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    Inband Full-duplex Wireless Communications for Dynamic Spectrum Sharing Systems

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    Author
    Afifi Ahmed, Wessam
    Issue Date
    2016
    Advisor
    Krunz, Marwan
    
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    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    Over the last decade, there has been an exponential growth in the wireless demand, driven by an increase in the number of devices, users, and applications. Combined with an increase in the number of connections (due to Internet of things or IoT) and the spike in mobile video, this growth led to a spectrum crisis. To face this problem, various solutions have been proposed, including more cell densification and higher spectrum efficiency. Industry and academia are gearing to develop new wireless technologies such as full-duplex (FD) communications and massive multiple-input and multiple-output (MIMO) to enhance network performance and improve user experience. To solve the aforementioned spectrum crisis, self-interference-suppression (SIS) techniques have been developed in the previous few years to enable inband FD communications (i.e., simultaneous transmission and reception over the same channel). Traditionally, bidirectional communications can be achieved by separating the forward and reverse links in time, frequency, or code. The challenge in achieving simultaneous transmission and reception over the same band is that the received power of the intended signal is much smaller than the power of the transmitted signal generated at the same node. While this node is receiving, its own transmission is considered as self-interference, which could overwhelm the receiver and prevent correct decoding. Inspired by the recent developments in FD communications, in this dissertation, we incorporate SIS techniques in the design of wireless systems, specifically targeting dynamic spectrum sharing systems. First, we consider an opportunistic spectrum access (OSA) network in which secondary users (SUs) are equipped with partial/complete SIS, enabling them to operate in either simultaneous transmit-and-sense (TS) mode or simultaneous transmit-and-receive (TR) mode. We analytically study the performance metrics for the two modes. From this analysis, we evaluate the sensing/throughput tradeoff. Motivated by the competing goals of primary user (PU) protection (in the TS mode) and SU performance (in the TR mode), we present an optimal adaptive switching strategy and an associated communication protocol for FD OSA systems. Specifically, we optimize the spectrum-awareness/efficiency tradeoff by allowing the SU link to adaptively switch between various modes, depending on the forecasted PU dynamics. In practice, SIS is imperfect, resulting in residual self-interference that degrades the sensing performance in the TS mode. Accordingly, we study different spectrum sensing techniques in the TS mode, while illustrating their accuracy-complexity tradeoffs. Second, we consider the coexistence problem of concurrent transmissions between multiple FD-enabled links with different SIS capabilities; each link can operate in either FD or half-duplex mode. We determine the optimal mode for each link while taking into account residual and mutual interferences. The interactions between links are studied via a Bayesian game for which the Bayesian Nash equilibrium is derived. Finally, we consider the coexistence between FD-enabled Wi-Fi systems and LTE-unlicensed small cells in the 5 GHz bands. We introduce MAC-layer procedures and propose an adaptation scheme for the clear channel assessment (CCA) threshold of the Wi-Fi system. Our objective is to maximize the spatial reuse while maintaining fairness between LTE-U and Wi-Fi systems. We evaluate the performance of various proposed schemes in this dissertation using numerical results, simulations, and hardware USRP experiments.
    Type
    text
    Electronic Dissertation
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Electrical & Computer Engineering
    Degree Grantor
    University of Arizona
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