Yashvi Mojidra, Vidhi Sheth, Rizwan Alad, Nirav Desai, Ashish Pandya, Purvang Dalal | International Journal of Microwave Engineering and Technology | Vol 12, Issue 02 | ISSN: 2455-0337
Abstract
Due to its great spectral efficiency and resilience to multipath fading, orthogonal frequency division multiplexing,
or OFDM, has become a popular modulation technique in contemporary wireless communication systems.
Reliable OFDM reception depends on accurate channel estimate, and methods like Least Squares (LS) and
Minimum Mean Square Error (MMSE) estimation are frequently used to make up for channel impairments.
However, despite effective channel estimation, practical receiver performance can still be degraded by radio-
frequency front-end imperfections, particularly I/Q imbalance caused by gain and phase mismatches between the
in-phase and quadrature branches. This work investigates the impact of I/Q imbalance on OFDM receiver
performance. A mathematical model incorporating gain and phase mismatches is developed, and the resulting
Image Rejection Ratio (IRR) is analyzed as a key indicator of receiver impairment. The relationship between IRR
and image leakage is examined to demonstrate how increased image signal power reduces the receiver's image
suppression capability. Furthermore, the effect of image leakage on 64-QAM constellation distortion is analyzed
under gain mismatch, phase mismatch, and combined imbalance conditions. The resulting constellation distortion
is shown to degrade the effective Signal-to-Noise Ratio (SNR), which subsequently increases the Bit Error Rate
(BER). Numerical results including IRR, image leakage, constellation diagrams, SNR performance, and BER
characteristics are presented to evaluate the overall impact of I/Q imbalance on OFDM communication systems.
The study provides a comprehensive understanding of the degradation mechanisms introduced by receiver-side
RF impairments and their influence on communication reliability.
Keywords: I/Q Imbalance; OFDM Systems; Image Rejection Ratio (IRR); 64-QAM; Bit Error Rate (BER).
References
[1] Souleymane B, Mondol SR, Wei Z. Comparative performance study of ls and mmse channel estimation over time varying channel in ofdm system. International Journal of Engineering Research & Technology (IJERT).2016 Mar;5(03). [2] Zaier A, Bouallegue R. Channel estimation study for block-pilot insertion in OFDM systems under slowly time varying conditions. arXiv preprint arXiv:1202.1552. 2012 Feb 7. [3] Vilas Boas EC, e Silva JD, de Figueiredo FA, Mendes LL, de Souza RA. Artificial intelligence for channel estimation in multicarrier systems for B5G/6G communications: a survey. EURASIP Journal on Wireless Communications and Networking. 2022 Dec 2;2022(1):116. [4] Saeed HF, Zafar A. Widely linear equalization for IQ imbalance contaminated multicarrier systems. Physical Communication. 2022 Feb 1;50:101511. [5] Lang O, Hofbauer C, Tockner M, Feger R, Wagner T, Huemer M. OFDM-based waveforms for joint sensing and communications robust to frequency selective IQ imbalance. IEEE Transactions on Vehicular Technology. 2024 Sep 18;74(1):1078-91. [6] Yan F, Zhu WP, Ahmad MO. Carrier frequency offset estimation and I/Q imbalance compensation for OFDM systems. EURASIP Journal on Advances in Signal Processing. 2007 Dec 1;2007(1):045364. [7] Tandur D, Moonen EURASIP Member M. Efficient compensation of transmitter and receiver IQ imbalance in OFDM systems. EURASIP Journal on Advances in Signal Processing. 2010 Aug 16;2010(1):106562. [8] Cao X, Liu Y, Hu D. Simplified LLR algorithm for mâQAM demodulation. the Journal of Engineering. 2019 Nov;2019(21):7370-5. [9] Jacovic M, Juretus K, Kandasamy N, Savidis I, Dandekar KR. Physical layer encryption for wireless OFDM communication systems. Journal of Hardware and Systems Security. 2020 Sep;4(3):230-45. [10] Rizk M, Baghdadi A, JĂ©zĂ©quel M. A Literature Survey on Algorithms and Hardware Architectures of Max- Log-MAP Demapping. Journal of Circuits, Systems and Computers. 2022 Feb 10;31(03):2230001. [11] Yu Y, Wang J, Zhou X, Wang C, Bai Z, Ye Z. Review on channel estimation for reconfigurable intelligent surface assisted wireless communication system. Mathematics. 2023 Jul 23;11(14):3235. [12] Oruthota U, Tirkkonen O. SER/BER expression for M-QAM OFDM systems with imperfect channel estimation and I/Q imbalance. EURASIP Journal on Wireless Communications and Networking. 2012 Sep 25;2012(1):303. [13] Jaradat AM, Hamamreh JM, Arslan H. Modulation options for OFDM-based waveforms: Classification, comparison, and future directions. IEEE Access. 2019 Jan 31;7:17263-78. [14] Tarighat A, Bagheri R, Sayed AH. Compensation schemes and performance analysis of IQ imbalances in OFDM receivers. IEEE Transactions on Signal Processing. 2005 Aug 31;53(8):3257-68. [15] Ha T, Park J. Attention-Aided MMSE for OFDM Channel Estimation. In2025 59th Asilomar Conference on Signals, Systems, and Computers 2025 Oct 26 (pp. 1437-1443). IEEE.11 [16] Kumar TA, Anjaneyulu L. Channel estimation techniques for multicarrier OFDM 5G wireless communication systems. In2020 IEEE 10th international conference on system engineering and technology (ICSET) 2020 Nov 9 (pp. 98-101). IEEE. [17] Sutar MB, Patil VS. LS and MMSE estimation with different fading channels for OFDM system. In2017 international conference of electronics, communication and aerospace technology (ICECA) 2017 Apr 20 (Vol. 1, pp. 740-745). IEEE. [18] Shamasundar B, Chockalingam A. Joint estimation of channel and IQ imbalance in media-based modulation. In2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring) 2019 Apr 28 (pp. 1-5). IEEE. [19] Tarafder P, Chun C, Ullah A, Kim Y, Choi W. Channel estimation in 5G-and-beyond wireless communication: A comprehensive survey. Electronics. 2025 Feb 14;14(4):750. [20] Guneser MT, Sahab AS, Seker C. Performance analysis of modulation techniques in 5G communication system. China Communications. 2022 Aug 17;19(8):100-14.
