es. As an example [10], studies of the 3GPP Release 12 dense outdoor small cell scenarios with 10 small cells within a localized circular area with radius of 50 m show that even at high offered traffic load, only approximately half of the cells are scheduling users in each transmission time interval. This finding is for the case where the traffic arrival is according to a homogeneous Poisson process, assuming a finite payload for each user. It is furthermore found that only approximately 30% of the users have a dominant interference ratio (DIR) above 3 dB, as typically required to achieve worthwhile gains from mitigating the dominant interferer. The dominant interferer for a user is furthermore found to be highly time-variant due to the small cells downlink transmit power variations depending on whether they have schedulable users. Hence, the findings from [11] essentially tell us that only a subset of users in an UDN can gain from ICIC, and for those clear victim users with a high DIR, the ICIC mechanism needs to be rather dynamic as the cell playing the role of aggressor is likely to vary during the call duration for the user. Those are properties that are different from what is typically observed for other network deployments such as macro-only carriers or co-channel macro-pico scenarios. In the following, two examples of efficient network-based ICIC schemes for UDN cases are presented. First, a proactive ICIC scheme is presented, which relies on coordinated time-domain muting among the small cells. The basic principle of the proactive ICIC scheme is LTE Small Cell Optimization to constantly optimize the system performance. Second, a reactive carrier-based ICIC scheme is presented, which is first activated if interference problems are detected that prevent the users from having their minimum data rate requirement fulfilled. Performance results for those two solution candidates are presented by dense outdoor and indoor small cell deployments, respectively. 8.4.2 Proactive Time-Domain Inter-cell Interference Coo