Vector RLS-Based Joint Estimation of Channel Response and Frequency Offsets for MIMO-OFDM

Abstract

This paper proposes a pilot-aided algorithm for the joint estimation of the channel impulse response (CIR), carrier frequency offset (CFO) and sampling frequency offset (SFO) in burst-mode multiple-input multiple-output (MIMO) - orthogonal frequency division multiplexing (OFDM) systems. We employ the vector recursive least-squares (RLS) algorithm that can function as an adaptive filter with multiple outputs for the joint estimation problem in MIMO scenarios. Specifically, based on the received signal samples that contain pilot tones in the frequency domain, we formulate a cost function that includes the multi-antenna channel impulse responses and frequency offsets for the vector RLS-based joint estimation of CIR CFO and SFO. Analytical and simulated results show that, over large ranges of CFO and SFO values, the proposed estimation and tracking approach offers fast convergence, high stability, and provides a near optimum receiver performance that is remarkably close to the ideal one in the case of perfect channel estimation and synchronization over Rayleigh multi-path fading channels.