Paper
10 August 2004 Semi-blind channel estimation for zero padded-OFDM systems with asynchronous interferers
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Abstract
In this paper, a subspace-based semi-blind channel identification scheme is developed for a zero padded-orthogonal frequency division multiplexing (ZP-OFDM) system with asynchronous interferers. In our model of multiuser OFDM signals, an asynchronous interferer has a guard interval within the transmitted data block when the observation window is synchronized with respect to the desired user. As a result, the interfering user's channel vector lies in a different null space relative to the desired user's subspace, allowing the desired user's channel vector to be separated and determined uniquely up to a multiplicative scalar. However, in practice, a noisy sample correlation matrix produces a number of small eigenvalues, which can cause poor performance when conventional subspace techniques are employed. This problem is overcome by using several eigenvectors corresponding to the smallest eigenvalues; the channel estimates are obtained by linear combinations of these vectors. In order to find the linear combining coefficients, known pilot symbols are required. However, the pilot-only estimation method is not feasible when the channel order and the number of active users are large. Therefore, we use the preceding method to develop a subspace-based semi-blind algorithm that guarantees estimation of every user's channel vector. Simulation results demonstrate that the semi-blind channel estimator offers more than a 2dB gain over pilot-only channel estimation in the bit error rate (BER) performance.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hyejung Jung and Michael D. Zoltowski "Semi-blind channel estimation for zero padded-OFDM systems with asynchronous interferers", Proc. SPIE 5440, Digital Wireless Communications VI, (10 August 2004); https://doi.org/10.1117/12.542316
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KEYWORDS
Orthogonal frequency division multiplexing

Signal to noise ratio

Antennas

Error analysis

Data modeling

Algorithm development

Computer simulations

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