Path Loss Exponent Estimation for Indoor Wireless Sensor Positioning

Abstract

Rapid developments in wireless sensor networks have extended many applications, hence, many studies have developed wireless sensor network positioning systems for indoor environments. Among those systems, the Global Position System (GPS) is unsuitable for indoor environments due to Line-Of-Sight (LOS) limitations, while the wireless sensor network is more suitable, given its advantages of low cost, easy installation, and low energy consumption. Due to the complex settings of indoor environments and the high demands for precision, the implementation of an indoor positioning system is difficult to construct. This study adopts a low-cost positioning method that does not require additional hardware, and uses the received signal strength (RSS) values from the receiver node to estimate the distance between the test objects. Since many objects in indoor environments would attenuate the radio signals and cause errors in estimation distances, knowing the path loss exponent (PLE) in an environment is crucial. However, most studies preset a fixed PLE, and then substitute it into a radio propagation loss model to estimate the distance between the test points; such method would lead to serious errors. To address this problem, this study proposes a Path Loss Exponent Estimation Algorithm, which uses only four beacon nodes to construct a radio propagation loss model for an indoor environment, and is able to provide enhanced positioning precision, accurate positioning services, low cost, and high efficiency.

Practical Aspects for the Integration of 5G Networks and IoT Applications in Smart Cities Environments

“…PLE has a significant impact on the quality of the transmission links. In the far field region of the transmitter, if PL(d 0 ) is the path loss measured in dB at a distance d 0 from the transmitter, then the loss in signal power expected when moving from distance d 0 to d (d>d 0 ) is [88][89][90] is Figure 15. Usually PLE is considered to be known upfront but in most instances PLE needs to be assessed for the case at hand.…”

“…PLE estimation is achieved by comparing the observed values over a sample of measurements to the theoretical values. Obstacles absorb signals, thus treating the PLE as a constant is not an accurate representation of the real environments, both indoors and outdoors (for example treating PLE as a constant which may cause serious positioning errors in complicated indoor environments [88]). Usually to model real environments the shadowing effects cannot be overlooked, by taking the PLE as a constant (a straight-line slope).…”

GPS-Assisted Path Loss Exponent Estimation for Positioning in IEEE 802.11 Networks

“…Next, we shall review works which estimate PLE for WLAN in indoor environments. Authors in [30] proposed and implemented a system framework which consists of a central server, a base station, and four beacon nodes. The algorithm dynamically estimates a PLE between the beacons and the blind node.…”

Positioning Scheme Based on Iterative Path-Loss Exponent Estimation in WSNs

“…세 앵커들로 구성된 삼각형 내부에 존재하는 지 여 부를 판단하도록 하는 APIT [4] 알고리즘과 앵커로부 터의 홉 거리 정보를 이용하는 DV-hop [5] 정을 통한 위치 추정방법들 [7,8] Step 1) 그림4 과 같이 센서 노드  는 초기에 …”