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In this section, we compare the network simulation results of ZTE's WCDMA system with the field test data from real-world networks. The analysis shows that the discrepancy between simulated and actual results can be kept within an acceptable range, confirming that WCDMA network simulations are highly valuable for planning and optimizing future networks.
Wireless network planning plays a crucial role in the development of carrier networks. Effective planning helps achieve a balance between coverage, capacity, quality, and cost. It supports operators in choosing the best implementation strategies at each stage of network construction and expansion, maximizing the return on investment. Simulation is a key component of this process, as it allows engineers to evaluate critical performance metrics such as pilot coverage, optimal cell selection, system load, and handover areas—providing essential guidance for real-world deployment.
To assess the accuracy of these simulations, ZTE conducted extensive comparative analyses between simulation outputs and field test data across multiple test networks both domestically and internationally. The results showed that when simulation parameters are correctly selected and the standardized process is followed, the error between simulated and measured data remains within an acceptable margin. This validates the use of simulation tools in guiding WCDMA network planning and optimization.
WCDMA systems introduce a wide range of data services, making their service characteristics significantly more complex than traditional 2G networks, which primarily focused on voice and low-speed data. Different services cover different areas, and varying service compositions lead to significant differences in required system capacity. Additionally, WCDMA has "soft capacity," meaning its capacity is power-limited and non-linearly related to user numbers and throughput. This complexity makes accurate capacity estimation challenging without specialized simulation tools.
During the simulation process, detailed input data about the planned area—such as geographical features, population density, economic status, and communication models—is essential. The precision of these inputs directly impacts the reliability of the simulation results. However, due to the complexity of real-world conditions, some parameters must be estimated based on industry experience or literature. These approximations may cause deviations between simulated and actual results.
To evaluate these discrepancies, a comparison between simulation and actual measurements is necessary. This not only verifies the accuracy of the simulation but also helps refine the model by identifying and adjusting key parameters. In early planning stages, such comparisons can validate the correctness of wireless parameter settings and improve overall simulation accuracy.
One of the main methods used for comparing simulation and measurement data is analyzing the data stored in "bins"—geographical grid points. For example, if the electronic map used in the simulation has a resolution of 20 meters, each 20m x 20m area is considered a bin. Both simulation and field test data are stored in these bins, and their alignment is analyzed to determine how well they match.
ZTE developed a dedicated tool to compare simulation and actual measurement data. It provides statistical analysis of errors, including mean, standard deviation, probability distribution functions (PDF), cumulative distribution functions (CDF), and confidence intervals. These results are visually represented on maps using MapInfo, offering a clear and objective evaluation of simulation accuracy.
Key performance indicators (KPIs) such as pilot strength (Ec) and pilot quality (Ee/Io) are commonly compared during the analysis. These parameters are essential for assessing network performance and ensuring that the simulation aligns with real-world conditions.
In one case study, ZTE used Aircom software to simulate a test network and compared the results with field test data collected using an Agilent Road Tester. The propagation model used in the simulation included several factors such as path loss, diffraction loss, and clutter loss. The base station distribution was visualized in a map, and the simulation results were compared with the actual drive test data.
The analysis of 8,324 valid samples revealed that the mean error in Ec was -3.45 dB, with a standard deviation of 9.47 dB. The error distribution was visualized through PDF and CDF histograms, showing that the simulation results were generally slightly lower than the measured values. This indicates that the simulation was close to real-world conditions and could be further refined by adjusting simulation parameters, especially the propagation model.
Based on the statistical analysis, confidence intervals for the mean and standard deviation were calculated. At a 95% confidence level, the error range was found to be within acceptable limits. Although some discrepancies remained due to the complexity of the wireless environment, the simulation accuracy could be improved through parameter adjustments and the use of multiple propagation models.
By applying the comparison tool, engineers could visualize error distributions along specific road segments and fine-tune simulation parameters accordingly. This iterative process helped reduce the gap between simulation and reality, leading to more accurate predictions and better-informed network decisions.
In summary, ZTE’s simulation results have proven to be reliable and useful in both pre-planning and network optimization phases. Through continuous comparisons and adjustments, the company has refined its simulation techniques, gaining deeper insights into local conditions and improving the accuracy of its planning tools. By integrating the latest field test data, simulations are now continuously updated and optimized, making them an essential part of modern network management.