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On the intelligent components geometry design of a current reuse folded cascode concurrent dual-band CMOS LNA

机译:电流复用折叠共源共栅双频CMOS LNA的智能组件几何设计

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In this paper, an optimized design procedure based on evolutionary algorithms for automatic synthesis of a current reuse folded cascode dual-band concurrent fully integrated low-noise amplifiers (LNA) targeted to 802.16d @ 3.5GHz and 802.11b, g @ 2.4GHz standards is discussed. Algorithm is intended to compute the circuit elements geometry and bias levels capable of maintaining the best level of gain, input matching, output matching and power consumption. The genetic algorithm optimization engine is developed in MATLAB environment and performance evaluation in 0.18μm RF CMOS TSMC technology is ceded to HSPICE. Results indicate that the automated scheme well renders the desired circuit in an acceptable computation time, otherwise, either tremendous manual trial and errors or an astronomical cycles of exhaustive search is required.
机译:在本文中,基于进化算法的优化设计程序可自动合成针对802.16d @ 3.5GHz和802.11b,g @ 2.4GHz标准的电流复用折叠共源共栅双频并发完全集成低噪声放大器(LNA)讨论。算法旨在计算能够保持最佳增益水平,输入匹配,输出匹配和功耗的电路元件的几何形状和偏置水平。在MATLAB环境下开发了遗传算法优化引擎,并将HSPICE转换为0.18μmRF CMOS TSMC技术的性能评估。结果表明,该自动化方案可以在可接受的计算时间内很好地呈现所需的电路,否则,将需要大量的人工尝试和错误,或者需要详尽的天文搜索周期。

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