Comparison of Various Modulations in TS-LMS-based TDS-OFDM Frame Structure for Channel Estimation in Digital Terrestrial Television Broadcasting Systems
Comparison of Various Modulations in TS-LMS-based TDS-OFDM Frame Structure for Channel Estimation in Digital Terrestrial Television Broadcasting Systems |
||
 |
 |
|
| © 2023 by IJETT Journal | ||
| Volume-71 Issue-6 |
||
| Year of Publication : 2023 | ||
| Author : Ghanshyamkumar Sah, Mehul Shah, Rukmi Chavda |
||
| DOI : 10.14445/22315381/IJETT-V71I6P202 | ||
How to Cite?
Ghanshyamkumar Sah, Mehul Shah, Rukmi Chavda, "Comparison of Various Modulations in TS-LMS-based TDS-OFDM Frame Structure for Channel Estimation in Digital Terrestrial Television Broadcasting Systems," International Journal of Engineering Trends and Technology, vol. 71, no. 6, pp. 8-15, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I6P202
Abstract
In various wireless communication applications, such as digital television terrestrial broadcasting (DTTB), orthogonal frequency division multiplexing (OFDM) is the most often used data transmission technique. Time-domain synchronous OFDM (TDS-OFDM), which is based on iterative padding subtraction (IPS), offers good spectral efficiency across fast-fading channels but is computationally complex. Dual Pseudo Noise Stuffing (DPNS) based TDS-OFDM to IPS-based TDS-OFDM, spectral efficiency is sacrificed to lower computational complexity. TDS-OFDM system performance is improved over a quick time-varying channel by using an alternative time-frequency-domain (TFD) entrenched frame building, albeit at a high computing cost. This work offers a unique frame structure for an OFDM-based DTTB system. It manifests the comparison of QPSK, 8-PSK, and 16-PSK modulation techniques using time-domain training sequence (TS) least mean square (LMS) based TDS-OFDM frame structure for channel estimation. The recommended frame structure is constructed on two-stage channel impulse response (CIR) estimation. The first stage aims to compute the CIR helped with the training sequence in guard intervals. Using the CIR obtained in the first stage as a starting point, the initial weights of an adaptive filter are later modified in the second phase using the LMS approach. Even if the provided frame structure outperforms DPNS-based TDS-OFDM in terms of BER, the loss in spectral efficiency is negligible since fewer than 1.5% of all sub-carriers in this frame structure are used as redundant pilots. As opposed to 8-PSK and 16-PSK, the QPSK achieves a higher level of BER.
Keywords
Digital Terrestrial Television Broadcasting (DTTB), Time Domain Synchronous Orthogonal Frequency Division Multiplexing (TDS-OFDM), Fast Fading Channel, Channel Estimation, Least Mean Square (LMS) Algorithm, Quadrature Phase Shift Keying (QPSK).
References
[1] Linglong Dai, Zhaocheng Wang, and Zhixing Yang, “Next-Generation Digital Television Terrestrial Broadcasting Systems: Key Technologies and Research Trends,” IEEE Communications Magazine, vol. 50, no. 6, pp. 150–158, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Y. S. Cho, J. Kim, W. Y. Yang, and C. G. Kang, MIMO-OFDM Wireless Communications with MATLAB, Wiley Publishing, 2010.
