Semi-Blind Channel Estimation Algorithm for OFDM Systems

A semi-blind channel estimation algorithm based on subspace approach for orthogonal frequency division multiplexing（OFDM） systems over the frequency-selective channel is proposed. A linear preeoding is applied on each block before the IFFT operation and a low-rank structure is created in the received signal. Then subspace properties can be exploited to identify the channel up to a scalar ambiguity. The residual scalar ambiguities eliminated by inserting pilots into data stream. Simulation results illustrate the performance of the proposed semi-blind algorithm.

Adaptive Bit Loading Scheme with Semi-Blind Channel Estimation for OFDMSystems

An adaptive bit loading and power-allocation scheme is proposed in order to augment the performance of the system based on orthogonal frequency division multiplexing （OFDM）, which is based on the maximum power margin. Coinciding with the adaptive loading scheme, a semi-blind channel estimation algorithm using subspace decomposition method is proposed, which uses the information in the cyclic prefix. An initial channel state information is estimated by using the training sequences with the method of interpolation filtering. The proposed adaptive scheme is simulated on an OFDM wireless local area network（WLAN） system in a time-varying channel. The performance is compared to the constant loading scheme.

A Novel Blind Channel Estimation for a 2x2 MIMO System

A novel blind channel estimation method based on a simple coding scheme for a 2 by 2 multiple input multiple output (MIMO) system is described. The proposed algorithm is easy to implement in comparison with conventional blind estimation algorithms, as it is able to recover the channel matrix without performing singular value decomposition (SVD) or eigenvalue decomposition (EVD). The block coding scheme accompanying the proposed estimation approach requires only a block encoder at the transmitter without the need of using the decoder at the receiver. The proposed block coding scheme offers the full coding rate and reduces the noise power to half of its original value. It eliminates the phase ambiguity using only one additional pilot sequence.

Optimization on semi-blind channel estimation for MIMO-OFDM systems

An orthogonal frequency division multiplexing （OFDM） is one of the effective techniques used in wireless communication. In OFDM systems, channel impairments due to multipath dispersive spreading can cause deep fades in wireless channels. Thus, the OFDM receiver requires channel state information when coherent detection is involved. Therefore, to overcome the impact of channel fades good channel estimation （CE） methods are needed in OFDM systems. And one of these CE methods is a semi-blind CE. However, the semi-blind method requires a large number of processing operations. In order to avoid the high computing complexity of the existing method, scaled least square （SLS） technique is applied to improve the performance of the semi-blind channel estimator which require less knowledge of the channel second-order statistics and have better performance than the least square （LS） which used in semi-blind CE. Simulation results shows, this proposed method of semi-blind CE has the capacity of elevating CE performance in multiple-input multiple-output （MIMO） OFDM systems.

Orthogonal procrustes based semi-blind MIMO channel estimation under space-time block code transmissions

This work investigates a novel semi-blind channel estimation for multiple-input multiple-output （MIMO） space-time block coding （STBC） systems. Algorithms for channel estimation based on whitening-rotation （WR） decomposition that provides a combined quality and spatial scalability is utilized. Using a space-time code-constrained input design, our approach exploits the orthogonality of the signal and noise subspaces in conjunction with orthogonal procrustes （OP） technique to obtain an accurate estimate of the unitary rotation matrix and, consequently, of the channel parameters. Unitary rotation matrices are parameterized a much fewer number of parameters, and significant estimation gains can then be achieved by estimation of such orthogonal matrices. Furthermore, the proposed semi-blind MIMO channel estimation approach is conducted to reduce the complexity of system design when the number of the receive antennas is no less than the number of transmit antennas. Computer simulations are conducted to corroborate the effectiveness of the proposed channel estimation, and they demonstrate the improved performance compared to the existing training-based estimation.