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摘要: 随着信息产业和相关无线电通信业务的不断发展，频谱管理问题将更具挑战性。合适的频谱管理方法使得发射机有效地重复利用频率，用户设备(UE)可以选择最佳的基站。电磁环境地图(REM)概念作为解决频谱稀缺性和提高频谱利用率的工具，使不同的用户有效地共享频谱资源。电磁环境地图正在成为越来越普及的干扰管理和资源分配方法。构建电磁环境地图并不需要昂贵和耗时的调查或复杂的校准过程。给出了Shepard插值技术，并在某些方面对其进行改进，从而构建精确的电磁环境地图。此外，通过均方根误差(RMSE)作为性能度量，对测量值的数量和分布的影响进行分析比较。仿真结果表明，通过迭代聚类采样和优化的Shepard插值技术，并增加测量次数，从均方根误差的性能指标角度出发，能获得最精确的电磁环境地图。Abstract: The increased development of information industry and relevant radio communication services is making the spectrum management problem more challenging to solve. A suitable spectrum management method enables transmitters to reuse the frequency efficiently and the user equipment (UE) can select the optimum base station. The radio environment map (REM) concept has been proposed as a tool to solve spectrum scarcity and improve spectrum utilization, making different users share spectrum resource efficiently. The REMs are becoming an increasingly popular method for interference management and resource assignment. The reason for this is that REMs can be constructed without the need for surveys or complex calibration processes which are costly and time consuming. This paper gives Shepard interpolation techniques and modifies it in some respects for estimating radio environments with a limited number of measurement data, thus constructing accurate REMs. Additionally, it presents our systematic investigation of the impact of the number and distribution of measurements using the averaged root mean square error (RMSE) as the performance metric. Simulation results show that increasing the number of measurements with the clustering sampling and the modified Shepard interpolation technique, the most accurate REM is obtained in terms of the performance metric RMSE. And the interpolation accuracy can be improved by almost 14 dB with the modified method, which proves that our approach can effectively determine sharing conditions of radio spectrum use both in time and space.
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Figure 3. The real-time data collection equipment used in the measurements, with the transmitter, antenna and spectrum analyzer visible
Figure 4. RMSE with three sampling categories for (a) classic Shepard interpolation and (b) modified Shepard interpolation
Figure 6. REMs by (a) classic Shepard interpolation and (b) modified Shepard interpolation
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