overed by several cells. During the working hours traffic is higher and subscribers are concentrated within central business districts which are challenging from inter-cell interference control point of view (due to the high rise buildings with site acquisition constraints). Figure 13.31 shows how the network efficiency varies as a function of downlink data volume per cell per hour. It can be seen how the average reported CQI decreases in linear manner as the downlink data volume per cell increases. The starting point, indicated by point 1 in Figure 13.31 for average CQI during the hours of low data volume per cell per hour is mainly a function of cell density and dominance. During the low data volume per cell per hour the interference is caused by downlink cell-specific Downlink data volume per cell per hour (GB) Figure 13.31 Channel quality indicator as a function of downlink data volume per cell per hour over all the cells in the network LTE Small Cell Optimization Normal hours Mass event hours DL data volume per cell per hour (GB) Figure 13.32 Average channel quality indicator as a function of downlink data volume per cell per hour in a cluster of 24 cells over a few days, including the mass event hours reference signals transmitted by neighbouring cells (assuming no cancellation of cell-specific reference signals by the UEs). When the data volume per cell per hour increases, indicated by point 2 in Figure 13.31, the PDSCH usage increases and becomes the dominant source of interference from and to neighbouring cells. The slope is defined mostly by the same factors as the starting point - cell density and dominance. There is also a separate distinctive group, indicated by point 3 in Figure 13.31, below the linearly distributed samples that is generated during the working hours as the distribution of UEs in the network has changed to more concentrated in certain areas increasing the data volume per cell per hour more than on average across all the cells in the network. Mass event is an extreme example of radica