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We consider cross-layer adaptive transmission for a single-user system with stochastic data traffic and a time- varying wireless channel. The objective is to vary the transmit power and rate according to the buffer and channel conditions so that the system throughput, defined as the long-term average rate of successful data transmission, is maximized, subject to an average transmit power constraint. When adaptation is subject to a fixed bit error rate (BER) requirement, maximizing the system throughput is equivalent to minimizing packet loss due to buffer overflow. When the BER requirement is relaxed, maximizing the system throughput is equivalent to minimizing total packet loss due to buffer overflow and transmission errors. In both cases, we obtain optimal transmission policies through dynamic programming. We identify an interesting structural property of these optimal policies, i.e., for certain correlated fading channel models, the optimal transmit power and rate can increase when the channel gain decreases toward outage. This is in sharp contrast to the water-filling structure of policies that maximize the rate of transmission over fading channels. Numerical results are provided to support the theoretical development.