FPGA Implementation of Reconfigurable Modulation Scheme and Hamming Encoder for Cognitive Radio

FPGA Implementation of Reconfigurable Modulation Scheme and Hamming Encoder for Cognitive Radio

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© 2023 by IJETT Journal
Volume-71 Issue-3
Year of Publication : 2023
Author : M. A. Usha Rani, C. R. Prashanth
DOI : 10.14445/22315381/IJETT-V71I3P227

How to Cite?

M. A. Usha Rani, C. R. Prashanth, "FPGA Implementation of Reconfigurable Modulation Scheme and Hamming Encoder for Cognitive Radio," International Journal of Engineering Trends and Technology, vol. 71, no. 3, pp. 261-275, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I3P227

Abstract
Cognitive Radio (CR) is broadly accepted as a wireless communication technology because the CR minimizes the problem of bandwidth shortages by using idle spectrum. However, the development of the communication application of CR is vulnerable to noise and high resource consumption. This paper proposes the Reconfigurable Modulation Scheme (RMS) approach and the Hamming Encoder (HE) to improve communication over the CR. Instead of using Digital modulation techniques like QPSK, QAM and BPSK in the spectrum sensing, the RMS technique is used for less hardware utilization. These three modulation techniques (QPSK, QAM, and BPSK) are performed in a single RMS, whereas the HE is used to perform the error correction process. Here, the Field Programmable Gate Array (FPGA) based CR communication is developed RMS, and HE is developed by using the Xilinx ISE 14.2 software. The developed RMS-HE-FPGA architecture was also analysed by using a hardware development board, i.e., Spartan 6 FPGA. The performance of the RMS-HE-FPGA architecture is analyzed in terms of all aspects related to FPGA.

Keywords
Cognitive radio, Error correction process, Field programmable gate array, Hamming encoder, Hardware utilization, Reconfigurable modulation scheme.

