Use of symbolic performance models in layout-inclusive RF low noise amplifier synthesis

Ranjan, Madhu; Bhaduri, Amitava; Verhaegen, Wim; Mukherjee, Bhaskar; Vemuri, Ranga; Gielen, G.; Pacelli, A.

doi:10.1109/bmas.2004.1393995

Cited by 15 publications

(10 citation statements)

References 11 publications

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“…Stochastic optimization routines based on simulated annealing [23], particle swarm optimization [24], or evolutionary algorithms [25], while eventually converging to near-optimum solutions, require significant simulation time for problems with nonlinear constraints. Consequently, these algorithms are appropriate for complex optimization problems with noisy objective and constraint functions with many local minima or discrete design variables.…”

Section: B Single-objective Lna Optimizationmentioning

confidence: 99%

Expression of Concern: Hierarchical Optimization Methodology for Wideband Low Noise Amplifiers

Nieuwoudt

Ragheb

Massoud

2007

2007 Asia and South Pacific Design Automation Conference

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In this paper, we present a systematic synthesis methodology for fully integrated wideband low noise amplifiers that simultaneously optimizes impedance matching, noise figure, and other performance parameters. Leveraging an accurate analytical model, we hierarchically couple global optimization techniques with local convex optimization methods to efficiently locate optimal wideband LNA circuits. The results indicate that the methodology yields significant improvement in key LNA design constraints over existing methodologies while achieving up to one order of magnitude speedup in computational performance.

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Section: B Single-objective Lna Optimizationmentioning

confidence: 99%

Expression of Concern: Hierarchical Optimization Methodology for Wideband Low Noise Amplifiers

Nieuwoudt

Ragheb

Massoud

2007

2007 Asia and South Pacific Design Automation Conference

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“…They appear when num assumes values close to zero. On the other hand, negative peaks of IIP2 are due to peaks of num 4 .…”

Section: Performance Figures Via Surrogate Modelsmentioning

confidence: 99%

“…To compute circuit performances in the optimization loop, the former category of tools calls a commercially available circuit simulator, such as Spectre or Hspice. The second category includes a builtin performance evaluation module based on a symbolic performance model of the circuit [4], [6], [2]. Although symbolic models enable a faster evaluation of performances than circuit simulations, their accuracy is lower.…”

Section: Introductionmentioning

confidence: 99%

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Forward and Reverse Modeling of Low Noise Amplifiers Based on Circuit Simulations

Tommasi

Rommes

Beelen

et al. 2011

Lecture Notes in Electrical Engineering

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Forward and reverse modeling of RF circuit blocks are useful approaches in design space exploration. The underlying idea of forward modeling is the creation of accurate surrogate models, which can be used to predict the circuit performances replacing (expensive) circuit simulations. On the other hand, reverse modeling concerns multiobjective optimization to explore relevant trade-offs between performances. This paper provides a discussion of application of surrogate models and multiobjective optimization to narrow-band low noise amplifier design. We discuss numerical difficulties encountered when the forward model is derived by using surrogate models of low noise amplifier admittances to compute performance figures via analytical equations. Afterward, we provide an example where direct performace modeling leads to a more accurate result even when the simplest surrogate model type (a lookup table) is used. Finally, a detailed tutorial of the normal boundary intersection optimization method is provided.

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“…Stochastic single objective and multi-objective optimization routines based on simulated annealing [8], particle swarm optimization [9] or evolutionary algorithms [10], while eventually converging to near-optimum solutions, require significant simulation time for problems with nonlinear constraints. Consequently, these algorithms are appropriate for complex optimization problems with many local minima or discrete design variables.…”

Section: Introductionmentioning

confidence: 99%

Soc-Nlna

Nieuwoudt

Ragheb

Massoud

2006

Proceedings of the 43rd Annual Conference on Design Automation - DAC '06

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In this paper we present SOC-NLNA, a systematic synthesis methodology for fully integrated narrow-band CMOS Low Noise Amplifiers (LNA) in high performance System-on-Chip (SoC) designs. SOC-NLNA is based on deterministic numerical nonlinear optimization and the Normal Boundary Intersection (NBI) method for Pareto optimization. To enable SoC integration, we simultaneously optimize both devices and passive components to yield integrated inductor values that are significantly less than those generated by traditional design techniques. When the synthesized LNAs are simulated using Cadence SpectreRF, SOC-NLNA yields up to 35 and 58 percent improvement in noise figure and gain. Leveraging the efficiency of our methodology, we are able to generate the Pareto surfaces between LNA performance metrics in seconds.

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Use of symbolic performance models in layout-inclusive RF low noise amplifier synthesis

Cited by 15 publications

References 11 publications

Expression of Concern: Hierarchical Optimization Methodology for Wideband Low Noise Amplifiers

Expression of Concern: Hierarchical Optimization Methodology for Wideband Low Noise Amplifiers

Forward and Reverse Modeling of Low Noise Amplifiers Based on Circuit Simulations

Soc-Nlna

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