Browsing by Subject "Capacity"
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Item Bureaucratic access points and leverage(2013-08) Sternemann, Daniel Thomas; Jones, Bryan D.This project studies how bureaucratic behavior influences policy implementation. It presents a novel bureaucratic access points and leverage theory, which help us understand how policies are successfully implemented in the midst of bureaucratic challenges resulting from organizational roles and responsibilities and contrasting assessments. The concept of access points has traditionally involved lobbyists and interest groups accessing elected officials and their staffs. I ask what is the effect of bureaucrats accessing bureaucrats directly in the policy implementation process and its subsequent evaluation. I argue that bureaucrats leverage other bureaucrats during policy implementation proceedings, which adds the notion of power to access points theory. The focus of this investigation is the relationship between humanitarian assistance and disaster relief (HA/DR) agencies and associated Department of Defense (DOD) components, particularly DOD medical components providing wellness intervention. Bureaucratic access and leverage enables a more unified implementation of over-arching HA/DR policy by disparate agencies with unique missions, resources, capabilities, and assessment measures. The existing literature does not fully capture how such agency differences are mitigated and overcome in implementing policy that spans multiple entities. Bureaucratic access points and leverage theory offers bureaucrats the analytical capability to know who is controlling policy implementation. It also presents a tool they can use to maintain and increase their own influence and power within a policy domain.Item Capacity of interference networks : achievable regions and outer bounds(2010-05) Sridharan, Sriram; Vishwanath, SriramIn an interference network, multiple transmitters communicate with multiple receivers using the same communication channel. The capacity region of an interference network is defined as the set of data rates that can be simultaneously achieved by the users of the network. One of the most important example of an interference network is the wireless network, where the communication channel is the wireless channel. Wireless interference networks are known to be interference limited rather than noise limited since the interference power level at the receivers (caused by other user's transmissions) is much higher than the noise power level. Most wireless communication systems deployed today employ transmission strategies where the interfering signals are treated in the same manner as thermal noise. Such strategies are known to be suboptimal (in terms of achieving higher data rates), because the interfering signals generated by other transmitters have a structure to them that is very different from that of random thermal noise. Hence, there is a need to design transmission strategies that exploit this structure of the interfering signals to achieve higher data rates. However, determining optimal strategies for mitigating interference has been a long standing open problem. In fact, even for the simplest interference network with just two users, the capacity region is unknown. In this dissertation, we will investigate the capacity region of several models of interference channels. We will derive limits on achievable data rates and design effective transmission strategies that come close to achieving the limits. We will investigate two kinds of networks - "small" (usually characterized by two transmitters and two receivers) and "large" where the number of users is large.Item Cognitive radios : fundamental limits and applications to cellular and wireless local networks(2012-05) Chung, Goochul; Vishwanath, Sriram; Shakkottai, Sanjay; Andrews, Jeffrey; Caramanis, Constantine; Choi, JihwanAn ever increasing number of wirelessly-enabled applications places a very high demand on stringent spectral resources. Cognitive radios have the potential of enhancing spectral efficiency by improving the usage of channels that are already licensed for a specific purpose. Research on cognitive radios involves answering questions such as: how can a cognitive radio transmit at a high data rate while maintaining the same quality of service for the licensed user? There are multiple forms of cognition studied in literature, and each of these models must be studied in detail to understand its impact on the overall system performance. Specifically, the information-theoretic capacity of such systems is of great interest. Also, the design of cognitive radio is necessary to achieve those capacities in real applications. In this dissertation, we formulate different problems that relate to the performance of such systems and methods to increase their efficiency. This dissertation discusses, firstly, the means of "sensing" in cognitive systems, secondly, the optimal resource allocation algorithms for interweave cognitive radio, and finally, the fundamental limits of partially and overly cognitive overlay systems.Item Optimal finite alphabet sources over partial response channels(Texas A&M University, 2004-11-15) Kumar, DeepakWe present a