Coexistence of directional and non-directional technologies in 6G wireless dense networks
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Dense networks are characterized by the prevalence of wireless access points (APs) in close proximity to a population of user devices on a similar scale. By increasing AP density, the aggregate data consumption of a system can be dramatically increased. In this dissertation we consider dense deployment of directional visible light APs. Firstly, we analyze the performance of a visible light communication (VLC) link and propose algorithmic methods as well as novel receiver structures to enhance its quality. Secondly, we study handover algorithms and investigate an AP placement strategy that ties to the system outage probability. Thirdly, we use a geometric model for an indoor space and a reference optical channel model to formulate an optimization problem that proposes a dynamic field of view (FOV) receiver with a goal of optimizing receiver FOV for maximum signal to noise ratio (SNR). From the promising results we get, we then propose the dynamic FOV technique with receiver tracking capability. Its results show an average SNR increase of up to 40% when compared to a fixed FOV receiver. These results motivate the adoption of dynamic pointing and adaptive FOV at the receiver in order to realize improved performance for mobile devices in an optical wireless dense network. This opts us to study interference in VLC systems and how to mitigate it using our proposed receivers. In the context of multi-user networks, we formulate two main novel optimization problems i) a joint optimization of transmit emission pattern and transmit power while satisfying illumination requirements and ii) an optimization to allocate users, balance the network load and optimize device FOV for best performance. We then evaluate the effect of self-blockage as well as random human blockers on our proposed receivers. Finally, we propose to deploy the VLC system in a hybrid setting of other technologies to evaluate the overall system performance for future 6G networks.
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