References
[1] Mahesh S. Murty, and Rahul Shrestha “Hardware Implementation and VLSI Design of Spectrum Sensor for Next‐Generation LTE‐A Cognitive‐Radio Wireless Network,” IET Circuits, Devices & Systems, vol. 12, no. 5, pp. 542-550, 2018. Google Scholar | CrossRef | Publisher Link
[2] Ardalan Alizadeh, Hamid Reza Bahrami, and Mehdi Maleki, “Performance Analysis of Spatial Modulation in Overlay Cognitive Radio Communications,” IEEE Transactions on Communications, vol. 64, no. 8, pp. 3220-3232, 2016. Google Scholar | CrossRef | Publisher Link
[3] Rohit B. Chaurasiya, and Rahul Shrestha, “A New Hardware-Efficient Spectrum-Sensor VLSI Architecture for Data-Fusion-Based Cooperative Cognitive-Radio Network,” IEEE Transactions on Very Large-Scale Integration (VLSI) Systems, vol. 29, no. 4, pp. 760-773, 2021. Google Scholar | CrossRef | Publisher Link
[4] Bin Tang et al., “Digital Signal Modulation Classification with Data Augmentation Using Generative Adversarial Nets in Cognitive Radio Networks,” IEEE Access, vol. 6, pp. 15713-15722, 2018. Google Scholar | CrossRef | Publisher Link
[5] Xin Liu et al., “A Multichannel Cognitive Radio System Design and Its Performance Optimization,” IEEE Access, vol. 6, pp.12327-12335, 2018. Google Scholar | CrossRef | Publisher Link
[6] D. Damodaram, and T. Venkateswarlu, “FPGA Implementation of Genetic Algorithm to Detect Optimal User By Cooperative Spectrum Sensing,” ICT Express, vol. 5, no. 4, pp. 245-249, 2019. Google Scholar | CrossRef | Publisher Link
[7] C. S. Karthikeyan, and M. Suganthi, “Optimized Spectrum Sensing Algorithm for Cognitive Radio,” Wireless Personal Communications, vol. 94, no. 4, pp. 2533-2547, 2017. Google Scholar | CrossRef | Publisher Link
[8] Mingxuan Li et al., “Generative Adversarial Networks-Based Semi-Supervised Automatic Modulation Recognition for Cognitive Radio Networks,” Sensors, vol. 18, no. 11, p. 3913, 2018. Google Scholar | CrossRef | Publisher Link
[9] Rohit B. Chaurasiya, and Rahul Shrestha, “Fast Sensing-Time and Hardware-Efficient Eigenvalue-Based Blind Spectrum Sensors for Cognitive Radio Network,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 67, no. 4, pp.1296-1308, 2019. Google Scholar | CrossRef | Publisher Link
[10] E.Ganesan, and V.Sakthivel, "A Novel FPGA Design with Hybrid LUT / MUX Architecture," SSRG International Journal of Electronics and Communication Engineering, vol. 3, no. 11, pp. 6-8, 2016. Google Scholar | CrossRef | Publisher Link
[11] R.Belly Ballot, T.Anisley, and N.Addison, "Advanced Signal Recognition Method for Path Using FPGA," SSRG International Journal of VLSI & Signal Processing, vol. 4, no. 3, pp. 26-30, 2017.
CrossRef | Publisher Link
[12] Rugui Yao et al., “Intelligent Modulation Pattern Recognition Based on Wavelet Approximate Coefficient Entropy in Cognitive Radio Networks,” IEEE Access, vol. 8, pp. 226176-226187, 2020. Google Scholar | CrossRef | Publisher Link
[13] Xiaoyong Sun et al., “Modulation Classification Using Compressed Sensing and Decision Tree–Support Vector Machine in Cognitive Radio System,” Sensors, vol. 20, no. 5, p. 1438, 2020. Google Scholar | CrossRef | Publisher Link
[14] E.Gnana Manoharan, and K.Vadivelu, “CFD Technique-Based Spectrum Sensor for Hardware-Efficient and Fast Sensing of Cognitive Radio Network,” European Journal of Molecular & Clinical Medicine, vol. 7, no. 9, pp. 1770-1776, 2020. Google Scholar | Publisher Link
[15] Ms.Manjula B.M, and Dr.Chirag Sharma, "FPGA Implementation of BCG Signal Filtering Scheme by Using Weight Update Process," SSRG International Journal of VLSI & Signal Processing, vol. 3, no. 3, pp. 1-7, 2016. Google Scholar | CrossRef | Publisher Link
[16] S. N. Hemanth Kumar et al., “FPGA Implementation of Digital Modulation Schemes Using Verilog Hdl,” Turkish Journal of Computer and Mathematics Education (TURCOMAT), vol.12, no. 12, pp. 2442-2451, 2021. Google Scholar | Publisher Link
[17] A. Rajalakshmi, and A. Kavitha, “Suppression of EMI Using Cost-Effective FPGA-Based Digital Communication Modulation Techniques in Power Converters,” IETE Journal of Research, pp. 1-12, 2021. Google Scholar | CrossRef | Publisher Link
[18] Md Wahid Sadiq, and Md Ahasan Kabir., “Design and Implementation of Reconfigurable ASK and FSK Modulation and Demodulation Algorithm on FPGA (Field Programmable Gate Array),” Sensors International, vol. 3, pp. 100155, 2022. Google Scholar | CrossRef | Publisher Link