serially concatenated coding scheme for partial response channels. The encoder consists of an outer irregular LDPC code and an inner matched spectrum trellis code. These codes are shown to offer considerable improvement over the i.i.d. capacity (> 1 dB) of the channel for low rates (approximately 0.1 bits per channel use). We also present a qualitative argument on the optimality of these codes for low rates. We also formulate a performance index for such codes to predict their performance for low rates. The results have been verified via simulations for the (1-D)/sqrt(2) and the (1-D+0.8D^2)/sqrt(2.64) channels. The structure of the encoding/decoding scheme is considerably simpler than the existing scheme to maximize the information rate of encoders over partial response channels.Item Source and channel aware resource allocation for wireless networks(2011-08) Jose, Jubin; Vishwanath, Sriram; Andrews, Jeffrey G.; Shakkottai, Sanjay; de Veciana, Gustavo; Morton, DavidWireless networks promise ubiquitous communication, and thus facilitate an array of applications that positively impact human life. At a fundamental level, these networks deal with compression and transmission of sources over channels. Thus, accomplishing this task efficiently is the primary challenge shared by these applications. In practice, sources include data and video while channels include interference and relay networks. Hence, effective source and channel aware resource allocation for these scenarios would result in a comprehensive solution applicable to real-world networks. This dissertation studies the problem of source and channel aware resource allocation in certain scenarios. A framework for network resource allocation that stems from rate-distortion theory is presented. Then, an optimal decomposition into an application-layer compression control, a transport-layer congestion control and a network-layer scheduling is obtained. After deducing insights into compression and congestion control, the scheduling problem is explored in two cross-layer scenarios. First, appropriate queue architecture for cooperative relay networks is presented, and throughput-optimality of network algorithms that do not assume channel-fading and input-queue distributions are established. Second, decentralized algorithms that perform rate allocation, which achieve the same overall throughput region as optimal centralized algorithms, are derived. In network optimization, an underlying throughput region is assumed. Hence, improving this throughput region is the next logical step. This dissertation addresses this problem in the context of three significant classes of interference networks. First, degraded networks that capture highly correlated channels are explored, and the exact sum capacity of these networks is established. Next, multiple antenna networks in the presence of channel uncertainty are considered. For these networks, robust optimization problems that result from linear precoding are investigated, and efficient iterative algorithms are derived. Last, multi-cell time-division-duplex systems are studied in the context of corrupted channel estimates, and an efficient linear precoding to manage interference is developed.Item Valuation of an advanced combined cycle power plant and its cost of new entry (CONE) into the ERCOT market(2014-08) Zaborowski, Jeremy Ronald; Webber, Michael E., 1971-The Texas ERCOT market is one of the most open, deregulated electricity markets in the world. This open market brought electricity costs down for Texas residents and businesses, creating a much more competitive economic climate. However, these low prices currently generate insufficient revenue for generators to finance construction of new or replacement generation assets. In the instance of combined cycle advanced natural gas, the Independent Market Monitor 2012 annual report estimated that a plant needed to generate 2.5 times as much as revenue it did in 2012 to incent new generation. This author argues that while the gap is still significant, the continuous changes to the ERCOT market since its inception make an historical examination like that used by the IMM less accurate. New market rules such as price caps or changes in fuel markets through new technologies like hydraulic fracturing create a very different valuation gap than a model based on historical activity alone. This analysis attempts to get a more accurate approximation of the gap through the use of publicly traded futures contracts for natural gas and electricity. Electricity futures reflect market expectations of revenue based on current and future market rules. Gas futures reflect price expectations in light of market changes like fracturing, potential LNG exports, and other changes. Financial positions can be maintained in both markets to give a fixed rate of return. Using this method, one can create a very conservative valuation model that still more accurately reflects market sentiment. This thesis starts with a brief history of ERCOT deregulation from the early 2000s to present in order to clarify for the reader the changes that have taken place in the market. It then demonstrates the futures-valuation model using an advanced combined cycle power plant as an example.