Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/11814
Authors: Kartheek, M.
Issue Date: 2007
Abstract: There is a rapid expansion in the demand for all types of services, ranging from voice to high rate data and multimedia applications over wireless channels. However, the time- dispersive and frequency-selective nature of the wireless channel limits the effectiveness of wireless communications. Orthogonal Frequency Division Multiplexing (OFDM) has been considered as a very promising solution because of its robustness against frequency-selective fading and its capability to support high-data-rate transmission in broadband wireless communication systems. OFDM can be used both as a modulation scheme and as a part of the multiple access technique.- In OFDMA, also referred to as multi-user OFDM, multiple users share the same channel and the transmit power. Adaptive resource allocation deals with the allocation of sub-carrier, bits per sub-carrier and power of the sub-carrier. In this dissertation, adaptive resource allocation has been studied for multi-user OFDM. In a multi-user OFDM system, for a specific sub-carrier, if a user experiences deep fading, the others users may not be in deep fading. We can choose the user in a good channel condition to transmit data on that sub-carrier and this eventually results in multi-user diversity effects. If the transmit power for each user and for each sub-carrier is appropriately adapted to the channel conditions, multi-user diversity can be exploited. In this work, we have studied the rate adaptive schemes for adaptive resource allocation for following: 1. Maximization of the total data rate under total power constraint 2. Maximization of the minimum user data rate under total power constraint 3. Maximization of the total data rate under minimum user data rate, total transmitted power and BER constraints. The performance of the schemes has been evaluated through simulation and by solving for the optimal and sub-optimal cases using integer programming. In integer programming, complexity increases exponentially with the number of users and number of sub-carriers. The sub-optimum solution yields results close to those of the optimal case.
Other Identifiers: M.Tech
Research Supervisor/ Guide: Chakravorty, S.
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' THESES (E & C)

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