Browsing by Autor "Hugo Orlando Condori Quispe"

Now showing 1 - 4 of 4

Design and Characterization of a 24 GHz Transceiver with Adaptative Power Control for 5 G mmWave Systems
(2025) Hugo Orlando Condori Quispe; Karel Walter Gomez Orellana; Alejandro Javier Jurado Morales; Juan Carlos Paredes Condori; Rodrigo Apaza Huanca
The progression towards 5 G communications in millimeter-wave (mmWave) bands imposes stringent requirements on the linearity and power stability of the radio frequency (RF) chain. This paper presents the design, modeling, and experimental characterization of a complete 24.2 GHz transceiver featuring a closed-loop power control system. The system employs a Software-Defined Radio (SDR) for the generation and demodulation of a 5 G waveform at a 5 GHz intermediate frequency (IF). Frequency conversion to the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{R F}$</tex> band is performed by a subharmonic mixer, which utilizes an internal frequency multiplier to generate a 24.2 GHz RF carrier from a 9.6 GHz local oscillator (LO) signal supplied by a synthesizer. The output power is monitored in real-time by an RMS power detector, the output of which feeds a digital control loop implemented in a microcontroller. Theoretical analysis of the mixing cascade, signal quality metric (EVM), and control algorithm is presented. Experimental results characterize the open-loop system performance, including the compression point and EVM degradation, and demonstrate the effectiveness of the control loop in maintaining a constant output power and ensuring linear operation against variations in input power and chain gain.
Integrated Power Detection Architecture for mmWave 5G Transmitter
(2023) Jorge Vallejos; Karel Walter Gomez Orellana; Hugo Orlando Condori Quispe
This article presents the architecture of an output power control subsystem integrated into the transmission chain of a 5G mmWave communication station. The subsystem incorporates a power amplifier, antenna system, directional coupler, and RMS power detector to enable real-time monitoring and voltage signal translation. The directional coupler design effectively samples the mmWave signal, while the power detector facilitates accurate average power estimation. Our simulation results validate the system’s potential for enhancing power management and communication performance.
Modelado del comportamiento de un amplificador de potencia para 5G utilizando Machine Learning
(2024) Miguel Angel Chiri Yupanqui; Hugo Orlando Condori Quispe
El propósito principal de esta investigación es modelar el comportamiento de un amplificador de radiofrecuencia (RF) mediante técnicas de machine learning. Para lograr este objetivo, utilizamos el software Advanced Design System (ADS) de Keysight, primero se obtienen los datos de gráficas relevantes, los cuales se transforman en datos tabulares. Estos datos son esenciales para el entrenamiento del modelo. Se emplea el intérprete de Python de ADS, para este propósito. Los resultados obtenidos muestran una notable concordancia con el comportamiento esperado del amplificador RF, lo que confirma la efectividad del enfoque propuesto. Este hallazgo no sólo valida la viabilidad de modelar amplificadores, sino que también sugiere la aplicabilidad de estas técnicas en el modelado de diversos sistemas electrónicos con un alto grado de precisión y fiabilidad.
Power and Linearity Optimization of a 24.2 GHz Transmitter Chain Through Behavioral Modeling and Look-Up Tables
(2025) Hugo Orlando Condori Quispe; Juan Carlos Paredes Condori; Karel Walter Gomez Orellana; Rodrigo Apaza Huanca; Alejandro Javier Jurado Morales
The optimization of the trade-off between power efficiency and linearity is a challenge in the design of millimeterwave (mmWave) transmitters for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{5 G}$</tex> systems. This paper presents a systematic methodology for experimental characterization and subsequent optimization of a 24.2 GHz transmit chain through the development of a predictive behavioral model. A multidimensional, automated sweep of the chain's key control parameters—intermediate frequency (IF) input power, mixer gain, and IF stage attenuation—is performed to exhaustively map the operational space. For each configuration point, the RF output power and Error Vector Magnitude (EVM) are empirically determined. The extensive dataset is then used to construct a multi-dimensional look-up table (LUT) that functions as an accurate, data-driven behavioral model of the system. This model facilitates the prediction of transmitter performance and the identification of optimal operating points that maximize output power subject to a specific linearity constraint (EVM) without necessitating manual, iterative tuning. The utility of the model as a powerful design-time optimization tool is demonstrated, effectively decoupling performance tuning from the constraints of real-time hardware implementation.