A Review on Optimization Methods for Designing RF Power Amplifiers

Kouhalvandi, Lida; Ceylan, Osman; Özoğuz, Serdar

doi:10.23919/eleco47770.2019.8990396

Cited by 13 publications

(9 citation statements)

References 27 publications

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“…46 The number of simulations must be decreased to reduce time to market. 271 Bayesian optimization, space mapping, 272,273 combination of the evolutionary optimization approaches with deep learning methods, 274 and combination of coarse and fine models 275 are some of the methods that can accelerate the optimization process. These optimization methods can substantially reduce the computational design time and provide faster optimization duration than direct optimizations.…”

Section: Trading Off Between Accuracy and Speedmentioning

confidence: 99%

Overview of evolutionary algorithms and neural networks for modern mobile communication

Kouhalvandi

Shayea

Özoğuz

et al. 2022

Trans Emerging Tel Tech

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The sixth generation (6G) of mobile networks must support the huge growth of mobile connections and provides various intelligent services in future mobile networks. For that, designing high-performance network architecture and communication systems (CSs) as well as finding coherent solutions for the determined problems is critical demand that needs to be achieved in 6G networks.Optimal solutions are mainly sought by using modifiable, smart, and perceptive algorithms aimed at optimizing more specific tasks. Therefore, advanced optimization methods are highly required to accommodate the requirements of CSs efficiently. That will be in various parts of the future networks such as advanced mobility management, multi communication links, efficient power consumption, ultra-lower latency, ultra-security, high speed, and reliable connectivity.Accordingly, highly accurate and smart functions must be modeled to optimize the required communication parameters in the network. This study provides a comprehensive overview of optimization methods that may need further investigations and developments to be applied in 6G networks at various parts of networks. A detailed theoretical description for each method is presented and discussed to elucidate future research directions for optimizing specific characteristics with multi-objective optimizations. Moreover, this article illustrates the conceptual and structural viewpoints of reported optimization methods. Also, the capability of various optimization methods that can offer industrial solutions in 6G is discussed. The potential applications of each method are also analyzed. Finally, this article presented the research issues and future directions of optimization technology and research gaps that need to be addressed before the standardization of 6G networks. INTRODUCTIONRecently, innovative solutions of communication systems (CSs) have been developed impressively, as data traffic is increasing exponentially by more than 50% per year. 1 Several factors will contribute for increasing data demand massively, for example, as predicted by CISCO, the video will make up 82% of the all IP traffic by 2022. 2,3 This massive increase in data traffic will cause several new issues that will facing the implementation of future mobile networks. That will include a dramatic increase for wider spectrum need, 4 the necessity for big system capacity, 5 further mobility issues, 6,7 and higher energy consumption, 8 in which cannot be handled efficiently by the current cellular networks.

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Section: Trading Off Between Accuracy and Speedmentioning

confidence: 99%

Overview of evolutionary algorithms and neural networks for modern mobile communication

Kouhalvandi

Shayea

Özoğuz

et al. 2022

Trans Emerging Tel Tech

Self Cite

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“…For these reasons, optimizing analog and radio frequency circuits have a checkered history over the last years and have continued to find domination. In this study with combination of methods presented in [10], we provide a revival of interest in this area and summarize feasible solutions applied in various analog and RF circuit designs. Different methods proposed by the researchers are reviewed with clarifying the area of applications with the hope of providing a general perceptive on circuit designs.…”

Section: First Iteration Second Iteration Third Iterationmentioning

confidence: 99%

“…This work is focused on reviewing various optimizing techniques applied for designing complementary metaloxide-semiconductor (CMOS) analog and RF circuits and systems. In [10], some reliable optimization techniques for designing power amplifiers (PAs) [11,12]: as bayesian optimization [13], simplified real frequency technique (SRFT) [14], space mapping [15][16][17], neural network [18] and Padé approximation based modeling [19] are described clearly. We extend the study in [10] and explain further state-of-the-art optimization techniques used in the last decade.…”

Section: Introductionmentioning

confidence: 99%

“…In [10], some reliable optimization techniques for designing power amplifiers (PAs) [11,12]: as bayesian optimization [13], simplified real frequency technique (SRFT) [14], space mapping [15][16][17], neural network [18] and Padé approximation based modeling [19] are described clearly. We extend the study in [10] and explain further state-of-the-art optimization techniques used in the last decade. Table 1 summarizes various optimization methods applied in the domains of analog and microwave.…”

Section: Introductionmentioning

confidence: 99%

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Optimization techniques for analog and RF circuit designs: an overview

Kouhalvandi

Ceylan²,

Özoğuz

2020

Analog Integr Circ Sig Process

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Optimizations have gained much consideration from the researchers working in the domains of analog and radio frequency (RF), recently. Dealing with highly nonlinear behavior of active components and aiming to meet design specifications are common issues in all nonlinear circuit designs. As a consequence and accordingly, many studies have been conducted on diverse optimization methods and algorithms for tackling the design problems and meeting optimal solutions with high accuracy. The main purpose of this article is to provide a comprehensive and systematic literature review for the optimization approaches applied by the researchers for designing various analog and microwave circuits. We focus on considering the existing optimization methods from the newly published optimization methods in the last decade. Thus, this study can guide and enlighten complementary metal-oxide-semiconductor analog and RF microwave circuit designers to consider optimization methods commonly used in both areas and to expand conventional performance figures used in their area.

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“…In a transceiver system, the power amplifier is the most dissipative module, which consumes power from the system's battery. Hence, in order to extend the battery life in portable devices, it is imperative to design a power amplifier that demonstrates a high power efficiency [1][2][3][4][5]. Moreover, recently, the Federal Communications Commission (FCC) has also emphasized maximizing the battery life of the client device operating at the new unlicensed 6 GHz band (5.925 GHz to 7.125 GHz) [5].…”

Section: Introductionmentioning

confidence: 99%

A 6 GHz Integrated High-Efficiency Class-F−1 Power Amplifier in 65 nm CMOS Achieving 47.8% Peak PAE

Ali

Hasan

2021

Electronics

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This paper reports a “single-transistor” Class-F−1 power amplifier (PA) in 65 nm CMOS, which operates at the microwave center frequency of 6 GHz. The PA is loaded with a Class-F−1 harmonic control network, employing a new “parasitic-aware” topology deduced using a novel iterative algorithm. A dual-purpose output matching network is designed, which not only serves the purpose of output impedance matching, but also reinforces the harmonic control of the Class-F−1 harmonic network. This proposed PA yields a peak power-added efficiency (PAE) of 47.8%, which is one of the highest when compared to previously reported integrated microwave/millimeter-wave PAs in CMOS and SiGe technologies. The amplifier shows a saturated output power of 14.4 dBm along with an overall gain of 13.8 dB.

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A Review on Optimization Methods for Designing RF Power Amplifiers

Cited by 13 publications

References 27 publications

Overview of evolutionary algorithms and neural networks for modern mobile communication

Overview of evolutionary algorithms and neural networks for modern mobile communication

Optimization techniques for analog and RF circuit designs: an overview

A 6 GHz Integrated High-Efficiency Class-F−1 Power Amplifier in 65 nm CMOS Achieving 47.8% Peak PAE

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