Joint TX/RX IQ imbalance parameter estimation using a generalized system model

Abstract

The joint estimation and compensation of IQ imbalance (IQI) parameters at both transmitter (TX) and receiver (RX) is studied in this paper. We develop a generalized system model with a reduced number of parameters (RNP) that covers a wide range of mobile communications scenarios. We devise efficient direct least-squares (DLS) and alternating least-squares (ALS) techniques for IQI parameter estimation based on the generalized system model. For the ALS based method, we prove that the algorithm will converge to a local optimal solution of the optimization problem. Numerical results show that compared with a previously reported method, the proposed DLS-RNP achieves similar performance with a reduced computational complexity, and the proposed ALS-RNP algorithm has significantly better performance with comparable complexity, with a gain over 5 dB for QPSK and 10 dB for 64QAM in the high signal-to-noise-ratio (SNR) region.

Asymmetric Modulation for Hardware Impaired Systems—Error Probability Analysis and Receiver Design

“…where χ m =h 1 x m +h 2 x * m depends on the transmitted symbol m and z is the accumulated noise component (4). For a given channel, I/Q imbalance estimates [48] and transmitted signal x m , the real component y r and imaginary component y i of the received signal y are jointly Gaussian with PDF as given in (8), where the useful in-phase signal component χ m r and quadrature component χ m i are given, respectively, as…”

“…Equivalently,P s can be represented with Gauss hypergeometric function for easy implementation as given in (48).…”

Widely Linear Precoding for Large-Scale MIMO with IQI: Algorithms and Performance Analysis

“…[cos(θ n /2) + jg n sin(θ n /2)], a n2 = 1 1 + σ 2 g [g n cos(θ n /2) − j sin(θ n /2)], (1) 1 The IQI at the user's receiver only degrades its own signal and can be addressed individually by IQI compensation techniques [8]. In contrast, the IQI at the BS affects all the users and is severe in large-scale MIMO systems due to the potential use of cheap hardware for cost issues.…”

“…The IQI exists when there is a gain difference between the two branches and/or the phase difference is not exactly 90 • . The IQI can be present at both the transmitter and the receiver, according to many studies [6]- [8].…”

“…One way of handling IQI is to estimate the IQ parameters and compensate for them (see [8]- [10] and references therein). However, the IQ parameters are usually mingled with the channel coefficients, and thus are difficult to obtain, especially for large-scale MIMO systems, where the number of IQ parameters is proportional to the system size and thus the estimation and compensation for IQI can be very computationally expensive.…”