Keywords: 
• spectrum management /
• radio environment map /
• modified spatial interpolation algorithm /
• root mean square error

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.