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In this section, we analyze the results of ZTE's WCDMA network simulations by comparing them with field test data. The findings indicate that the discrepancies between simulation and real-world measurements are within an acceptable range, which confirms the value of WCDMA network simulations in guiding network planning and optimization. Wireless network planning plays a crucial role in the development of carrier networks, as it helps achieve a balanced approach between coverage, capacity, quality, and cost. Proper planning allows operators to implement the most effective strategies at every stage of network construction, expansion, and optimization, ultimately maximizing returns on investment.
Simulation is a vital component of the planning process. By simulating system behavior, key performance indicators such as pilot coverage, optimal cell selection, system load, and handover areas can be evaluated. These insights provide critical guidance for real-world deployment. To ensure the accuracy of these simulations, ZTE conducted extensive comparative analyses between simulated results and field test data across multiple test networks globally. The results showed that when simulation parameters are correctly selected and processes are followed according to standards, the difference between simulation and actual test results remains within an acceptable margin. This validates the effectiveness of simulation tools in supporting WCDMA network planning and optimization.
WCDMA systems introduce a wide variety of data services, making their network characteristics significantly more complex than traditional 2G networks, which were primarily voice-focused. Different services cover different areas, and varying service mixtures affect the required system capacity. Additionally, WCDMA has soft capacity, meaning it is power-limited and non-linear in relation to user numbers and throughput. This complexity makes accurate capacity estimation difficult, requiring specialized planning tools. Simulation tools help evaluate system performance more accurately, enabling better decisions regarding network scale and investment.
To conduct simulations, detailed input data about the planned area is essential, including geographical features, population density, economic status, and communication models. The more precise these inputs, the more reliable the simulation outcomes. However, even with accurate data, some level of deviation from real-world measurements is inevitable due to simplified assumptions and parameter estimates based on industry experience. Therefore, comparing simulation results with actual measurements is crucial for verifying accuracy and improving future simulations.
ZTE developed a dedicated tool to compare simulation and measured data, allowing statistical analysis of errors, standard deviations, probability distributions, and confidence intervals. These results are visually displayed on maps, offering objective evaluation of simulation accuracy. Key performance indicators like pilot strength (Ec) and pilot quality (Ee/Io) are commonly compared during analysis.
In practice, ZTE has applied simulation extensively in trial networks, contributing significantly to pre-planning and optimization phases. The comparison between simulation and field testing not only verifies the reliability of simulation but also helps refine techniques through repeated practice. For example, in one test network, ZTE used a propagation model expressed as:
Path_Loss = K1 + K2 log(d) + K3(Hms) + K4 log(Hms) + K5 log(Heff) + K6 log(Heff) log(d) + K7(Diffraction Loss) + Clutter_Loss
With K1-K7 values of 153.23, 40.23, -2.88, 0, -13.82, -6.55, and 0.8, respectively. The simulation results were compared with actual road test data, revealing a mean error of -3.45 dB and a standard deviation of 9.47 dB. These results show that the simulation closely aligns with real-world conditions, though some minor discrepancies exist due to environmental complexities.
Through continuous refinement of simulation parameters and propagation models, the accuracy of predictions can be further improved. In areas where discrepancies occur, using multiple propagation models or adjusting simulation settings based on localized data can enhance precision. Moreover, by analyzing error distributions across different road segments, adjustments can be made to reduce gaps between simulated and actual results, leading to more effective network planning and optimization.
In summary, the comparison between simulation and actual measurements is an ongoing, iterative process. It not only improves the accuracy of simulations but also supports network optimization by providing actionable insights. As ZTE continues to refine its methods, the role of simulation in wireless network development becomes increasingly significant, helping operators achieve better performance and return on investment.