[19] Shanigarapu Nareshkumar, and Kalagadda Bikshalu, “Adaptive Absolute SCORE Algorithm for Spectrum Sensing in Cognitive Radio,” Microprocessors and Microsystems, vol. 69, pp. 43-53, 2019. Google Scholar | CrossRef | Publisher Link
[20] Rohit B. Chaurasiya, and Rahul Shrestha, “Hardware-Efficient and Fast Sensing-Time Maximum-Minimum-Eigenvalue-Based Spectrum Sensor for Cognitive Radio Network,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 66, no. 11, pp. 4448-4461, 2019. Google Scholar | CrossRef | Publisher Link
[21] Mohammad Khayyeri, and Karim Mohammadi, “Design and Implementation of a High-Performance and High-Speed Architecture for Wideband Spectrum Sensing in Cognitive Radio Networks,” Circuits, Systems, and Signal Processing, vol. 39, no. 4, pp. 2151-2177, 2020. Google Scholar | CrossRef | Publisher Link
[22] Penilop Parukutty Sanker et al., “Spectrum Shaping Using NC-OFDM for Cognitive Radio Applications,” IET Communications, vol. 14, no. 7, pp. 1120-1128, 2020. Google Scholar | CrossRef | Publisher Link
[23] C. Srinivasa Murthy, and K. Sridevi, “FPGA Implementation of High Speed-Low Energy RNS Based Reconfigurable-FIR Filter for Cognitive Radio Applications,” WSEAS Transactions on Systems and Control, vol. 16, pp. 278-293, 2021. Google Scholar | CrossRef | Publisher Link
[24] Rahul Sharma, Rahul Shrestha, and Satinder K. Sharma, “Hardware-Efficient and Short Sensing-Time Multicoset-Sampling Based Wideband Spectrum Sensor for Cognitrive Radio Network,” IEEE Transactions on Circuits and Systems, vol. 70, no. 3, pp. 1298-1310, 2023. Google Scholar | CrossRef | Publisher Link
[25] Tolga Keleş, Sıddıka Berna Örs Yalçın, and Yaşar Kemal Alp, “Model Based Design of Software Defined and Cognitive Radio and Implementation on FPGA,” Signal Processing and Communication Applications Conference (SIU), pp. 1-4, 2021. Google Scholar | CrossRef | Publisher Link
[26] Abderrezzaq Bouhdjeur, “Autonomous Global Threshold Adjustment Algorithm for Energy Detection in Self-Reconfigurable Cognitive Radio Systems,” International Conference on Advanced Electrical Engineering (ICAEE), pp. 1-5, 2022. Google Scholar | CrossRef | Publisher Link
[27] Qiang Li et al., “Interplay Between Reconfigurable Intelligent Surfaces and Spatial Modulation: New Appliocation Paradigms,” IEEE Wireless Communications, pp. 1-18, 2022. Google Scholar | CrossRef | Publisher Link
[28] Rinu C Varghese, and A. Amir, “Design of Computationally Efficient FRM Based Reconfigurable Filter Structure for Spectrum Sensing in Cognitive Radio for IoT Networks,” IEEE Humanitarian Technology Conference, pp. 281-287, 2022. Google Scholar | CrossRef | Publisher Link
[29] Mário Lopes Ferreira, and João Canas Ferreira, “Flexible and Dynamically Reconfigurable FPGA-Based FS-FBMC Baseband Modulator,” IEEE International Symposium on Circuits and Systems, pp. 1-5, 2018. Google Scholar | CrossRef | Publisher Link
[30] Mahesh S. Murty, and Rahul Shrestha, “Reconfigurable and Memory-Efficient Cyclostationary Spectrum Sensor for Cognitive Radio Wireless Networks,” IEEE Transactions on Circuits and Systems, vol.65, no.8, pp. 1039-1043, 2018. Google Scholar | CrossRef | Publisher Link
[31] D. Teguig, and M.S. Azzaz., “FPGA Implementation of Spectrum Sensing Methods for Cognitive Radio,” International Symposium on Networks Computer and Communications, pp. 1-5, 2018. Google Scholar | CrossRef | Publisher Link
[32] K.A. Arun Kumar., “FPGA Implementation of Spectrum Sensing Engine for Cognitive Radios,” International Conference on Networks and Advances in Computational Technologies, pp. 116-119, 2017. Google Scholar | CrossRef | Publisher Link
[33] Ramya R, and Madhura R, "FPGA Implementation of Optimized BIST Architecture for Testing of Logic Circuits," SSRG International Journal of VLSI & Signal Processing, vol. 7, no. 2, pp. 36-42, 2020.
CrossRef | Publisher Link
[34] Mohammad Khayyeri, and Karim Mohammadi, “Cooperative Wideband Spectrum Sensing in Cognitive Radio Based on Sparse Real-Valued Fast Fourier Transform,” IET Communications, vol. 14, no. 8, pp. 1340-1348, 2020. Google Scholar | CrossRef | Publisher Link
[35] Rohit B. Chaurasiya, and Rahul Shrestha, “Area-Efficient and Scalable Data-Fusion Based Cooperative Spectrum Sensor for Cognitive Radio,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 68, no. 4, pp. 1198-1202, 2020. Google Scholar | CrossRef | Publisher Link
[36] Sumin D. Joseph et al., “UWB Sensing Antenna, Reconfigurable Transceiver and Reconfigurable Antenna Based Cognitive Radio Test Bed,” Wireless Personal Communications, vol. 96, no. 3, pp. 3435-3462, 2017. Google Scholar | CrossRef | Publisher Link