Dr. Ari Arapostathis for all the helpful discussions and ideas that
1Optimal Foresighted Multi-User Wireless Video
"... Recent years have seen an explosion in wireless video communication systems. Optimization in such systems is crucial – but most existing methods intended to optimize the performance of multi-user wireless video transmission are inefficient. Some works (e.g. Network Utility Maximization (NUM)) are my ..."
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Recent years have seen an explosion in wireless video communication systems. Optimization in such systems is crucial – but most existing methods intended to optimize the performance of multi-user wireless video transmission are inefficient. Some works (e.g. Network Utility Maximization (NUM)) are myopic: they choose actions to maximize instantaneous video quality while ignoring the future impact of these actions. Such myopic solutions are known to be inferior to foresighted solutions that optimize the long-term video quality. Alternatively, foresighted solutions such as rate-distortion optimized packet scheduling focus on single-user wireless video transmission, while ignoring the resource allocation among the users. In this paper, we propose an optimal solution for performing joint foresighted resource allocation and packet scheduling among multiple users transmitting video over a shared wireless network. A key challenge in developing foresighted solutions for multiple video users is that the users ’ decisions are coupled. To decouple the users ’ decisions, we adopt a novel dual decomposition approach, which differs from the conventional optimization solutions such as NUM, and determines foresighted policies. Specifically, we propose an informationally-decentralized algorithm in which the network manager updates resource “prices ” (i.e. the dual variables associated with the resource constraints), and the users make individual video packet scheduling decisions based on these prices. Because a priori knowledge of the system dynamics is almost never available at run-time, the proposed solution can learn online, concurrently with performing the foresighted optimization. Simulation results show 7 dB and 3 dB improvements in Peak Signal-to-Noise Ratio (PSNR) over myopic solutions and existing foresighted solutions, respectively. Keywords Wireless video, multi-user wireless communication, resource allocation, video packet scheduling,
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"... Abstract — Multicasting video over wireless networks is a best effort service. To multicast a video, Scalable Video Coding with spatial, temporal and quality scalabilities is adopted. Scalable Video multicast system consists of channel probing stage and transmission stage. The optimal resource alloc ..."
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Abstract — Multicasting video over wireless networks is a best effort service. To multicast a video, Scalable Video Coding with spatial, temporal and quality scalabilities is adopted. Scalable Video multicast system consists of channel probing stage and transmission stage. The optimal resource allocation problem is formulated by maximizing the video quality of the clients subject to transmission energy and channel access constraints. This problem is a joint optimization of the selection of Modulation and Coding Scheme (MCS), and the transmission power allocation. The proposed scheme is of linear complexity and leads to the maximized video quality for the admitted clients. It also satisfies the energy budget and access time constraints.
