Proposed Title :

• FPGA Implementation of Large Integer Multiplication with using application of OFDM Transceiver and Receiver

Improvement of this Project:

• • Phase1:

    • To design complete OFDM with 8-QPSK Modulation with using NTT and 8-QPSK Demodulation with using INTT and shown the performance with compared to existing design of FFT and IFFT.

    Phase2:

    • Implement this OFDM of NTT and INTT method in VHDL and synthesized in Xilinx Software with Hardware Implementation using FPGA-X6LX9 and shown the output in ADC/DAC Interface.

Software implementation:

• Modelsim & Xilinx

Low-Complexity VLSI Design of Large Integer Multipliers for Fully Homomorphic Encryption

Proposed System : 

In a recent technology of digital communication system where as multiple carriers signal are used to transmit and received the data in the application of Orthogonal frequency division Multiplexing (OFDM). In a OFDM method of digital signal processing application will not support large integers values in all arithmetic operations. Here, we introduce a Fully Homomorphic encryption(FHE) algorithm to allows a computations in large integer multiplication, addition and division to be carried out directly on cipher texts for ensuring data privacy on un-trusted servers, thus attracting much attention for cloud computing applications. In this paper, we are focusing on the design and implementation on OFDM with using Large integer multiplication with using NTT (Number theoretic transform) and INTT(Inverse Number Theoretic transform) in Fig.2 will shown the basic diagram of complete OFDM Design with using NTT/INTT method. This FHE method will have various efficient schemes to tackle and carrying out large integer multiplication based on Schönhage – Strassen algorithm (SSA). This proposed method will designed in VHDL and synthesized in Xilinx FPGA-S6LX9, finally compared with existing OFDM Technique of FFT and IFFT Method and shown the compared terms of Area, Power and delay.

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Low-Complexity VLSI Design of Large Integer Multipliers for Fully Homomorphic Encryption

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