the air interface. Small cell UE (normal CQI) Small cell UE (ABS CQI) = Normal subframe Macro cell UE = Mandatory ABS subframe = Optional ABS Figure 7.17 UE measurements with ABS adaptation LTE Small Cell Optimization Pico cell ABS info ABS info ABS info ABS info Macro NTTIs NTTIs NTTIs uRE = number of UEs in range extension area Figure 7.18 Periodic reporting over X2 for fast ABS adaptation The gain of fast ABS adaptation is illustrated by means of system level simulations. The performance results presented in Figures 7.19 and 7.20 are obtained for the same 3GPP Release 12 small cell scenario 1 as used in Section 'Basic eICIC Performance Considerations'. For both the slow and fast ABS adaptation cases, the pico cell RE is semi-statically adjusted as a function of the average offered traffic. It is clearly observed how the application of fast ABS offers additional benefits in both the 5-percentile and 50-percentile end-user throughput. Thus, using fast ABS adjustment algorithms further boosts the performance of eICIC. The added gain from fast ABS adjustment is on the order of 30-50% as compared to the slow semi-static adaptation of the ABS muting pattern. The gain from fast ABS adjustment is simply a result of more accurately adapting the macro cells muting pattern in coherence with local experi- enced traffic fluctuations. Additional results and insight on fast ABS adjustment are available in [8], [13] and [14]. Fast ABS adaptation Slow ABS adaptation Average offered load (Mbps) Figure 7.19 5-percentile end-user throughput with slow and fast ABS adaptation Small Cell Interference Management Fast ABS adaptation Slow ABS adaptation Average offered load (Mbps) Figure 7.20 50-percentile (median) end-user throughput with slow and fast ABS adaptation eICIC Performance in a Site-Specific Scenario In order to shed further light on the performance of eICIC, we next present results from a site- specific use case. The site-specific use case is based on data from a dense metropolitan area with realistic deployment of macro 