Cooperative Interference Prediction for Enhanced Link Adaptation in the 3GPP LTE Uplink

The interference situation in the uplink of cellular networks, such as the 3GPP UTRAN Long Term Evolution (LTE), is usually highly volatile since from one transmission time interval to the other different users might be scheduled in nearby cells, thus often causing completely different levels of interference. This unstable behavior of the interference generally has a negative impact on the performance of fast link adaptation schemes since there is always an inherent delay between the time when the link adaptation is performed and the actual data transmission. In order to partially mitigate this problem, we propose in this paper a novel approach for predicting the interference situation during the actual data transmission already in advance, so that the link adaptation process can be considerably improved. This is accomplished by exchanging scheduling information between a set of cooperating base stations combined with multi-cell channel estimation. The performance of the proposed scheme is evaluated by means of extensive system-level simulations and we show that significant performance gains may be realized this way.