An improved framework for sums of Gaussian-class random variables with applications to radar and communication systems

• Grant number: 21/03923-9
• Support type: Scholarships in Brazil - Post-Doctorate
• Effective date (Start): September 01, 2021
• Effective date (End): August 31, 2023
• Field of knowledge: Engineering - Electrical Engineering - Telecommunications
• Principal researcher: José Cândido Silveira Santos Filho
• Grantee: Fernando Darío Almeida García
• Home Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

In radar and communication systems, the radio signal experiences random fluctuations caused by various factors and phenomena, such as the displacement between transmitter and receiver, objects and topographical elements obstructing the signal path, absorption, reflection, refraction, and diffraction. These signal fluctuations can greatly degrade the system performance. In order to capture the random behavior of the received signal, one can treat the communication link as a stochastic process, in which each signal sample is modeled as a Random Variable (RV) characterized by its Probability Density Function (PDF) and Cumulative Distribution Function (CDF). Specialized signal-processing techniques are employed to alleviate those random signal fluctuations, relying usually on sums of multiple signal replicas.Therefore, the statistical analysis of sums of RVs plays a pivotal role in the performance evaluation of many wireless applications. Unfortunately, the exact analytical assessment of these sum statistics may be rather cumbersome or, in some cases, too demanding to be executed. Most solutions available are time-consuming and prone to convergence and instability problems, if not infeasible, as the number of RVs increases. Hence, the search for faster, more tractable exact solution frameworks remains an appealing open problem. In this postdoctoral research project, we help to fill that gap. Specifically, we will obtain exact analytical expressions for the PDF and CDF of sums of so-called Gaussian-class RVs. This class of RVs comprises the best candidate distributions for modeling radio links in next-generation wireless networks and modern radar systems. Based on the sum statistics derived, we will also obtain corresponding analytical expressions for key performance metrics of those systems and networks. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

ALMEIDA GARCIA, FERNANDO DARIO; CARVAJAL MORA, HENRY RAMIRO; OROZCO GARZON, NATHALY VERONICA. ovel Expressions for Ricean Sum Distributions and Densitie. IEEE COMMUNICATIONS LETTERS, v. 25, n. 11, p. 3513-3517, NOV 2021. (21/03923-9)