Doctor of Philosophy, The Ohio State University, 2022, Electrical and Computer Engineering

The real-time applications and the IoT promote the need for a newer idle spectrum to support the required high traffic. This pushes toward the emergence of the millimeter-wave (mmWave) and the sub-Terahertz (sub-THz) bands in wireless communication. Albeit these higher frequency bands offer wide spectrum help improving the spectral efficiency, it comes with the challenge of alleviating the severe attenuation. MmWave transceivers use large antenna arrays to form high-directional beams and overcome severe attenuation. A large array size leads to a costly beam alignment process if no prior information about beam directions is available. Beam alignment has two phases: beam discovery, and beam tracking. Beam discovery is finding the beam direction by consuming several pilot symbols to find the optimum direction. Moreover, beam tracking is a common approach to keep the discovered beams tightly coupled without frequent beam discovery to eliminate the overhead associated with realignment. Both phases become more difficult as the beams get narrower since slight mismatches lead to significant degradation in SNR as the beam coherence times are short. As a result, beams may lose alignment before they can be readjusted periodically with the aid of pilot signals. In this thesis, we introduce two complementary proposals. The first proposal is for the issue of beam tracking, and the second proposal is for the issue of beam discovery. In the first part of the thesis, we propose a model where the receiver adjusts beam direction continuously over each physical-layer sample according to a carefully calculated estimate of the continuous variation of the beams. Our approach contrasts the classical methods, which fix the beams in the same direction between pilots. In our approach, the change of direction is configured using the estimate of variation rate via two different methods; a Continuous-Discrete Kalman filter and an MMSE of a first-order approximation of the variation. Our method (open full item for complete abstract)

Committee: C. Emre Koksal (Advisor); Eylem Ekici (Committee Member); Abhishek Gupta (Committee Member) Subjects: Computer Science; Electrical Engineering; Information Science