Dynamic rate control algorithms for HDR throughput optimization

Abstract

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. The algorithms are validated through extensive numerical experiments. Besides verifying long-run convergence, we also examine the transient performance, in particular the rate of convergence to the optimal revenue vector. The results show that the target throughput ratios are tightly maintained, and that the algorithms are well able to track sudden changes in the channel conditions or throughput targets.2000 Mathematics Subject Classification: 60K25 (primary), 68M20, 90B18, 90B22 (secondary).

Beyond Proportional Fair: Designing Robust Wireless Schedulers

“…In the past, a number of channel-aware scheduling algorithms have been proposed [1,2,3,4] to exploit the time-varying nature of user channel conditions without sacrificing fairness. The Proportional Fair (PF) algorithm [5] is one such channel-aware algorithm that has been widely deployed in cellular data networks, especially in 3G networks such as CDMA-based EV-DO [5] and GSM-based HSDPA networks.…”

Flow-Level Stability of Channel-Aware Scheduling Algorithms

“…The next proposition provides a characterization of the optimal solution to the above linear program based on the complementary slackness conditions [4], [13].…”

“…A prime example is the Proportional Fair algorithm, which has been adopted as the default scheduler for the CDMA 1xEV-DO system [7], [14], [16], and is also considered for implementation in HSDPA. The performance of channel-aware scheduling algorithms has mainly been investigated at the packet level for a static user scenario, sometimes including packet-scale dynamics [4], [28], but often assuming infinite backlogs [1], [13], [23], see also [24], [25], [31], [33] for related results. The assumption of a static user population is a reasonable modeling convention because of the separation of time scales: the scheduling mechanism operates at the packet level on which the user population evolves only relatively slowly.…”

Exploiting wireless channel state information for throughput maximization

“…The problem of scheduling transmissions over a wireless channel with time-varying transmission rates is considered in [11], [6], [9] and [8]. The problem of providing a scheduling policy that stabilizes the system whenever the arrival-rate vector lies within the stability region is dealt in [11] and in [8].…”

“…In [9] and [6] the problem of developing a scheduling policy for efficient channel utilization is considered for the case that all the queues are unstable. In [9] the state of a channel is modeled by a stochastic process, which represents the level of performance of the given channel.…”