Link adaptation algorithms for channel estimation error mitigation in LTE systems

In Long Term Evolution (LTE) systems, the evolved Node B (eNodeB) performs link adaptation to improve the system performance on the basis of channel quality information estimated and fedback by the user equipments (UEs). However, the channel estimation error (CEE) can not be avoided due to hardware constraint. To make up the performance loss caused by CEE, two types of link adaptation algorithms are proposed: weighted average (WA) algorithm based on three different parameters and an enhanced adaptive time window (ATW) algorithm. Unlike pervious work, this paper not only presents the specific process of all the algorithms but also takes the theoretical derivation of performance comparison into consideration. Moreover, simulation results are demonstrated using an LTE system-level simulator, which show that the WA algorithm based on channel estimation value can effectively mitigate CEE and achieve a significant gain. Subsequently, a better system performance can be obtained using ATW algorithm by adjusting the window size dynamically.