<p> This thesis addresses the design of fractionally-spaced equalizers for a digital communication system which is susceptible to Adjacent Channel Interference (ACI). ACI can render an otherwise well designed system prone to excess bit errors. Algorithms for a trained adaptive FIR linear fractionally-spaced equalizer (FSE) with explicit sidelobe control are developed in order to provide robustness to ACI. The explicit sidelobe control is achieved by imposing a quadratic inequality constraint on the frequency response of the equalizer at a discrete set of frequency points in the sidelobe region.</p> <p> Algorithms are developed for both block adaptive and symbol-by-symbol adaptive modes. These algorithms use interior point optimization techniques to find the optimal equalizer coefficients. In the block adaptive mode, the problem is reformulated as a Second Order Cone Program (SOCP). In the symbol-by-symbol adaptive mode, the philosophy of the barrier approach to interior point methods is adopted. The concept of a central path and the Method of Analytic Centers (MAC) are used to develop two practically implementable algorithms, namely IPM2 and SBM, for performing symbol-by-symbol adaptive, fractionally-spaced equalization, with multiple quadratic inequality constraints.</p> <p> The performance of the proposed algorithms is compared to that of the Wiener filter, and the standard RLS algorithm with explicit diagonal loading. In the computer simulations, the proposed algorithms perform better in the sense that they provide the desired robustness when the communication model is prone to intermittent interferers in the sidelobe region of the frequency response of the FSE. Although the proposed algorithms have a moderately higher computational cost, their insensitivity to the deleterious effects of ACI make them an attractive choice in certain applications.</p> / Thesis / Master of Applied Science (MASc)