Self-orientation of directional antennas, assisted by mobile robots, for receiving the best wireless signal strength

A Multi-Sensor RSS Spatial Sensing-Based Robust Stochastic Optimization Algorithm for Enhanced Wireless Tethering

“…The role of the RSS has been significant in most of the research in wireless communication performance optimization. Much research has been done on using the RSS in multi-robot wireless tethering and wireless localization [ 19 , 22 , 23 , 25 ]. In [ 22 ], a data-driven probabilistic model is used for RSS-based localization and wireless tethering algorithms.…”

“…In this paper, we borrow the concepts from [ 16 , 17 , 23 , 27 ] while intending to remove the hurdles and drawbacks observed in these state-of-the-art methods. The proposed method is novel in the following way compared to the state of the art (which also shows how we depart from others): no prior knowledge or model of the radio environment is required; a combination of spatial and temporal pre-processing techniques is used to deal with the measurement noise and stochastic nature of the RSS and to mitigate fading effects; multiple receivers spatially distributed on-board the relay node are used instead of using multiple antennas connected to the same receiver, therefore avoiding the need to switch between different antennas connected to the same receiver and also making the algorithm applicable directly at the application layer.…”

“…A fundamental attribute of the stochastic optimization algorithm is the 2D RSS gradient vector , which can be estimated using spatially-distributed RSS measurements from sensors on-board the relay robot. As our intention is to provide a sampling method that is both simple to implement (in different hardware platforms) and reliable to guarantee performance, we make use of multiple wireless transceivers as sensors to enhance reliability and redundancy in wireless networking and implicitly use the concept of multi-sensor spatial diversity to measure RSS gradients instead of methods, such as the least squares gradient estimation (LSGE) method [ 16 , 19 ], search-based methods [ 46 ] and multi-antenna spatial diversity techniques [ 20 , 23 , 27 ].…”

Using Mobile Robots to Establish Mobile Wireless Mesh Networks and Increase Network Throughput

“…We have then established several assumptions as follows. International Journal of Distributed Sensor Networks The second assumption may differ from the real world application, because the RSSI values are not often proportional to the distance between the two nodes due to the ever-changing RSSI patterns [2]. However, in the Friis transmission formular (2), if we assume antenna gains G R and G T are equal to 1 and the loss factor also equals 1, then the power level of received signal P R can be approximated as a function of distance r between the two nodes as a domination factor affecting its value P R /P T ≈ 1/4πr 2 :…”

Received signal strength indicator‐based decentralised control for robust long‐range aerial networking using directional antennas

“…By fusing real‐time RSSI information, the estimation accuracy and robustness of UAV flight state and directional antenna headings can be significantly improved in GPS unstable and denied environment. A few studies have been conducted on RSSI measurement and RSSI‐based localisation [15, 16]. For instance, an RSSI‐based UAV trajectory control algorithm was developed in [15] to localise a stationary source.…”