Interweave Cognitive Radio for 4G Long Term Evolution and 5G New Radio Self-Reliant Networks

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Computer Science and Electrical Engineering


Engineering, Computer

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Existing cellular networks have untapped radio frequency resources, also known as white space, available for cognitive radio applications. A secondary network can opportunistically interweave communication within the white space of an existing cellular signal by leveraging cognitive radio. This thesis presents a novel methodology for forming a cognitive interwoven self-reliant secondary network with no additional physical infrastructure, collaboration from the existing primary network, or software or hardware changes in the primary network. The methodology is tested first with 4G and later with 5G cellular technological standards. For the physical layer, this thesis optimizes synchronization as the initial step in aligning to a cellular signal in time, frequency, and sector identity. We improve synchronization through sensitivity, execution time, and applies a threshold to form a "cell detector” instead of the traditional "cell search,” which only considers the most detectable signal. After synchronization, resource detectors monitor the available spectral resources of the entire cellular infrastructure. Modern cellular networks have grown in complexity and become an ecosystem that includes the host technologies, such as 4G Long Term Evolution (LTE) and 5G New Radio (NR), along with subsystems such as narrowband internet of things (NB-IoT), category M1 (Cat-M1/LTE-M), observed time difference of arrival (OTDOA), and support for 4G/5G coexistence using dynamic spectrum sharing (DSS). Such an increased complexity has driven the need for network monitoring to enable load tracking, congestion control, spectral efficiency analysis, intrusion detection, and cognitive radio communications. This thesis develops resource monitoring that can passively monitor the entire cellular ecosystem, including reservations configured with high-layer messages that are only accessible to in-network, active, and sometimes user-specific equipment. Resource monitoring provides white-space reservations for cognitive communications. We define interference control to prevent interference with the primary network through physical layer access schemes and power control cluster protocols to access resources safely. With the added complexity of 5G as a host technology, our research leverages geospatial beamforming of known signals as spatially dependent white space. In this case, the known synchronization signal burst must be detected with a "beam detector” instead of a "beam search” to properly use beam resources that are not close to cognitive radio nodes. The thesis applies the self-reliant methodology, which defines opportunistic access and power control protocols that limit interference between cellular networks in both the time and frequency domains with additional support in the geospatial domain for 5G NR. Our research determines that an adapted version of Slotted ALOHA for medium access control (MAC) with a no-back-off contention fits the self-reliant approach of our work and timing constraints found in 4G LTE and 5G NR networks.