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A technique is proposed for the derivation of upper bounds on channel capacity. It is based on a dual expression for channel capacity where the maximization (of mutual information) over distributions on the channel input alphabet is replaced with a minimization (of average relative entropy) over distributions on the channel output alphabet. We also propose a technique for the analysis of the asymptotic capacity of cost-constrained channels. The technique is based on the observation that under fairly mild conditions capacity achieving input distributions "escape to infinity." The above techniques are applied to multiple-antenna flat-fading channels with memory where the realization of the fading process is unknown at the transmitter and unknown (or only partially known) at the receiver. It is demonstrated that, for high signal-to-noise ratio (SNR), the capacity of such channels typically grows only double-logarithmically in the SNR. To better understand this phenomenon and the rates at which it occurs, we introduce the fading number as the second-order term in the high-SNR asymptotic expansion of capacity, and derive estimates on its value for various systems. It is suggested that at rates that are significantly higher than the fading number, communication becomes extremely power inefficient, thus posing a practical limit on practically achievable rates. Upper and lower bounds on the fading number are also presented. For single-input-single-output (SISO) systems the bounds coincide, thus yielding a complete characterization of the fading number for general stationary and ergodic fading processes. We also demonstrate that for memoryless multiple-input single-output (MISO) channels, the fading number is achievable using beam-forming, and we derive an expression for the optimal beam direction. This direction depends on the fading law and is, in general, not the direction that maximizes the SNR on the induced SISO channel. Using a new closed-form expression for the expectation of the logarithm of a noncentral chi-square distributed random variable we provide some closed-form expressions for the fading number of some systems with Gaussian fading, including SISO systems with circularly symmetric stationary and ergodic Gaussian fading. The fading number of the latter- is determined by the fading mean, fading variance, and the mean squared error in predicting the present fading from its past; it is not directly related to the Doppler spread. For the Rayleigh, Ricean, and multiple-antenna Rayleigh-fading channels we also present firm (nonasymptotic) upper and lower bounds on channel capacity. These bounds are asymptotically tight in the sense that their difference from capacity approaches zero at high SNR, and their ratio to capacity approaches one at low SNR.