Mass-Market Receiver for Static Positioning: Tests and Statistical Analyses

Nowadays, there are several low cost GPS receivers able to provide both pseudorange and carrier phase measurements in the L1band, that allow to have good realtime performances in outdoor condition. The present paper describes a set of dedicated tests in order to evaluate the positioning accuracy in static conditions. The quality of the pseudorange and the carrier phase measurements let hope for interesting results. The use of such kind of receiver could be extended to a large number of professional applications, like engineering fields: survey, georeferencing, monitoring, cadastral mapping and cadastral road. In this work, the receivers performance is verified considering a single frequency solution trying to fix the phase ambiguity, when possible. Different solutions are defined: code, float and fix solutions. In order to solve the phase ambiguities different methods are considered. Each test performed is statistically analyzed, highlighting the effects of different factors on precision and accurac

User Effects on Mobile Phone Antennas: Review and Potential Future Solutions

This paper explores the significant impact of human proximity on antenna design evolutionin mobile communication from GSM to LTE and future 5G technologies. It offers a comprehensive viewof the challenges posed by human interactions in current antenna designs, alongside modern solutions tomitigate these issues. Central to our study is the crucial role of extensive data acquisition in enabling AI-driven methodologies. We emphasize the need for diverse and comprehensive datasets to refine AI models.Our research demonstrates notable achievements, with our deep neural network-based models reaching upto 90% accuracy in radiation pattern classification and 87.5% in angular delay profile categorization.These results underscore our proficiency in incorporating AI into antenna engineering. We trace thehistorical trajectory of user-induced antenna challenges and their current implications, illustrating a coherentprogression. This narrative underscores the parallel evolution of antenna designs and user interactions,enhanced by our advanced model classification techniques. Our work presents an efficient method toaddress user effects using cutting-edge machine learning algorithms. (PDF) User Effects on Mobile Phone Antennas: Review and Potential Future Solutions. Available from: https://www.researchgate.net/publication/375926643_User_Effects_on_Mobile_Phone_Antennas_Review_and_Potential_Future_Solutions [accessed Nov 28 2023].This paper explores the significant impact of human proximity on antenna design evolution in mobile communication from GSM to LTE and future 5G technologies. It offers a comprehensive view of the challenges posed by human interactions in current antenna designs, alongside modern solutions to mitigate these issues. Central to our study is the crucial role of extensive data acquisition in enabling AI-driven methodologies. We emphasize the need for diverse and comprehensive datasets to refine AI models. Our research demonstrates notable achievements, with our deep neural network-based models reaching up to 90% accuracy in radiation pattern classification and 87.5% in angular delay profile categorization. These results underscore our proficiency in incorporating AI into antenna engineering. We trace the historical trajectory of user-induced antenna challenges and their current implications, illustrating a coherent progression. This narrative underscores the parallel evolution of antenna designs and user interactions, enhanced by our advanced model classification techniques. Our work presents an efficient method to address user effects using cutting-edge machine learning algorithms.</p