0 5.0 Number of Europe, North America, sectors per APAC, ANZ subscribers Latin America, Middle East, 1.1 1.1 Africa Figure 12.52 Network density benchmarking as estimated number of sectors per 1000 subscribers Figure 12.53 Average UE-reported CQI of cells in the network increases as with very dense networks any excessive resource usage for signalling can cause massive inter-cell interference problems. 12.10 Summary The LTE network performance measured by network or drive test KPIs can be perfected by parameter tuning. When the networks get more and more dense the parameter tuning must also take into account that inter-cell interference should be always minimized. Therefore, the optimization target is to have the best possible KPI values with lowest possible resource LTE Small Cell Optimization and power allocations. Physical layer optimization should never be ignored as highest gains in network performance can be achieved via physical layer optimization. This is especially the case of very dense networks and when the network loading and therefore inter-cell inter- ference increases. The throughput performance can be further (on top of the physical layer optimization) improved by use of spatial multiplexing transmission modes especially when cross-polarized antennas are used at the eNodeB side. Upgrading from 2x2 MIMO to 4x2 MIMO improves user and cell throughputs across the whole SINR range but especially at the poor SINR area. Activation of 3GPP-specified restricted cyclic shift set for random access preamble generation can greatly improve the KPIs for the cells covering the high-speed train. References [1] 3GPP TS 36.213, 'Physical Layer Procedures', V. .10.9.0, 2013. [2] 3GPP TS 36.101, 'Evolved Universal Terrestrial Radio Access (E-UTRA); User Equipment (UE) Radio Trans- mission and Reception', v.10.9.0, 2013. [3] 3GPP TS 36.300, 'Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Overall Description; Stage 2', v.10.9.0, 2012. [4] 3GPP TS 36.3