Design a low-noise 5GHz wideband microwave power amplifier using 90nm CMOS technology with area reduction employing an active inductor

Abstract

Systems that rely on wireless technology frequently use radio frequency integrated circuits (RFICs). Modern wireless communication systems rely heavily on low-noise amplifiers, particularly those operating in the 5 GHz frequency spectrum using 90nm technology. Improving the performance of 5 GHz low-noise amplifiers is the goal of research into these devices, which tries to solve problems with noise, gain, and power efficiency. When designing better, more efficient, and more balanced wireless communication systems, low-noise amplifiers are a must-have component. This research study introduces a 5 GHz wideband low-noise amplifier (LNA) for 5G Wi-Fi applications. A 1.2 V power source powers it. The circuit features an optimized common source topology to lower the noise figure, which in turn increases the voltage gain and reduces power consumption. To ensure that the circuit is compatible with the source impedance, methods such as inductive source decomposition and single-stage common source decomposition are employed. The mathematical analytical method was incorporated into the design process and served as its fundamental element. The results showed that with a transistor width of 165 μm and a current flowing through the circuit of 4 mA,(NF = 1.266) a gain of 18.493 dB S (2,1) and a power consumption of 4.8 mw were achieved. In terms of achieving a balance between the results of noise and gain, we were unable to accomplish the essence of the design process through mathematical analysis. Since a satisfactory outcome cannot be achieved through mathematical analysis, we optimise using the genetic algorithm. This method is known for its high efficiency in establishing a gain-noise balance and yields effective optimization solutions. We got these results: With an NF of 1.308 and an ideal power usage of 2.64 mW, we achieved an optimal gain of 27.21 dB(S2, 1). Our results show that evolutionary algorithms greatly improve LNA performance by pointing to the best settings for maximizing gain and reducing noise. Lastly, this work illustrates how genetic algorithm optimization has drastically changed LNA design. Engineers can accomplish RF signal amplification feats never seen before by integrating state-of-the-art computational tools and modelling methodologies. Since these methods successfully satisfy the demanding requirements of modern wireless communication systems, the findings indicate that RFIC technology is heading in the right direction