Linearly time-varying channel estimation and symbol detection for OFDMA uplink using superimposed training

Authors:
Han Zhang;Xianhua Dai;Dong Li;Sheng Ye
Affiliations:
Department of Electronics & Communication Engineering, Sun Yat-Sen University, Guangzhou, China;Department of Electronics & Communication Engineering, Sun Yat-Sen University, Guangzhou, China;Department of Electronics & Communication Engineering, Sun Yat-Sen University, Guangzhou, China;Department of Electronics & Communication Engineering, Sun Yat-Sen University, Guangzhou, China
Venue:
EURASIP Journal on Wireless Communications and Networking - Special issue on OFDMA architectures, protocols, and applications
Year:
2009

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Abstract

We address the problem of superimposed trainings- (STs-) based linearly time-varying (LTV) channel estimation and symbol detection for orthogonal frequency-division multiplexing access (OFDMA) systems at the uplink receiver. The LTV channel coefficients are modeled by truncated discrete Fourier bases (DFBs). By judiciously designing the superimposed pilot symbols, we estimate the LTV channel transfer functions over the whole frequency band by using a weighted average procedure, thereby providing validity for adaptive resource allocation. We also present a performance analysis of the channel estimation approach to derive a closed-form expression for the channel estimation variances. In addition, an iterative symbol detector is presented to mitigate the superimposed training effects on information sequence recovery. By the iterative mitigation procedure, the demodulator achieves a considerable gain in signal-interference ratio and exhibits a nearly indistinguishable symbol error rate (SER) performance from that of frequency-division multiplexed trainings. Compared to existing frequency-division multiplexed training schemes, the proposed algorithm does not entail any additional bandwidth while with the advantage for system adaptive resource allocation.