On the CFO/Channel estimation technique for MIMO-OFDM systems without using a prior knowledge of channel length

Tsui-Tsai Lin,Fuh-Hsin Hwang

doi:10.1186/s13638-015-0318-1

Abstract

In this paper, we propose an estimator which jointly estimates the carrier frequency offset (CFO) and channel state without a prior knowledge of channel length (CL) for a multiple-input multiple-output orthogonal frequency-division multiplexing system. A preliminary CFO/channel estimate is first reached based on the maximum-likelihood criterion. To improve the over-determined problem, a CL estimation technique is further developed. The first-order Taylor series expansion approach is used to determine the trimmed CFO estimate such that the exhaustive point search can be avoided. Simulation results have been presented to demonstrate that the proposed scheme provides a performance comparable to that of the optimal estimation which assumes that CL is known in advance.

Highlights

The multiple-input multiple-output (MIMO) scheme [1,2] incorporating with the orthogonal frequency division multiplexing (OFDM) [3,4] has attracted much attention of research workers for a long while
The above-mentioned studies [16,17,18] including the Maximum likelihood (ML) estimate approaches [17,18] provide superior performance while taking their predominance into account, all of these approaches require a prior knowledge of channel length (CL), but CL is difficult to be acquired especially when carrier frequency offset (CFO) is considered in MIMO-OFDM systems
6 Conclusions An algorithm for the joint CFO and channel estimation is presented for the MIMO-OFDM scenario

Summary

Introduction

The multiple-input multiple-output (MIMO) scheme [1,2] incorporating with the orthogonal frequency division multiplexing (OFDM) [3,4] has attracted much attention of research workers for a long while. Lin and Hwang EURASIP Journal on Wireless Communications and Networking (2015) 2015:79 in [17] Another novel ML-based scheme that estimates the aggregate effects of the channel and CFO by using two successive OFDM preambles can be found in [18]. The above-mentioned studies [16,17,18] including the ML estimate approaches [17,18] provide superior performance while taking their predominance into account, all of these approaches require a prior knowledge of channel length (CL), but CL is difficult to be acquired especially when CFO is considered in MIMO-OFDM systems. A joint channel and CL estimation is proposed for single-input single-output (SISO) OFDM systems in [23] where the Levinson recursion technique is employed without significant incremental cost. Om×n is an m×n zero matrix. 1n and 0n stand for all-one and allzero vectors with length n, respectively. diag{a1, · · · , an} is a diagonal matrix with diagonal entries taking from a1, · · · , an. (·)∗, (·)T , and (·)H are, respectively, the complex conjugate, transpose, and Hermitian transpose of (·). ⊗, {·}, E{·}, | · |, and · denote the operations taking the Kronecker product, real part, ensemble average, absolute value, and the Frobenius norm, respectively

Data model and ML estimation

Over-determined case

Findings

Conclusions