Orthogonal Frequency Division Multiplexing (OFDM) becomes the foundation technique for broadband wireless communications because of its various advantages including high spectrum efficiency, low complexity equalization and great flexibility in resource optimization. However, one well-known disadvantage of OFDM is its high sensitivity to carrier frequency offset (CFO) [
1]. CFO refers to the frequency difference between the local oscillators in the transmitter and receiver. CFO causes intercarrier interference (ICI) and could deteriorate the system performance seriously. CFO itself is not difficult to estimate and compensate, using either training-based or blind estimation schemes [
2,
3]. However, when some distortions, in particular, I/Q mismatch, are entangled with CFO, the performance of conventional CFO estimator will degrade significantly [
4].
I/Q mismatch is caused by the imbalance between the components of the Inphase (I-) and Quadrature (Q-) branches in I/Q modulated systems. I/Q mismatch includes gain and phase mismatches. Gain mismatch is caused by the gain difference of amplifiers or filters in I- and Q- branches. Phase mismatch is caused by the nonideal
rotation in local oscillators and the phase difference between analogue filters in I- and Q- branches. In a practical receiver with analog I/Q separation, I/Q mismatch always exists and contributes as interference in general CFO estimation. On the other hand, without the knowledge of CFO, a training-based estimator cannot estimate I/Q mismatch accurately. CFO estimation in the presence of I/Q mismatch is not trivial, and has been investigated in, for example, [
5‐
14]. Each of these schemes partially solves the CFO estimation problem in the presence of I/Q mismatch, with respective drawbacks. In [
5,
6], initial CFO is estimated in the presence of errors caused by I/Q imbalance. Then, based on the CFO estimates, [
5] proposes an iterative I/Q mismatch estimation approach, which requires five iterations to obtain the gain parameter. In [
6], a simple time domain I/Q mismatch estimation method is proposed, but the performance degrades significantly when CFO is small. [
6] also proposes a frequency domain estimator which improves performance when CFO is small, however, it is sensitive to transmitter side mismatch. In [
7], an iterative scheme is proposed, requiring special training symbols which contain many zeros to suppress the I/Q mismatch effect in the receiver. In [
8], a searching-based CFO estimator is developed. The high computational complexity, however, may prevent it from practical applications. In [
12] iterative estimators are proposed, and they have relatively high complexity. In [
13], a frequency domain adaptive I/Q mismatch compensation scheme is proposed, however, it requires perfect CFO knowledge. In [
14], perfect CFO knowledge is required either in the training based RLS method or in forming the per-tone-equalizer. In [
9,
10], CFO estimators based on three identical training symbols are proposed. However, [
9] only uses a cosine function of the CFO to estimate the CFO parameter. The scheme is thus very sensitive to noise when CFO and/or I/Q mismatch is small, and has a phase ambiguity problem with positive and negative phases. Improvement to [
9] is made in [
10], using two groups of three identical training symbols. Although this estimator is robust to both transmitter and receiver I/Q mismatch, the special long training symbols designed for CFO estimation increase system overhead and are incompatible with current standards. In [
11], a complete CFO and I/Q mismatch estimation and compensation scheme is proposed based on the CFO estimator in [
9]. However, I/Q mismatch parameters are estimated based on the CFO estimates, which is sensitive to noise, particularly when CFO is small.
In our early work [
15], we independently developed a CFO estimation scheme partially similar to the approach in [
10]. Different to [
10], our scheme only requires one group of three identical training symbols by forming an approximated estimator for the CFO. The scheme works well for various I/Q mismatch values when the CFO is not too small (say,
of the normalized CFO), and the performance otherwise degrades. In this paper, we propose some novel estimation schemes which are robust to any values of both transmitter and receiver I/Q mismatch, and have better accuracy of the I/Q mismatch estimation for small CFO. The schemes use a group of at least three identical training symbols, which are generally present in the preamble of current systems, for example, WLAN and WiMAX systems. They serially estimate I/Q mismatch and CFO with low complexity, without incurring iterative process. The schemes mainly consist of three steps. Firstly, a cosine function of the CFO, which is free of I/Q mismatch interference, is formed using a group of three identical training symbols. Secondly, based on the estimated value of the cosine function instead of the CFO estimate, the I/Q mismatch parameters are estimated. Thirdly, the I/Q mismatch is compensated using the estimates, and a sine function of the CFO is formed based on the compensated signal. Combining the results of cosine and sine functions, CFO can then be estimated accurately. The use of cosine value instead of the CFO estimate for I/Q mismatch estimation is from the insight that the cosine value is much more robust to noise than the CFO estimate. The rest of the paper is organized as follows. Section 2 formulates the problem of CFO and I/Q mismatch estimation in OFDM systems. In Section 3, the proposed CFO and I/Q mismatch estimation schemes are developed. Simulation results are presented in Section 4. Section 5 concludes the paper.