Dynamic Programming and Optimal Control
Dynamic Programming and Optimal Control
Optimizing the Power Allocation for Rayleigh Block-Fading Channels with Outage Capacity Constraints
IEEE Transactions on Wireless Communications
Optimum power control over fading channels
IEEE Transactions on Information Theory
Limiting performance of block-fading channels with multiple antennas
IEEE Transactions on Information Theory
Communication over fading channels with delay constraints
IEEE Transactions on Information Theory
Delay-constrained capacity with causal feedback
IEEE Transactions on Information Theory
Service outage based power and rate allocation
IEEE Transactions on Information Theory
Service outage based power and rate allocation for parallel fading channels
IEEE Transactions on Information Theory
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In this letter, a Rayleigh block-fading (BF) channel, subject to an information outage probability constraint, is considered. The transmitter is assumed to have causal knowledge of the channel state information (CSI), which is exploited to intelligently allocate the power over the blocks (and hence vary the channel mutual information) to minimize the average transmitted power per block for satisfying the outage probability constraint for a given target code-rate. We first show that the optimal solution to this problem can be obtained by solving the reverse problem of minimizing the outage probability for a range of long-term power constraints through repeated uses of dynamic programming (DP), which is nevertheless prohibitively complex. Then, we develop a suboptimal allocation algorithm which still uses DP to exploit the CSI causality but at a much reduced complexity. A performance lower-bound is further derived, which permits us to see that the proposed algorithm is near-optimal, especially in the small outage probability regime. A scheme called equal-outage-probability per block (EOPPB) which compromises the performance further for reducing the complexity is also devised. To compare the methods, we evaluate both analytically and numerically their complexities and performance. The results are finally generalized to multiple-input multiple-output (MIMO) BF channels.