Blind Compensation of I/Q Impairments in Wireless Transceivers

Abstract

The majority of techniques that deal with the mitigation of in-phase and quadrature-phase (I/Q) imbalance at the transmitter (pre-compensation) require long training sequences, reducing the throughput of the system. These techniques also require a feedback path, which adds more complexity and cost to the transmitter architecture. Blind estimation techniques are attractive for avoiding the use of long training sequences. In this paper, we propose a blind frequency-independent I/Q imbalance compensation method based on the maximum likelihood (ML) estimation of the imbalance parameters of a transceiver. A closed-form joint probability density function (PDF) for the imbalanced I and Q signals is derived and validated. ML estimation is then used to estimate the imbalance parameters using the derived joint PDF of the output I and Q signals. Various figures of merit have been used to evaluate the efficacy of the proposed approach using extensive computer simulations and measurements. Additionally, the bit error rate curves show the effectiveness of the proposed method in the presence of the wireless channel and Additive White Gaussian Noise. Real-world experimental results show an image rejection of greater than 30 dB as compared to the uncompensated system. This method has also been found to be robust in the presence of practical system impairments, such as time and phase delay mismatches.

Application of Approximation Constructions with a Small Number of Parameters for the Estimation of a Rayleigh Fading Multipath Channel with Doppler Spectrum Spreading

“…A review of methods [25][26][27][28][29][30][31][32] for estimating the channel and signal distortion in a direct conversion receiver showed that most often, the estimation of IQ imbalance is considered, or high-precision procedures for joint estimation of channel parameters and signal distortion, such as IQ imbalance, frequency shift, and DC offset, which have a very high computational complexity [32]. Known algorithms work either according to special test sequences [29][30][31] or "blindly" [33].…”

“…This means that this approach requires the transmission of a test signal again. For example, in [25] the statistical properties of the channel are known, in [26] it is necessary to know the joint PDF of the signal components. In [27], joint estimation and compensation of IQ imbalance are considered.…”

Localization Error Bounds for 5G mmWave Systems Under I/Q Imbalance

“…example [6]), to the best of our knowledge, it has not been investigated for 5G, despite its severity in mmWave systems [7]. IQI gain and phase parameters are usually compensated during the channel estimation phase [6], [8]. In mmWave systems, this is the phase during which DOD, DOA, and TOA are estimated and ultimately a position fix is obtained.…”

Localization Error Bounds For 5G mmWave Systems Under I/Q Imbalance: An Extended Version

“…Although the effect of IQ imbalance (IQI) on positioning was studies previously in several papers (See for example [6]), to the best of our knowledge, it has not been investigated for 5G, despite its severity in mmWave systems [7]. IQI gain and phase parameters are usually compensated during the channel estimation phase [6], [8]. In mmWave systems, this is the phase during which DOD, DOA, and TOA are estimated and ultimately a position fix is obtained.…”