Fading channels, seen in many wireless systems, provide a hostile environment for reliable communication. Conventional analysis of fading channels has been performed from the single-attempt paradigm . That is, the amount of information that can be reliably communicated with a single codeword transmission attempt is quantified. This works well for idealized, delay-unconstrained systems that always transmit a single, infinite-length codeword. However, practical systems are delay-limited since they must use finite-length codewords. Therefore, the conventional performance metrics based on the single-attempt paradigm have drawbacks for delay-limited systems: &epsis;- capacity does not provide a measure of error-free performance, while delay-limited capacity underestimates performance. For delay-limited systems, transmitters need not restrict themselves to a single transmission attempt per codeword. In fact, practical communication protocols, such as TCP or ARQ, retransmit data when errors occur. Clearly, there is a disconnect in the design of delay-limited systems (multi-attempt) and the conventional measures used to quantify their performance (single-attempt). In this thesis we provide a new analysis framework for delay-limited systems based on the multi-attempt paradigm . We maximize the average communications throughput by optimizing system parameters and use the maximum throughput as a measure of delay-limited communication performance. We consider two common scenarios, the first being only when the receive has channel state information (CSI-R), while in the second both transmitter and receiver it (CSI-RT). With CSI-R, the average transmit power is held constant and throughput is maximized by performing optimal rate selection . With CSI-RT, the transmitter knows the condition of the channel at the time of transmission and can vary the power accordingly. Our analysis is done for an average power constraint on the transmitted signal. We also consider the scenario if an additional peak power constraint on the transmitted signal is added. Therefore throughput is maximized by performing optimal rate selection and power control . As a pre-requisite for throughput maximization, we also solved the outage minimization problem for signals with both peak and average power constraints. We propose maximum &epsis;-throughput (M&epsis;T) and maximum zero-outage throughput (MZT) as measures of best-case communications performance when there is, and is not, a restriction on the maximum number of transmission attempts per codeword, respectively. We show that a far greater throughput is achieved with the multi-attempt approach than the single-attempt approach. The increased throughput comes at the cost of queueing delays that are not present when transmitters are limited to a single transmission attempt. Therefore, we also consider the important situation in which throughput is maximized with a constraint on the queueing delay. In this thesis we provide the procedure to maximize communications throughput for systems and give some non-intuitive design guidelines for delay-limited communication systems in fading channels. Our novel analysis shows that some conventionally held wisdom for delay-unconstrained systems does not hold for delay-limited systems.