Abstract
This paper proposes a turbo joint channel estimation, synchronization, and decoding scheme for coded multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. The effects of carrier frequency offset (CFO), sampling frequency offset (SFO), and channel impulse responses (CIRs) on the received samples are analyzed and explored to develop the turbo decoding process and vector recursive least squares (RLSs) algorithm for joint CIR, CFO, and SFO tracking. For burst transmission, with initial estimates derived from the preamble, the proposed scheme can operate without the need of pilot tones during the data segment. Simulation results show that the proposed turbo joint channel estimation, synchronization, and decoding scheme offers fast convergence and low mean squared error (MSE) performance over quasistatic Rayleigh multipath fading channels. The proposed scheme can be used in a coded MIMO-OFDM transceiver in the presence of multipath fading, carrier frequency offset, and sampling frequency offset to provide a bit error rate (BER) performance comparable to that in an ideal case of perfect synchronization and channel estimation over a wide range of SFO values.
Highlights
Coded multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) has been intensively explored for broadband communications over multipath-rich, time-invariant frequency-selective channels [1]
By analyzing the nonlinear interrelation between carrier frequency offset (CFO), sampling frequency offset (SFO), channel responses, and received subcarriers, we develop an iterative vector recursive least-squares (RLSs-)-based joint channel impulse responses (CIRs), CFO, and SFO tracking scheme that can be incorporated in the turbo processing between the MIMO-demapper and softinput soft-output (SISO) decoder for the coded MIMOOFDM receiver
Under the above implementation of the vector recursive least squares (RLSs)-based tracking of CIR, CFO, and SFO algorithm, the resulting computational complexity is (L3Nt3Nr3Nd) per each turbo iteration, where L denotes the channel length, Nt stands for the number of transmit antennas, Nr is the number of receive antennas, and Nd is the number of subcarriers used in each turbo iteration for the vector RLS tracking
Summary
Coded multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) has been intensively explored for broadband communications over multipath-rich, time-invariant frequency-selective channels [1]. Iterative detection and decoding issues in MIMO systems to achieve near-Shannon capacity limit [2] and performance gain [5] were investigated under the assumption of perfect channel estimation and synchronization. Taking into account the effects of imperfect channel knowledge on the system performance, [4] developed a combined iterative detection/decoding and channel estimation scheme to improve the overall performance of MIMOOFDM systems with perfect synchronization. Estimation of frequency offsets (CFO and SFO) and channel impulse responses (CIRs) are of crucial importance in (coded) MIMO-OFDM systems using coherent detection. The insufficient accuracy of initially estimated CFO, SFO, and channel responses as well as their time variation still require known pilot tones inserted in the data segment of the burst to update and enhance the CFO, SFO, and channel
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