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University of Colorado – 25 00MHz WiMAX RF Plan. Airspan RF Planning January 2011 V1.1. WiMAX 16e – MacroMAXe RF Inputs. DTM Layer. Clutter Layer. Network Layout. Frequency Plan. Frequency and Preamble Plan. BS and Sector Details. Network Analysis Layers Description.
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University of Colorado – 2500MHz WiMAX RF Plan Airspan RF Planning January 2011 V1.1
Network Analysis Layers Description • Best Server Signal Strength - This layer provides the downlink signal strength expressed in dBm for the best serving sector and for the chosen subscriber equipment. The best server is determined from the best signal CNIR of the preamble signal. • Best Server - This layer provides the downlink coverage area for the sector with the best preamble signal CNIR. • Downlink MCS - This layer provides information on the downlink modulation that has the highest spectral efficiency, i.e., the modulation that provides the highest useful bits per symbol ratio and where the coverage probability is above the defined target cell edge coverage probability. • Uplink MCS - This layer provides information about the best uplink modulation that offers the highest spectral efficiency, i.e., the modulation that provides the highest useful bits per symbol ratio. This layer only uses a fraction of all available sub-channels to illustrate uplink UL MCS coverage. • Downlink C/(N+I) - This layer provides the downlink C/(N+I) value of the best channel where C is computed based on the data or traffic power. • Uplink C/(N+I) - This layer provides the uplink C/(N+I) value of the best channel where C is computed based on the data or traffic power.
Uplink MCS UL – 10 Subchannels
Uplink C/(N+I) UL – 10 Subchannels
BS Sector Antenna 90-deg AW3008 2500MHz Fixed 4-deg Tilt
RF Plan Notes: Propagation Modelling • Propagation models simulate how radio waves travel through the environment from one point to another. Because of the complex nature of propagation modelling and the great amount of information needed to perform an accurate estimation of path loss, there will always be differences between the path loss estimation of a model and real-world measurements. Nevertheless, some models are inherently more accurate than others in specific situations, and it is always possible to refine a model (or its understanding of the environment) so that it better matches the real world. There are several things that can be done in order to minimize discrepancies between the propagation model and the real world, including choosing an appropriate model and calibrating it effectively. • This study uses the CRC-Predict 4.x propagation model. CRC-Predict is the most widely used propagation model in the suite of radio-wave prediction algorithms available in Mentum Planet. Originally developed by the Communications Research Centre (Ottawa, Canada), CRC-Predict is now developed by Mentum. Some traditional approaches to radio-wave propagation are empirical in nature and begin with the collection of real-world measurements, fitting them to curves and then applying the curves to similar geographic areas. The limitation of these approaches is that they cannot take into account the infinite variety of landscapes that can occur. In contrast, CRC-Predict is a deterministic model based on Physical Optics, a form of wave theory. Predictions are based on a detailed simulation of diffraction over terrain (including clutter), and include an estimate of local clutter attenuation. As a result, predictions of coverage gaps and interference areas are based specifically on the particular terrain in question and are more likely to be accurate, given that the terrain and clutter data are accurate. • Drive-test measurements are still required for reliable planning, but their use is more a matter of compensating for the incompleteness/inaccuracy of clutter data and adjustment of the model’s clutter property assignments to increase accuracy. This is called model tuning.
