ow). Examples in Section 13.3.3 show the impact of power control settings on different perfor- mance indicators during the mass event. Throughput per User and Spectral Efficiency The uplink throughput per user depends on the bandwidth allocation, spectral efficiency and number of users simultaneously transmitting data to a cell. As explained in the previous section the traffic increase causes inter-cell interference increase which is visible as PUSCH SINR decrease and PUSCH RSSI increase. PUSCH SINR decrease in turn means that the spectral efficiency of the cell decreases and therefore the end-user throughput decreases. On the other hand, the increase in the number of connected users which are uploading at the same time causes additional throughput per user degradation as the cell radio resources are shared among all the users. The throughput per user can be estimated based on the cell-level counters, for example, simply dividing the cell-level throughput by the number of estimated users which are having data in the UE buffer (i.e. those UEs from which the eNodeB has received buffer status report indicating that there is still data in the buffer and are therefore taken into account for scheduling of the resources in the next TTI). The cell-level throughput in turn can be estimated by dividing the received user plane bits by the number of active TTIs used to allocate resources to receive those bits. The number of bits should contain only the user plane data bits excluding the retransmissions, hybrid automatic repeat request (HARQ) or radio link control (RLC) retransmissions. Active TTI is a bit difficult to measure as the TTI is active regardless of the number of physical resource blocks (PRBs) used during the TTI. Therefore, this type performance indicator is not very accurate when the PRB utilization (how many PRBs are used from all available) is very low (<30%). Scaling the cell throughput for, for example, 10% PRB utilization to 100% PRB utilization, simply by dividing the cell throughput by PRB utilization ca