In the development and standardization of LTE, as well as in the implementation process of equipment manufacturers, simulations are necessary to test and optimize algorithms and procedures. This has to be carried out on the physical layer (link level) and in the network (system level) context:
Link level simulations
LL simulations allow for the investigation of channel estimation, tracking, and prediction algorithms, synchronization algorithms, Multiple-Input Multiple-Output (MIMO) gains, Adaptive Modulation and Coding (AMC) and feedback. Furthermore, receiver structures (typically neglecting inter-cell interference and impact of scheduling, as this increases simulation complexity and runtime dramatically), modelling of channel encoding and decoding, physical layer modelling crucial for system level simulations and alike are typically analyzed on link level. Although MIMO broadcast channels have been investigated quite extensively over the last years, there are still a lot of open questions that need to be resolved, both in theory and in practical implementation. For example, LTE offers the flexibility to adjust many transmission parameters, but it is not clear up to now how to exploit the available Degrees of Freedom (DoF) to achieve the optimum performance. Some recent theoretical results point out how to proceed in this matter, but practical results for LTE are still missing.
System level simulations
SL simulations focus more on network-related issues, such as resource allocation and scheduling, multi-user handling, mobility management, admission control, interference management], and network planning optimization. On top of that, in a multi-user oriented system, such as LTE, it is not directly clear which figures of merit should be used to assess the performance of the system. The classical measures of (un)coded Bit Error Ratio (BER), (un)coded BLock Error Ratio (BLER), and throughput are not covering multi-user scenario properties. More comprehensive measures of the LTE performance are for example fairness, multi-user diversity, or DoF. However, these theoretical concepts have to be mapped to performance values that can be evaluated by means of simulations.