Performance prediction for OFDMA systems with dynamic power and subcarrier allocation

It is well known that channel-dependent OFDMA resource assignment algorithms provide a significant performance improvement compared to static (i.e., channel-unaware) approaches. Such dynamic algorithms constantly adapt resource assignments to current channel states according to some objective function. Due to these dynamics, it is difficult to predict the resulting performance for such schemes given a certain scenario (characterized by the number of terminals in the cell and their average channel gains). In this paper we provide a novel, analytical framework for performance prediction, which takes dynamic power and subcarrier allocation into account. The analysis is based on fundamental transformations of the channel gains caused by the dynamic subcarrier allocations. This insight allows for deriving probability functions of the achieved rate per subcarrier which ultimately yields expressions for the expected minimal rates as well as outage probabilities for certain rate demands. Hence, the methods presented in this paper for performance prediction can be employed for admission control in systems with dynamic resource allocation. We illustrate the applicability of our derivations with respect to the capacity of 802.16e systems for Voice-over-IP and video streams. The results demonstrate a significant improvement compared to state-of-the art approaches but also reveal room for improvement of this approach compared to the optimal system performance.