Title :
Optimizing the transmit power for slow fading channels
Author :
Ligdas, Paschalis ; Farvadin, N.
Author_Institution :
Dept. of Electr. Eng., Maryland Univ., College Park, MD, USA
fDate :
3/1/2000 12:00:00 AM
Abstract :
We consider the design of power-adaptive systems for minimizing the average bit-error rate over flat fading channels. Channel state information, obtained through estimation at the receiver, is sent to the transmitter over a feedback channel, where it is used to optimally adapt the transmit power. We consider finite-state optimal policies to reflect the limitations of the feedback channel. We develop an iterative algorithm that determines the optimal finite-state power control policy given the probability density function (PDF) of the fading. Next, we present a discretized formulation of the problem and obtain a suboptimal solution via standard dynamic programming techniques. The discretization of the problem enables us to obtain a suboptimal policy for arbitrary fading channels for which the analytic expression of the fading probability density function is not available. Simulation results are used to draw conclusions regarding the effects of limited feedback channel capacity, delay and number of states on the bit-error rate performance of the proposed policies under slow and moderate fading conditions
Keywords :
adaptive control; channel capacity; delays; dynamic programming; error statistics; fading channels; feedback; iterative methods; power control; telecommunication channels; telecommunication control; PDF; average BER; bit error rate performance; channel state information; delay; dynamic programming; feedback channel; feedback channel capacity; finite-state optimal policies; flat fading channels; iterative algorithm; optimal finite-state power control policy; power-adaptive systems design; probability density function; simulation results; slow fading channels; suboptimal policy; time varying channel; transmit power optimization; transmitter; Bit error rate; Channel state information; Dynamic programming; Fading; Iterative algorithms; Power control; Probability density function; State estimation; State feedback; Transmitters;
Journal_Title :
Information Theory, IEEE Transactions on