Low-complexity adaptive iteration algorithm for frequency tracking in OFDM systems

The carrier frequency offset (CFO), destroying the orthogonality between subcarriers, greatly degrades the performance of an orthogonal frequency-division multiplexing system. One of the most frequently used ways for a CFO estimator design is to adopt maximum-likelihood (ML) estimation, achieving high accuracy tightly close to the Cramer-Rao lower bounds (CRLBs). One of the ML-based algorithms, called linearly-combined CFO (LC-CFO), evaluates all the single-time-slot CFO estimates first and then linearly combined these CFO estimates in the minimum mean-square-error sense. Its tracking range is quite wide up to half the carrier spacing, and convergence speed is very fast, costing only several tens of iterations; moreover, its mean-square error (MSE) performances are very much close to CRLBs at medium-to-high signal-to-noise ratio (SNR) values. However, a set of arctangent functions is needed to be evaluated for each iteration, which increases the computational complexity. In this article, a low complexity, called simplified LC-CFO (SLC-CFO), is proposed that the set of arctangent functions are replaced by low-complexity limiters, resulting in simplifying the receiver design and reducing the computational load while keeping nearly the same tracking range and MSE performances. With proper choice of a parameter, SLC-CFO even shows faster convergence speed and lower MSE value at low SNR, compared with LC-CFO. Simulation results demonstrate all these aforementioned properties.