In the received signal strength-based ranging algorithms, distance is estimated from a path loss model, in which the path loss exponent is considered a key parameter. The conventional RSS-based algorithms generally assume that the path loss exponent is known a priori. However, this assumption is not acceptable in the real world because the channel condition depends on the current wireless environment. In this paper, we propose an accurate estimation method of the path loss exponent that results in minimizing distance estimation errors in varying environments. Each anchor node estimates the path loss exponent for its transmission coverage by the sequential rearrangement of the received signal strengths of all sensor nodes within its coverage. Simulation results show that the proposed method can accurately estimate the actual path loss exponent without any prior knowledge and provides low distance estimation error.

Transmission power control (TPC) is an important aspects of underlay transmission in the cognitive radio (CR) networks since it is able to avoid the extra interference from secondary transmission which can let the CR user coexist with the primary systems around. However, due to the different coverage of the primary signal and CR signal, combined with the complexity of the wireless communication, the scanning CR transmitter may not detect the existence of the primary systems. It will cause inaccurate TPC which will severely disrupt the primary service. In this letter, we propose a dynamic neighbor coordinated power control scheme that can avoid the misdetection of the primary signal and provide relatively accurate TPC related distance estimation. Simulation results show that the proposed scheme greatly reduces interference to the primary systems while enhancing overall CR network throughput.