[Google Scholar] [Publisher Link]
[3] B. Muquet et al., “Cyclic Prefixing or Zero Padding for Wireless Multicarrier Transmissions?,” IEEE Transactions on Communications, vol. 50, no. 12, pp. 2136–2148, 2002.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Hsiao-Chun Wu et al., “Theoretical Studies and Efficient Algorithm of Semi-Blind ICI Equalization for OFDM,” IEEE Transactions on Wireless Communications, vol. 7, no. 10, pp. 3791–3798, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Hsiao-Chun Wu, Xiaozhou Huang, and Dongxin Xu, “Novel Semi-Blind ICI Equalization Algorithm for Wireless OFDM Systems,” IEEE Transactions on Broadcasting, vol. 52, no. 2, pp. 211–218, 2006.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Zeyad A. H. Qasem et al., “X-Transform Time-Domain Synchronous IM-OFDM-SS for Underwater Acoustic Communication,” IEEE Systems Journal, vol. 16, no. 2, pp. 1984-1995, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Jingjing Liu, Chao Zhang, and Changyong Pan, “Priori-Information Hold Subspace Pursuit: A Compressive Sensing-Based Channel Estimation for Layer Modulated TDS-OFDM,” IEEE Transactions on Broadcasting, vol. 64, no. 1, pp. 119–127, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Mehmet Başaran et al., “Channel Estimation for TDS-OFDM Systems in Rapidly Time-Varying Mobile Channels,” IEEE Transactions on Wireless Communications, vol. 17, no. 12, pp. 8123–8135, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Jun Wang et al., “Iterative Padding Subtraction of the PN Sequence for the TDS-OFDM Over Broadcast Channels,” IEEE Transactions on Consumer Electronics, vol. 51, no. 4, pp. 1148–1152, 2005.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Jian Fu et al., “A Simplified Equalization Method for Dual PN-Sequence Padding TDS-OFDM Systems,” IEEE Transactions on Broadcasting, vol. 54, no. 4, pp. 825–830, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Zhixing Yang et al., “Transmit Diversity for TDS-OFDM Broadcasting System Over Doubly Selective Fading Channels,” IEEE Transactions on Broadcasting, vol. 57, no. 1, pp. 135–142, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Harsimranjit Kaur, Kuldeepak Singh, and Tarandeep Singh, "Performance Analysis of CO-OFDM-FSO System using PDM," SSRG International Journal of Electrical and Electronics Engineering, vol. 7, no. 3, pp. 12-17, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Weisi Kong et al., “Compressive Sensing Based Channel Estimation for Mimo-Ofdm Systems,” 13th IEEE Conference on Industrial Electronics and Applications, IEEE, pp. 2164–2169, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Emad Farouk et al., “Joint Channel Estimation for TDS-OFDM Based on Superimposed Training,” 14th International Conference on Telecommunication, IEEE, pp. 55–62, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[15] B. P. Lathi, Modern Digital and Analog Communication Systems, Oxford University Press Inc., 1995.
[Google Scholar] [Publisher Link]
[16] T. S. Rappaport, Wireless Communications: Principles and Practice, Prentice Hall PTR New Jersey, vol. 2, 1996.
[Google Scholar] [Publisher Link]
[17] O. Rousseaux et al., “Gaussian Maximum-Likelihood Channel Estimation with Short Training Sequences,” IEEE Transactions on Wireless Communications, vol. 4, no. 6, pp. 2945–2955, 2005.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Hsiao-Chun Wu, and Xiaozhou Huang, “Joint Phase/Amplitude Estimation and Symbol Detection for Wireless ICI Self-Cancellation Coded OFDM Systems,” IEEE Transactions on Broadcasting, vol. 50, no. 1, pp. 49–55, 2004.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Hsiao-chun Wu, and Yiyan Wu, “Distributive Pilot Arrangement based on Modified M-Sequences for OFDM Intercarrier Interference Estimation,” IEEE Transactions on Wireless Communications, vol. 6, no. 5, pp. 1605–1609, 2007.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Linglong Dai, Zhaocheng Wang, and Zhixing Yang, “Time-Frequency Training OFDM with High Spectral Efficiency and Reliable Performance in High Speed Environments,” IEEE Journal on Selected Areas in Communications, vol. 30, no. 4, pp. 695–707, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Zijian Tang et al., “Pilot-Assisted Time-Varying Channel Estimation for OFDM Systems,” IEEE Transactions on Signal Processing, vol. 55, no. 5, pp. 2226–2238, 2007.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Mario Huemer, Alexander Onic, and Christian Hofbauer, “Classical and Bayesian Linear Data Estimators for Unique Word OFDM,” IEEE Transactions on Signal Processing, vol. 59, no. 12, pp. 6073–6085, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Vinay Ingle, Stephen Kogon, and Dimitris Manolakis, Statistical and Adaptive Signal Processing, 2005.
[Google Scholar] [Publisher Link]
[24] Ralph D. Hippenstiel, Detection Theory: Applications and Digital Signal Processing, CRC Press, 2017.
[Google Scholar] [Publisher Link]
[25] John G. Proakis, Digital Signal Processing: Principles Algorithms and Applications, Pearson Education India, 2001.
[Google Scholar] [Publisher Link]
[26] Linglong Dai et al., “Joint Time-Frequency Channel Estimation for Time Domain Synchronous OFDM Systems,” IEEE Transactions on Broadcasting, vol. 59, no. 1, pp. 168–173, 2013.
[CrossRef] [Google Scholar] [Publisher Link]