The detrimental effects rapid power fluctuation has on wireless narrowband communication channels has long been a concern of the mobile radio community as appropriate channel models seek to gauge link quality. Furthermore, advances in signal processing capabilities and the desire for spectrally efficient and low power radio systems have rekindled the interest for adaptive transmission schemes, hence some method of quickly probing the link quality and/or predicting channel conditions is required. Mathematical distributions for modeling the channel profile seek to estimate fading parameters from a finite number of discrete time samples of signal amplitude. While the statistical inference of such estimators has proven to be robust to rapidly shifting channel conditions, the benefits are quickly realized at the expense of processing complexity. Furthermore, computations of the best-known estimation techniques are often iterative, tedious, and complex. This thesis takes a renewed look at estimating fading parameters for the Nakagami-m, Rice-K, and Weibull distributions, specifically by showing that the need to solve transcendental equations in the estimators can be circumvented through use of polynomial approximation in the least-squared error sense or via asymptotic series expansion which often lead to closed-form and simplified expressions. These new estimators are compared to existing ones, the performances of which are comparable while preserving a lower computational complexity. In addition, the thesis also investigates the impact knowledge of the fading profile has on systems employing adaptive switching modulation schemes by characterizing performance in terms of average bit error rates (BER) and spectral efficiency. A channel undergoing Rice-$K$ fading on top of log-normal shadowing is simulated by correlating samples of received signal amplitude according to the user's doppler speed, carrier frequency, etc. The channel's throughput and BER performances are analyzed using the above estimation techniques and compared to non-estimation assumptions. Further discussion on narrowband fading parameter estimation and its applicability to wireless communication channels is provided. / Master of Science