Learning based hyperbolic position bounding in wireless networks

One of the recent schemes that has been put forward to localize a node is Hyperbolic Position Bounding (HPB) [4]. This scheme uses the relative Received Signal Strength (RSS) obtained by a number of trusted nodes to determine the position of a transmitter. Utilizing the RSS values, HPB uses a probabilistic model to estimate the range of distance differences between receiver pairs and a transmitter. Then, these distance differences are used to construct hyperbolas that bound the transmitter with some degree of confidence. Due to shadowing effect and other environmental factors, not all of the receiver pairs in HPB perform at the same level. Therefore, we proposed a modification of HPB that improves its performance. Our proposed system is called Hyperbolic Position Bounding with Learning Ability (HPB-LA). It consists of two phases, a learning phase and an operational phase. In the learning phase the system uses real data to measure the accuracy of the receiver pairs. Then, it ranks the receiver pairs according to their accuracy. After that, it groups the receiver pairs in subsets, evaluates the performance of these subsets, and finally selects the subset that provides the highest accuracy. In the operation phase, the subset of receiver pairs that is identified in the learning phase is used to localize nodes.;We also developed a new heuristic for the transmitter Effective Isotropic Radiated Power (EIRP) range estimation and evaluated it with experimental data and simulation data. This proposed heuristic adopts the receiver pair-based concept. For each receiver pair that includes the Maximal RSS Receiver (MRR), our heuristic assumes that the transmitter is located between the MRR and the other receiver, and then uses the RSS values to determine the EIRP range used by each receiver.;We conducted an experiment to evaluate the performance of HPB-LA. Our analysis results from the experimental data show that HPB-LA can achieve a higher success rate compared to HPB. The evaluation of our proposed transmitter EIRP range estimation process using the experimental data shows that HPB and HPB-LA have experienced a large reduction in the candidate area size, where the candidate area is the area bounded by the hyperbolas that are constructed by the receiver pairs. The analysis from the simulation results show that for any number of receivers, our proposed heuristic always gives a smaller candidate area in comparison to the heuristic used in the original HPB.