Reproducible LTE uplink performance analysis using precomputed interference signals
EURASIP Journal on Advances in Signal Processing
The consideration of realistic uplink inter-cell interference is essential for the overall performance testing of future cellular systems, and in particular for the evaluation of the radio resource management (RRM) algorithms. Most beyond-3G communication systems employ orthogonal multiple access in uplink (SC-FDMA in LTE and OFDMA in WiMAX), and additionally rely on frequency-selective RRM (scheduling) algorithms. This makes the task of accurate modeling of uplink interference both crucial and
... non-trivial. Traditional methods for its modeling (e.g., via additive white Gaussian noise interference sources) are therefore proving to be ineffective to realistically model the uplink interference in the next generation cellular systems. In this article, we propose the use of realistic precomputed interference patterns for LTE uplink performance analysis and testing. The interference patterns are generated via an LTE system-level simulator for a given set of scenario parameters, such as cell configuration, user configurations, and traffic models. The generated interference patterns (some of which are made publicly available) can be employed to benchmark the performance of any LTE uplink system in both lab simulations and field trials for practical deployments. It is worth mentioning that the proposed approach can also be extended to other cellular communication systems employing OFDMA-like multiple access with frequency-selective RRM techniques. The proposed approach offers twofold advantages. First, it allows for repeatability and reproducibility of the performance analysis. This is of crucial significance not only for researchers and developers to analyze the behavior and performance of their systems, but also for the network operators to compare the performance of competing system vendors. Second, the proposed testing mechanism evades the need for deployment of multiple cells (with multiple active users in each) to achieve realistic field trials, thereby resulting in significant cost (and time) savings in the field trails.