Date of Award
Doctor of Philosophy
Electrical and Computer Engineering
Recently, massive multiple-input multiple-output (MIMO) systems have gained significant attention as a new network architecture to not only achieving unprecedented spectral and energy efficiencies, but also to alleviating propagation losses and inter-user/inter-cell interference. Therefore, massive MIMO has been identified as one of the key candidate technologies for the 5th generation wireless standard. This dissertation thus focuses on (1) developing a performance analysis framework for cognitive massive MIMO systems by investigating the uplink transmissions of multi-cell multi-user massive MIMO secondary systems, which are underlaid in multi-cell multi-user primary massive MIMO systems, with taking into consideration the detrimental effects of practical transmission impairments, (2) proposing a new wireless-powered underlay cognitive massive MIMO system model, as the secondary user nodes is empowered by the ability to efficiently harvest energy from the primary user transmissions, and then access and utilize the primary network spectrum for information transmission, and (3) developing a secure communication strategy for cognitive multi-user massive MIMO systems, where physical layer secure transmissions are provisioned for both primary and secondary systems by exploiting linear precoders and artificial noise (AN) generation in order to degrade the signal decodability at eavesdropper. The key design feature of the proposed cognitive systems is to leverage the spatial multiplexing strategies to serve a large number of spatially distributed user nodes by using very large numbers of antennas at the base-stations. Moreover, the fundamental performance metrics, the secondary transmit power constraints, which constitute the underlay secondary transmissions subject to a predefined primary interference temperature, and the achievable sum rates of the primary and secondary systems, are characterized under different antenna array configurations. Additionally, the detrimental impact of practical wireless transmission impairments on the performance of the aforementioned systems are quantified. The important insights obtained throughout these analyses can be used as benchmarks for designing practical cognitive spectrum sharing networks.
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