Analytical Model of Proportional Fair Scheduling in Interference-limited OFDMA/LTE Networks

Various system tasks like interference coordination, handover decisions, admission control etc. in upcoming cellular networks require precise mid-term (spanning over a few seconds) performance models. Due to channel-dependent scheduling at the base station, these performance models are not simple to obtain. Furthermore, upcoming cellular systems will be interference-limited, hence, the way interference is modeled is crucial for the accuracy. In this paper we present an analytical model for the SINR distribution of the \textit{scheduled} subcarriers of an OFDMA system with proportional fair scheduling. The model takes the precise SINR distribution into account. We furthermore refine our model with respect to uniform modulation and coding, as applied in LTE networks. The derived models are validated by means of simulations. In additon, we show that our models are approximate estimators for the performance of rate-based proportional fair scheduling, while they outperform some simpler prediction models from related work significantly.Comment: 7 pages, 6 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

On Semi-Static Interference Coordination under Proportional Fair Scheduling in LTE Systems

In this paper we consider the design of semi-static inter-cell interference coordination schemes for LTE networks. In this approach, base stations coordinate the power settings per resource block over long time spans such as seconds. In order to optimize the power settings, one needs to employ models which predict the rate of terminals over the next coordination period under the usage of a given power setting. However, these models are typically quite simple and neglect the impact from fading as well as from dynamic resource allocation performed at the base stations on a millisecond basis. Ignoring such properties of OFDMA networks leads therefore to suboptimal transmit power settings. In this paper, we study the impact from a precise rate prediction model that accurately accounts for fading and dynamic resource allocation. On the down-side, this more precise model leads to a much more involved optimization problem to be solved once per coordination period. We propose two different heuristic methods to deal with this problem. Especially the usage of genetic algorithm results to be promising to counteract the complexity increase. We then study the overall system performance and find precise rate prediction models to be essential for semi-static interference coordination as they provide significant performance improvements in comparison to approaches with simpler models.QC 20130830</p