893 research outputs found

    Superimposed training-based channel estimation and data detection for OFDM amplify-and-forward cooperative systems under high mobility

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    In this paper, joint channel estimation and data detection in orthogonal frequency division multiplexing (OFDM) amplify-and-forward (AF) cooperative systems under high mobility is investigated. Unlike previous works on cooperative systems in which a number of subcarriers are solely occupied by pilots, partial data-dependent superimposed training (PDDST) is considered here, thus preserving the spectral efficiency. First, a closed-form channel estimator is developed based on the least squares (LS) method with Tikhonov regularization and a corresponding data detection algorithm is proposed using the linear minimum mean square error (LMMSE) criterion. In the derived channel estimator, the unknown data is treated as part of the noise and the resulting data detection may not meet the required performance. To address this issue, an iterative method based on the variational inference approach is derived to improve performance. Simulation results show that the data detection performance of the proposed iterative algorithm initialized by the LMMSE data detector is close to the ideal case with perfect channel state information. © 2006 IEEE.published_or_final_versio

    Channel Estimation for Time-Varying MIMO Relay Systems

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    In this paper, we investigate the channel estimation problem for multiple-input multiple-output (MIMO) relay communication systems with time-varying channels. The time-varying characteristic of the channels is described by the complexexponential basis expansion model (CE-BEM). We propose a superimposed channel training algorithm to estimate the individual first-hop and second-hop time-varying channel matrices for MIMO relay systems. In particular, the estimation of the secondhop time-varying channel matrix is performed by exploiting the superimposed training sequence at the relay node, while the first-hop time-varying channel matrix is estimated through the source node training sequence and the estimated second-hop channel. To improve the performance of channel estimation, we derive the optimal structure of the source and relay training sequences that minimize the mean-squared error (MSE) of channel estimation. We also optimize the relay amplification factor that governs the power allocation between the source and relay training sequences. Numerical simulations demonstrate that the proposed superimposed channel training algorithm for MIMO relay systems with time-varying channels outperforms the conventional two-stage channel estimation scheme

    Quadrature spatial modulation aided single-input multiple-output-media based modulation: application to cooperative network and golden code orthogonal super-symbol systems.

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    Doctoral Degree. University of KwaZulu-Natal, Durban.SIMO-MBM (single-input multiple-output media-based modulation) overcomes the limitations of SIMO (single-input multiple-output) systems by reducing the number of antennas required to achieve a high data rate and improved error performance. In this thesis, the quadrature dimension of the spatial constellation is used to improve the overall error performance of the conventional SIMO-MBM and to achieve a higher data rate by decomposing the amplitude/phase modulation (APM) symbol into real and imaginary components, similar to quadrature spatial modulation (QSM). The average bit error probability of the proposed technique is expressed using a lower bound approach and validated using the results of Monte Carlo simulation (MCS). The proposed system also investigates the effect of antenna correlation in combination with channel amplitude to select a sub-optimal mirror activation pattern. The results of MCS show a 3.5dB improvement at 10b/s/Hz with m =2 and a 7dB improvement at 12b/s/Hz with =2 over the traditional SIMO-MBM scheme. The effect of imperfect channel estimation on the proposed scheme is investigated, with a trade-off of 2dB in coding gain due to channel estimation errors. Cooperative Networking (CN) improves wireless network reliability, link quality, and spectrum efficiency by collaborating among nodes. The decode and forward relaying technique is used in this thesis to investigate the performance of QSM aided SIMO-MBM in a Cooperative Network (CN). This technique uses two source nodes that simultaneously transmit a unique message block on the same time slot to the relay node, which then decodes the received message block from both transmitting nodes before re-encoding and re-transmitting the decoded message block in the next time slot to the destinations in order to significantly improve the QSM aided SIMO-MBM’s error performance. Using network coding (NC) techniques, each Node can decode the data of the other Node. To enhance network performance, complexity, robustness, and minimize delays, data is encoded and decoded in NC; algebraic techniques are applied to the detected message to collect the various transmissions. The proposed scheme's theoretical average error probability was defined using a lower bound technique, and the results of Monte Carlo simulation (MCS) validated the result. The MCS results achieved exhibit a significant improvement of 8 dB at 6 b/s/Hz and 12 dB at 8 b/s/Hz over the conventional QSM aided SIMO-MBM scheme. The media-based modulation (MBM) technique can achieve significant throughput, increase spectrum efficiency, and improve bit-error-rate performance (BER). In this thesis, the use of MBM in single-input multiple-output systems is examined using radio frequency (RF) mirrors and Golden code (GC-SIMO). The goal is to lower the system's hardware complexity by maximizing the linear relationship between RF mirrors and spectral efficiency in MBM in order to achieve a high data rate with less hardware complexity. The GC scheme's encoder uses orthogonal pairs of the super-symbol, each transmitted via a separate RF mirror at a different time slot to achieve full rate full diversity. In the results of MCS obtained, at a BER of 10−5, the GC-SIMO-MBM exhibits a significant performance of approximately 7dB and 6.5 dB SNR gain for 4 b/s/Hz and 6 b/s/Hz, respectively, compared to GC-SIMO. The proposed scheme's derived theoretical average error probability is validated by the results of the Monte Carlo simulation
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