Radio Network planning is the most important part of the whole network design owing to its proximity to mobile users. However, earlier radio network approaches failed to account for the right selection of training parameters for diverse environmental circumstances in radio communications networks, resulting in poor reliability and unreliable coverage. Hence, a novel Radio Network TETRA Path Loss Calculation by statistical Polynomial Kernel Radial Wavelet Network Models for RSSI Predication and Comparison in Undulating Area has been designed for TETRA path loss calculation by deterministic, empirical RSSI Predication and effectively select the parameters in different environment. In existing techniques, the parameter selection, such as radio wave path calculation, frequency, antenna heights, distance, and angle elevation, are not analyzed accurately. Hence, a novel technique, namely Polynomial Kernel Radial Wavelet Network (PKRWN), has been designed in which the attenuation clustering radio environment to estimate the value of path loss and radio telecommunication 5G network and provide statistical descriptions of the relationship between path loss and propagation parameters. Moreover, it suffers from low stability because the Received Signal Strength Indicator (RSSI) is easily blocked and easily interfered by objects, environmental effects, and climatic conditions. Hence, a novel technique, Arid-Terrain-Ridge Integrational Radio Sensor Network, has been designed to get good stability of RSSI in various environmental effects such as urban, suburban, rural, hilly, plain, and desert areas. Also, the Deterministic and empirical statistical approaches are used to estimate the field strength. As a result, it accurately estimates the appropriate parameters in radio telecommunication networks with various environments with good stability and predictions of RSSI.