Carbon Nanotube Based Variation Tolerant Low Power Cache Memory for 5G Networks

Abstract

The overall performance of any integrated circuit is defined by its proper memory design, as it is a mandatory and major block which requires more area and power. The prime interest of this article is to design a memory structure which is tolerant to variations in CNFET (Carbon nanotube field effect transistor) parameters like pitch, diameter and number of CNT tubes, and also offer low power and high speed of operation. In this context, CNFET based stacked SRAM (Static random access memory) design is proposed to attain the above mentioned criteria. Concept of stack effect is utilized in the cross coupled inverter section of the memory structure to attain low power. The power, speed and energy analysis for the proposed structure is done, and compared with the conventional structures to justify the proposed memory cell performance. HSPICE simulation results has confirmed that the proposed structure offers about 34%, 54% and 95% power saving in hold mode, read mode and write mode respectively. In speed and energy point of view it provides about 97% read delay, 92% write delay and 98% energy savings than the conventional memory structures. These results make it clear that the proposed SRAM is suitable for the 5G networks where circuit speed, power and energy consumption are the major concern.

Keywords

• carbon nanotube (cnt)
• cnfet
• sram
• low power
• vlsi
• 5g networks.