Performance Evaluation of Carbon Nano Tube Field Effect Transistors based Content Addressable Memories

In modern wireless communication systems, reducing power consumption has been a top priority, specifically in the design of modern circuits that support emerging wireless devices and Internet of Things (IoT) technologies. Routing protocols progressively depend on stashed routing data keep in besides Static Random-Access Memory (SRAM) or Content Addressable Memory (CAM), the later present quick parallel search operations by differentiating input data straight with saved entries. CAM, perform comparably to the human brain by recover findings form on matter instead of address, is generally used in network routers, cache controllers, and lookup tables. Nevertheless, scheming low-power, high-performance CAM circuitry unwanted rigorous due to short-channel effects, leakage currents, and source-to-drain tunneling in nanoscale CMOS technologies. Carbon Nanotube Field Effect Transistors (CNTFETs) occur as a optimistic preference due to their near-ballistic transport, high mobility, and superior drive competence at nanometer scales. Adiabatic or energy-recovery logic beyond improves ability by diminishing dynamic power dissipation. In comparison to former research, this research develops optimised CNTFET parameters—number of tubes, chirality, pitch, and dielectric characteristics—and proposes an adiabatic CNTFET-based Binary CAM (BCAM) that appreciably enhances mean power and search delay equate to latest literature. Associated circuits such as decoders and priority encoders are also designed, revealing superior performance over CMOS counterparts. Moreover, an upgraded CNTFET-based Ternary CAM (TCAM) hiring Shorted-Gate and Independent-Gate CNTFETs is evolved and executed in a 4×4 array, demonstrating enriched mean power, peak power, and search delay metrics. General, the task carries high-performance CNTFET-driven BCAM and TCAM scheme capable for next-generation low-power applications.