Joint estimation of synchronization impairments in MIMO-OFDM system

Abstract

Maximum Likelihood (ML) algorithms, for the joint estimation of synchronization impairments and channel in Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system, are investigated in this work. A system model that takes into account the effects of carrier frequency offset, sampling frequency offset, symbol timing error, and channel impulse response is formulated. Cramér-Rao Lower Bounds for the estimation of continuous parameters are derived, which show the coupling effect among different impairments and the significance of the joint estimation. We propose an ML algorithm for the estimation of synchronization impairments and channel together, using grid search method. To reduce the complexity of the joint grid search in ML algorithm, a Modified ML (MML) algorithm with multiple one-dimensional searches is also proposed. Further, a Stage-wise ML (SML) algorithm using existing algorithms, which estimate fewer number of parameters, is also proposed. Performance of the estimation algorithms is studied through numerical simulations and it is found that the proposed ML and MML algorithms exhibit better performance than SML algorithm.

Maximum likelihood algorithms for joint estimation of synchronisation impairments and channel in multiple input multiple output–orthogonal frequency division multiplexing system

“…Cramér-Rao lower bounds (CRLBs) for the estimation of continuous parameters are derived, which show the coupling effect among different impairments and the significance of the joint estimation algorithms. Some results of this paper are also presented in [10].…”

Bayesian approach for joint estimation of phase noise and channel in orthogonal frequency division multiplexing system

“…with Γ defined as the standard Fisher information matrix (FIM) [15,23]. Let μ be the mean of the received signal vector r in (7). Then Γ is given by…”

Joint statistical framework for the estimation of channel and SFO in OFDM systems

“…A maximum likelihood (ML) joint estimator for carrier frequency offset (CFO) together with SFO for an OFDM system, assuming perfect channel knowledge, is described in [2]. Similarly, joint estimator for synchronisation impairments, assuming perfect channel knowledge, in OFDM-based communication system is described in [3]. Also, joint estimation of CFO, SFO, channel, and timing error in OFDM-based system is explored in [4].…”

“…In [7], a pilot-aided joint channel impulse response (CIR), CFO, and SFO estimation scheme, assuming a perfect start of frame detection and neglecting channel statistics, has been proposed for OFDM-based systems. However, the methods described in [2][3][4][5][6][7] have neglected the prior statistical information related to channel in the formulation of joint estimators and are not optimal in a statistical approach. The prior knowledge of the channel can be extracted using the methods described in [8], where estimation techniques of statistical properties of fading channels are discussed.…”

“…Similarly, joint estimator for synchronisation impairments, assuming perfect channel knowledge, in OFDM‐based communication system is described in [3]. Also, joint estimation of CFO, SFO, channel, and timing error in OFDM‐based system is explored in [4]. The importance of the estimation of channel together with SFO in OFDM‐based communication systems is described in [5] with formulation of different ML‐based joint estimation algorithms.…”