Bidirectional MIMO Channel Tracking Based on PASTd and Performance Evaluation

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.