published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Networks function properly only when nodes cooperate to provide service. In many networks, such as ad hoc and interdomain networks, network devices are deployed by different owners. Due to limited communication resources, nodes in such networks may behave selfishly. That is, they are only interested in maximizing their own utilities, leading to selfish networks. Incentives are required in such networks to stimulate cooperation. In wired selfish networks, existing work mainly focuses on traffic assignment among predetermined available paths for one source and destination pair. In wireless selfish networks, available bandwidth is assumed to be fixed and predetermined, and the interferences among flows are ignored. Resource allocation in selfish networks needs to be developed under more general models. This dissertation has devised general analytical models for bandwidth allocation in wired and wireless selfish networks. Based on the analogy between resource allocation in selfish networks and auction, auction theory has been adopted in the design and analysis of resource allocation schemes. With incentives introduced in the schemes, selfish nodes will follow the prescribed algorithm and report their information truthfully so that the system cost is minimized. I firstly propose a general model for bandwidth allocation in wired selfish networks. Bandwidth requirements of call routing requests in a given period are allocated as a batch and satisfied at the end of the period. Then, a centralized mechanism is designed to allocate bandwidth and determine payments with different sequencing strategies. Some properties of the mechanism such as individual rationality and incentive-compatibility are studied. I go on to develop the distributed algorithm in wired selfish networks. Available paths are no longer assumed to be fixed and predetermined. Destination nodes conduct the sub-auctions in a certain order for bandwidth allocation and determine payments in a distributed manner. Truthfulness of the distributed mechanism is guaranteed under Nash equilibrium. This distributed mechanism, as a more scalable solution to allocate bandwidth in wired selfish networks, can still guarantee the performance achieved by existing work. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

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Enabling "intelligent environments" that are effortlessly automated is a key promise of sensor networks of the future. These networks have a wide range of domains in which they can be effectively deployed, including health-care, emergency response, manufacturing and surveillance. Unlike the majority of existing (and perhaps better-understood) network configurations, wireless-implemented sensor networks suffer from extremely stringent constraints in terms of scalability and end-goal of deployment. Thus, it is imperative that we determine solutions that are tailored to the constraints and goals of these systems, by bringing together ideas in the domains of control, computing and communications to a common analytical platform. In this dissertation, we build a theoretical framework that uses system theory, stochastic control, queuing theory and information theory to determine the following: 1. A characterization of the stability and optimal control policies with sensor querying (i.e. which set of sensors must be queried and when) using system theory and stochastic control; 2. A delay-optimal energy efficient transmission scheme for these networks (i.e. with what power level must they communicate) using heavy traffic limits and stochastic control; and 3. A cooperative transmission strategy for maximizing capacity of these networks (i.e. how they should encode their data to send the most through) using network information theory.

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The shortage of radio spectrum has become the bottleneck of achieving broadband wire-less access. Overcoming this bottleneck in next-generation wireless networks hinges on successful implementation of multiple-input-multiple-output (MIMO) technologies, which use antenna arrays rather than additional bandwidth for multiplying data rates. The most efficient MIMO techniques require channel state information (CSI). In practice, such information is usually inaccurate due to overhead constraints on CSI acquisition as well as mobility and delay. CSI inaccuracy can potentially reduce the performance gains provided by MIMO. This dissertation investigates the impact of CSI inaccuracy on the performance of increasing complex MIMO networks, starting with a point-to-point link, continuing to a multiuser MIMO system, and ending at a mobile ad hoc network. Furthermore, this dissertation contributes algorithms for efficient CSI acquisition, and its integration with beamforming and scheduling in multiuser MIMO, and with interference cancelation in ad hoc networks. First, this dissertation presents a design of a finite-rate CSI feedback link for point-to-point beamforming over a temporally correlated channel. We address various important design issues omitted in prior work, including the feedback delay, protocol, bit rate, and compression in time. System parameters such as the feedback bit rate are derived as functions of channel coherence time based on Markov chain theory. In particular, the capacity gain due to beamforming is proved to decrease with feedback delay at least at an exponential rate, which depends on channel coherence time. This work provides an efficient way of implementing beamforming in practice for increasing transmission range and throughput. Second, several algorithms for multiuser MIMO systems are proposed, including CSI quantization, joint beamforming and scheduling, and distributed feedback scheduling. These algorithms enable spatial multiple access and multiuser diversity in a cellular system under the practical constraint of finite-rate multiuser CSI feedback. Moreover, this dissertation shows analytically that the throughput of the MIMO uplink and downlink using the proposed algorithms scales optimally as the number of users increases. Finally, the transmission capacity of a MIMO ad hoc network is analyzed for the case where spatial interference cancelation is applied at receivers. Most important, this dissertation shows that this MIMO technique contributes significant network capacity gains even if the required CSI is inaccurate. In addition, opportunistic CSI estimation is shown to provide a tradeoff between channel training overhead and CSI accuracy. / text

M. Tech. Electrical Engineering. / Wireless Sensor Networks (WSNs), which contribute to many applications in the military, environmental, medical, and civil domains, consist of small nodes with sensing, data computation, and wireless-communication capabilities. Node routing protocols have been specifically designed for WSNs in which energy conservation is an essential design issue. Rumor Routing (RR) is a hybrid protocol which combines both proactive and reactive routing methods, which balances event and query flooding quite well. This kind of protocol is well adapted to the case of few data and many queries. In this paper, Relative Coordinate Rumor Routing (RCRR), a straight-line routing method of both event and query, is proposed. It improves RR using some topological and abstract localisation method that shortens the source-to-sink route for the data transmission in order to save energy for broadcasting, even comparing to large data amount Routing Protocol. By adapting the Sensor-MAC protocol, the power consumption is much lower than that of the RR. Nodes can change to idle mode when notification of broadcasting does not apply to them. Simulation studies of RCRR with S-MAC can reduce energy by 60% compared to RR, which is a good improvement

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