Abstract
We consider a bidirectional time division duplex (TDD) multiple-input multiple-output (MIMO) communication system with time-varying channel and additive white Gaussian noise (AWGN). A blind bidirectional channel tracking algorithm, based on the projection approximation subspace tracking (PAST) algorithm, is applied in both terminals. The resulting singular value decomposition (SVD) of the channel matrix is then used to approximately diagonalize the channel. The proposed method is applied to an orthogonal frequency-division multiplexing-(OFDM-)MIMO setting with a typical indoor time-domain reflection model. The computational cost of the proposed algorithm, compared with other state-of-the-art algorithms, is relatively small. The Kalman filter is utilized for establishing a benchmark for the obtained performance of the proposed tracking algorithm. The performance degradation relative to a full channel state information (CSI) due to the application of the tracking algorithm is evaluated in terms of average effective rate and the outage probability and compared with alternative tracking algorithms. The obtained results are also compared with a benchmark obtained by the Kalman filter with known input signal and channel characteristics. It is shown that the expected degradation in performance of frequency-domain algorithms (which do not exploit the smooth frequency response of the channel) is only minor compared with time-domain algorithms in a range of reasonable signal-to-noise ratio (SNR) levels. The proposed bidirectional frequency-domain tracking algorithm, proposed in this paper, is shown to attain communication rates close to the benchmark and to outperform a competing algorithm. The paper is concluded by evaluating the proposed blind tracking method in terms of the outage probability and the symbol error rate (SER) versus. SNR for binary phase shift keying (BPSK) and 4-Quadrature amplitude modulation (QAM) constellations.
Highlights
In recent years, multiple-input multiple-output (MIMO)-OFDM schemes have gained increased interest in both theoretical and practical aspects
The tracking ability, the effective rate, the outage probability, and symbol error rate (SER) versus signal-to-noise ratio (SNR) curves are used to evaluate the algorithm and to compare it with the benchmark method based on the Kalman filter as described in Appendix A and the blind iterative MIMO algorithm (BIMA) algorithm, a channel tracking algorithm based on the iterative power method that was proposed by Dahl et al [12]
The method was compared with the BIMA tracking algorithm, which is based on the power method for calculating the channel singular vectors and with a benchmark derived for this evaluation study
Summary
MIMO-OFDM schemes have gained increased interest in both theoretical and practical aspects. Komninakis et al [4] use the Kalman filter in the time domain to track the channel coefficients. Hou et al [8] showed that the obtainable mean square error (MSE) of time- and frequency-domain channel estimation procedures is equivalent. Their analysis (based on pilot submission) is only applicable if an appropriate frequency-domain smoothing is performed. The derived Kalman-based bidirectional frequency-domain benchmark is compared with the proposed method.
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