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DESCRIPTION:Speaker: Rahul Urgaonkar, USC PhD Candidate
Talk Title: PhD Defense - Optimal Resource Allocation and Cross-Layer Control in Cognitive and Cooperative Wireless Networks
Abstract: Next generation wireless networks will be required to provide significantly higher data rates, reliability, and energy efficiency than the existing systems. Cognitive radio and cooperative communication are expected to be two essential technologies towards achieving this goal. In this thesis, we study several resource allocation problems in the area of cognitive and cooperative wireless networks. Our goal is to design optimal control algorithms that maximize time-average network utilities (such as throughput) subject to time-average constraints (such as power, reliability, etc.). This talk will present our work on two such problems. \n
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The first problem considers opportunistic cooperation in cognitive radio networks. Specifically, we assume that a secondary user can use its resources to improve the transmission rates of the primary user. In return, the secondary user can get more opportunities for transmitting its own data when the primary user is idle. In this scenario, it is important for the secondary user to balance the desire to cooperate more (to create more transmission opportunities) with the need for maintaining sufficient energy levels for its own transmissions. Such a model is applicable in the emerging area of cognitive femtocell networks. We formulate the problem of maximizing the secondary user throughput subject to a time average power constraint under these settings as a constrained Markov Decision Problem. Conventional solution techniques to this problem are based on dynamic programming and require either extensive knowledge of the system dynamics or learning based approaches that suffer from large convergence times. However, using the technique of Lyapunov optimization, we design a novel greedy and online control algorithm that does not require any knowledge of network dynamics or explicit learning, yet is optimal. \n
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The second problem investigates optimal routing and scheduling strategies for multi-hop wireless networks with rateless codes. Rateless codes allow each node of the network to accumulate mutual information with every packet transmission. This enables a significant performance gain over conventional shortest path routing. Further, it also outperforms cooperative communication techniques that are based on energy accumulation. However, it requires complex and combinatorial networking decisions concerning which nodes participate in transmission, and which decode ordering to use. We formulate the general problem as a combinatorial optimization problem and then make use of several structural properties to simplify the solution and derive optimal greedy algorithms. A key feature of these algorithms is that unlike prior works on these problems, they do not require solving any linear programs to compute the optimal solution.
Biography: Rahul Urgaonkar obtained the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology (IIT) Bombay in 2002 and the M.S. degree in Electrical Engineering from the University of Southern California, Los Angeles in 2005. He is currently a PhD candidate in Electrical Engineering at USC working with Prof. Michael Neely. His research interest is in the area of stochastic network optimization with applications to resource allocation and scheduling problems in next generation wireless networks and data centers.
Host: Prof. Michael J. Neely
SEQUENCE:5
DTSTART:20110223T103000
LOCATION:EEB 539
DTSTAMP:20110223T103000
SUMMARY:PhD Defense - Optimal Resource Allocation and Cross-Layer Control in Cognitive and Cooperative Wireless Networks
UID:EC9439B1-FF65-11D6-9973-003065F99D04
DTEND:20110223T113000
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