in megabytes per cell and per 15 minutes in buffer in uplink reaches much higher values than in downlink due to the fact that uplink spectral efficiency is much lower than downlink (no MIMO nor 64QAM). Also the uplink SINR decreases rapidly as the number of users with data in buffer in uplink increases as shown in Figure 13.56. The CQI remains almost constant regardless of the number of users with data in buffer in downlink as shown in Figure 13.57. Therefore, it can be said that this network uplink limited during the special event. As the number of users grows, and therefore the amount of users with data in buffer increases as well as the data volume increases as shown in Figure 13.51, the scheduling delay (the time instance between user's data packet arrival to the eNodeB and the packet successfully transmitted to the user) increases as shown in the Figure 13.52. This increased scheduling delay causes end-user-experienced throughput decrease as more and more TTIs are required between single UE scheduling instances. The results in Figure 13.51 can be used to derive spectral efficiency results. In down- link during maximum PRB utilization, around 2500 MB per 15 minutes can be delivered which is 22.2 Mbps on average. Considering 10 MHz bandwidth cells the spectral efficiency becomes 2.22 bps/Hz/cell which is at the upper end of the 3GPP-simulated results [4]. In uplink correspondingly 1000 MB per 15 minutes is received which indicates around 0.9 bps/Hz/cell which is also at the upper end of the 3GPP-simulated results when considering 2rx receiver [4]. The scheduling delay shown in Figure 13.52 can also be increased due to the PDCCH ing which delivers the uplink and downlink scheduling grants. Therefore, the CCE blocking shown in Figure 13.39 can cause increase in scheduling delay as shown in Figure 13.53. This is due to the fact that in case required aggregation level cannot be used for scheduling certain UE and transmission power increase cannot be done to boost the available aggregation level decoding performanc