s mute time for voice calls and as 0 Kbps throughput for other services. Throughput Optimization Throughput can be measured from drive tests or when traffic is high enough based on cell level counters (as shown in Chapter 13) or, as used in this chapter, based on methodology defined in [9]. As described in [9] in Figures 12.39 and 12.40, the 3GPP-defined scheduled IP throughput formula is slightly modified SO that denominator contains also the time when the eNodeB LTE Key Performance Indicator Optimization Low band (10 MHz) High band (10 MHz) High band (20 MHz) Expon. (low band (10 MHz)) Expon. (high band (10 MHz)) Expon. (high band (20 MHz)) 100,000 y =685.88e0.3125x 10,000 Average CQI per cell Figure 12.39 Downlink average non-GBR user throughput as a function of reported CQI. Cells with more than 250 MB downlink data volume transmitted per 15 minutes statistics sample are included into the analysis Low band (10 MHz) High band (10 MHz) High band (20 MHz) Expon. (low band (10 MHz)) Expon. (high band (10 MHz)) Expon. (high band (20 MHz)) 100,000 y = 2055.5e0.0923.x 10,000 751.34e Average PUSCH SINR (dB) Figure 12.40 Uplink average non-GBR throughput per user as a function of average PUSCH SINR. Cells with more than 100 MB uplink data volume received per 15 minutes statistics sample are included into the analysis LTE Small Cell Optimization buffer contains data to a UE but that UE is not scheduled. Also carrier aggregation (CA) is not considered, that is, throughput is given as single-carrier throughput. As shown in Figure 12.39 while the reported (by UE) CQI decreases the average non-GBR throughput per user decreases rapidly. Average throughput per user per cell per band decreases following exponential trend line. As can be seen, the high band with 20 MHz bandwidth performs the best followed by the low and high bands with 10 MHz bandwidth. It should be noted that only the 15 minutes statistics samples for which the cell delivers 250 MB or more downlink data volume are included. The CQI reduction in turn is caused