OFDM中利用酉变换和结构最小二乘的角度和时延联合估计

doi:10.3969/j.issn.0255-8297.2017.06.003

Abstract

Abstract:

In an orthogonal frequency division multiplexing (OFDM) system, traditional subspace-based joint angle and delay estimation algorithms show significant performance degradation at low signal-to-noise ratio (SNR). To solve the problem, a new algorithm using unitary transform and structured least squares (SLS) is proposed. With unitary transform, data are transformed to the real number domain. Two-dimensional SLS is then used to estimate two real-valued diagonal matrices that contain information of angles and delays. A complex matrix is constructed with the two real-valued matrices, and eigenvalues of the complex matrix are calculated. The real and imaginary parts of the eigenvalues correspond to angles and delays, respectively. Since SLS takes into account the coupling relationship between noise terms and restores the estimated signal subspace matrix, its estimation performance is closer to optimum than those of the others. Simulation results show that the proposed USLS-JADE algorithm is superior to traditional subspace-based algorithms in terms of accuracy and success rate.

Key words: wireless communications, joint angle and delay estimation (JADE), structured least squares (SLS), orthogonal frequency division multiplexing (OFDM)

CLC Number:

TN911.7

GUO Li-kai, WU Ying, YIN Jie-xin, WANG Cheng. Joint Angle and Delay Estimation for OFDM Using Unitary Transform and Structured Least Squares[J]. Journal of Applied Sciences, 2017, 35(6): 693-705.

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Joint Angle and Delay Estimation for OFDM Using Unitary Transform and Structured Least Squares

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