Dynamic Rate Control Algorithms for HDR Throughput Optimization

Friday, August 10, 2001 - 3:30pm - 4:30pm
Keller 3-180
Phil Whiting (Alcatel-Lucent Technologies Bell Laboratories)
The relative delay tolerance of data applications, together with the bursty traffic characteristics, opens up the possibility for scheduling transmissions so as to optimize throughput. A particularly attractive approach, in fading environments, is to exploit the variations in the channel conditions, and transmit to the user with the currently `best' channel. We show that the `best' user may be identified as the maximum-rate user when the feasible rates are weighed with some appropriately determined coefficients. Interpreting the coefficients as shadow prices, or reward values, the optimal strategy may thus be viewed as a revenue-based policy, which always assigns the transmission slot to the user yielding the maximum revenue.

Calculating the optimal revenue vector directly is a formidable task, requiring detailed information on the channel statistics. Instead, we present adaptive algorithms for determining the optimal revenue vector on-line in an iterative fashion, without the need for explicit knowledge of the channel behavior. Starting from an arbitrary initial vector, the algorithms iteratively adjust the reward values to compensate for observed deviations from the target throughput ratios.

Numerical experiments are presented which demonstrate long-run convergence of the algorithms and the transient performance is also examined. Generalisations of the approach beyond the one-user-at-a-time case are also discussed.