SDR Based Modulation Performance of RF Signal under Different Communication Channel
Keywords:Bit error rate, receiver operation, RF signal, signal noise ratio, transmitter, wireless channel
Hardware components are an integral part of Hardware Define Radio (HDR) for seamless operations and optimal performance. On the other hand, Software Define Radio (SDR) is a program that does not rely on any hardware components for its performance. Both of the latter radio programmers utilize modulation functions to make their core components from signal processing viewpoint. The following paper concentrates on SDR based modulation and their performance under different modulations. The bit error rate (BER) of modulations such as PSK, QAM, and PSAM were used as indicators to test channel quality estimation in planar Rayleigh fading. Though it is not commonly used for channel fading, the method of the adder determines the regionally segmented channel fading. Thus, the estimation error of the channel change substantially reduces the performance of the signal, hence, proving to be an effective option. Moreover, this paper also elaborates that BER is calculated as a function of the sample size (signal length) with an average of 20 decibels. Consequently, the size of the results for different modulation schemes has been explored. The analytical results through derivations have been verified through computer simulation. The results focused on parameters of amplitude estimation error for 1dB reduction in the average signal-to-noise ratio, while the combined amplitude deviation estimation error results are obtained for a 3.5 dB reduction.
O. Popescu, S. El-Tawab, S. Abraham, and S. Abraham, “A mobile platform using software defined radios for wireless communication systems experimentation,” ASEE Annual Conference & Exposition, Columbus, Ohio, pp. 1-12, 2017.
Z. Zhang, L. Xiao, X. Su, J. Zeng, and X. Xu, “A channel estimation method based on the improved LMS algorithm for MIMO-OFDM systems,” 12th International Symposium on Medical Information and Communication Technology (ISMICT), 2018. doi:10.1109/ismict.2018.8573728.
M. F. Flanagan and A. D. Fagan, “Iterative channel estimation, equalization, and decoding for pilotsymbol assisted modulation over frequency selective fast fading channels,” IEEE Transactions on Vehicular Technology, vol. 54, no. 4, pp. 1661- 1670, 2007.
H. Ning, H. Liu, and Y. Zhang, “Scalable and distributed key array authentication protocol in radio frequency identification-based sensor systems,” IET Communication, vol. 5, no. 12, pp. 1755-1768, 2011.
M.-D. Kim, J. Lee, J. Liang, and J. Kim, “Multipath channel characteristics for propagation between mobile terminals in urban street canyon environments,” 17th International Conference on Advanced Communication Technology (ICACT), 2015. doi: 10.1109/icact.2015.72249179/eusipco.2016.77606 75.
P. Zetterberg and R. Fardi, “Open source SDR front end and measurements for 60-GHz wireless experimentation,” IEEE Access, vol. 3, pp. 445- 456, 2015.
M. Chiani, E. Milani, and R. Verdone, “Optimization for weighed cooperative spectrum sensing in cognitive radio network,” Applied Computational Electromagnetic Society (ACES) Journal, vol. 26, no. 10, pp. 800-914, 2011.
J. Dai, “Bit-error-rate analysis of raptor codes over rician fading channels,” Journal of Electrical and Computer Engineering, vol. 2020, 2020. doi.org/ 10.1155/2020/2685075.
M. Abirami and A. Vimala, “A review of various antenna design methods for cognitive radio application,” 4 th International Conference on Electronics and Communication Systems, (ICECS), 2017. doi:10.1109/ecs.2017.8067850.
C. Schuler, “Research on correction algorithm of propagation error in wirelesssensor network coding,” EURASIP Journal on Wireless Communications and Networking, vol. 1, 2020.
H. Katiyar and R. Bhattacharjee, “Average capacity and signal-to-noise ratio analysis of multiantenna regenerative cooperative relay in Rayleigh fading channel,” IET Communication, vol. 5, no. 14, pp. 1971-1977, 2011.
S. Ohno and G. B. Giannakis, “Average-rate optimal PSAM transmissions over time-selective fading channels,” IEEE Transactions on Wireless Communications, vol. 1, no. 4, pp. 712-720, 2002.
M. C. Valenti and B. D. Woerner, “Iterative channel estimation and decoding of pilot symbol assisted turbo codes over flat-fading channels,” IEEE Journal on Selected Areas in Communications, vol. 19, no. 9, pp. 1697-1705, 2001.
S. J. Lee, W. Kang, and J. Seo, “Performance enhancement of OFDM-SQ2AM in distorted channel environments,” IEICE Electronics Express, vol. 7, no. 14, pp. 1020-1026, 2010.
S. Bernard, Digital Communications: Fundamentals and Applications. Prentice-Hall, 2nd Edition, pp. 30-33, 2001.
Y. Li, Y. Wang, and T. Jiang, “Norm-adaption penalized least mean square/fourth algorithm for sparse channel estimation,” Signal Processing, vol. 128, pp. 243-251, 2016. doi:10.1016/j.sigpro.2016. 04.003.
G. A. Ellis, “Wireless propagation in non line ofsight urban areas using uniform theory of diffraction,” Applied Computational Electromagnetic Society (ACES) Journal, vol. 18, no. 3, pp. 162-171, Nov. 2003.
Y. Zhang, S. B. Gelfand, and M. P. Fitz, “Soft-output demodulation on frequency selective Rayleigh fading channels using AR channel models,” IEEE Transactions on Communications, vol. 55, no. 10, pp. 1929-1939, 2007.