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Field Programmable Gate Arrays (FPGA) Based Computational Complexity Analysis of Multicarrier Waveforms

C. Ajitha1,*, T. Jaya2

1 Department of ECE, University College of Engineering, Nagercoil, Tamilnadu, 629004, India
2 Department of ECE, CSI Institute of Technology, Thovalai, Tamilnadu, 629302, India

* Corresponding Author: C. Ajitha. Email: email

Intelligent Automation & Soft Computing 2022, 34(2), 1033-1048. https://doi.org/10.32604/iasc.2022.021984

Abstract

Multicarrier waveforms with enhanced spectral efficiency, low latency, and high throughput are required for 5G wireless networks. The Orthogonal Frequency Division Multiplexing (OFDM) method is well-known in research, but due to its limited spectral efficiency, various alternative waveforms are being considered for 5G systems. In the recent communication world, NOMA (non-orthogonal multiple access) plays a significant part due to its wider transmission of data with less bandwidth allocation. Even if a high data rate can be attained, the transmission problem will arise due to the spread of multiple paths. In order to reduce complexity and area utilization, a novel PL-based FWFT (Fast walsh hadamard fourier transform) technique is proposed and implemented in the VLSI architecture. To achieve a high-performance system, the main concept of pass transistor logic (PL) with VLSI implementation is to diminish the size and power consumption. Finally, the performance of the proposed FWFT/ IFWFT implementation has been evaluated. For FPGA’s 16-point FWFT, the number of transistors decreased by 21% and the total power required was reduced by 5.5%. The same implementation for 34 transistor-pass-logic customs and power consumption is 2.764 mW with a latency of 78.256 ns. As a consequence, the proposed system achieves low power, area and low complexity system that can enhance the function of the multicarrier waveform systems.

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Cite This Article

C. Ajitha and T. Jaya, "Field programmable gate arrays (fpga) based computational complexity analysis of multicarrier waveforms," Intelligent Automation & Soft Computing, vol. 34, no.2, pp. 1033–1048, 2022.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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