Adaptive Semi-blind Channel Estimation for ST-BC MIMO-CDMA Systems with Hybrid User Signature

[[abstract]]we extend our previous work to present a new semi-blind transceiver for the direct-sequence code division multiple access (DS-CDMA) system that uses multiple transmit and receive antennas (MIMO) system, equipped with space-time block code (ST-BC). In the transmitter we design a new hybrid augmented user signature (AUS) that composes of the desired user signatures and the prefix/postfix zero-padding sequences with respect to individual transmit-antennas. The hybrid AUS is devised to resolve the phase ambiguity problem which occurs in all blind receivers. At the receiver we propose a Capon-like semiblind two-branch filter bank receiver, based on the linearly constrained constant modulus (LCCM) criterion, followed by the AUS-assisted semi-blind channel estimation and power method for block symbol recovery. This enables us to partially alleviate the effects of inter-block interference (IBI) and the multiple access interference (MAI). In the ST-BC MIMO-CDMA receiver with two-branch filterbank, we build on the generalized sidelobe canceller (GSC) structure with the RLS for implementing the adaptive semi-blind LCCM receiver. Via intense simulations it reveals that our proposed new transceiver has robust performance against the user’s acquisition inaccuracies comparing with current vailable algorithms and to resolve the phase ambiguity problem.[[sponsorship]]IEEE Circuits and Systems Society; IEICE ESS (Institute of Electronics, Information and Communication Engineers - Engineering Sciences Society); Tokyo City University; International Exchange Program of National Institute of Information and Communications Technology (NICT); Support Center for Advanced Telecommunications Technology Research, Foundation; Tateisi Science and Technology Foundation[[incitationindex]]EI[[conferencetype]]國際[[conferencedate]]20131112~20131115[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Okinawa, Japa

All-adaptive blind matched filtering for the equalization and identification of multipath channels: a practical approach

Blind matched filter receiver is advantageous over the state-of-the-art blind schemes due the simplicity in its implementation. To estimate the multipath communication channels, it uses neither any matrix decomposition methods nor statistics of the received data higher than the second order ones. On the other hand, the realization of the conventional blind matched filter receiver requires the noise variance to be estimated and the equalizer parameters to be calculated in state-space with relatively costly matrix operations. In this paper, a novel architecture is proposed to simplify a potential hardware implementation of the blind matched filter receiver. Our novel approach transforms the blind matched filter receiver into an all-adaptive format which replaces all the matrix operations. Furthermore, the novel design does not need for any extra step to estimate the noise variance. In this paper we also report on a comparative channel equalization and channel identification scenario, looking into the performances of the conventional and our novel all-adaptive blind matched filter receiver through simulations

Signal-perturbation-free semi-blind channel estimation for MIMO-OFDM systems

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) has been considered as a strong candidate for the beyond 3G (B3G) wireless communication systems, due to its high data-rate wireless transmission performance. It is well known that the advantages promised by MIMO-OFDM systems rely on the precise knowledge of the channel state information (CSI). In real wireless environments, however, the channel condition is unknown. Therefore, channel estimation is of crucial importance in MIMO-OFDM systems. Semi-blind channel estimation as a combination of the training-based or pilot-assisted method and the pure blind approach is considered to be a feasible solution for practical wireless systems due to its better estimation accuracy as well as spectral efficiency. In this thesis, we address the semi-blind channel estimation issue of MIMO-OFDM systems with an objective to develop very efficient channel estimation approaches. In the first part of the dissertation, several nulling-based semi-blind approaches are presented for the estimation of time-domain MIMO-OFDM channels. By incorporating a blind constraint that is derived from MIMO linear prediction (LP) into a training-based least-square method, a semi-blind solution for the time-domain channel estimation is first obtained. It is revealed through a perturbation analysis that the semi-blind solution is not subject to signal perturbation and therefore is superior to pure blind estimation methods. The LP-based semi-blind method is then extended for the channel estimation of MIMO-OFDM systems with pulse-shaping. By exploiting the pulse-shaping filter in the transmitter and the matched filter in the receiver, a very efficient semi-blind approach is developed for the estimation of sampling duration based multipath channels. A frequency-domain correlation matrix estimation algorithm is also presented to facilitate the computation of time-domain second-order statistics required in the LP-based method. The nulling-based semi-blind estimation issue of sparse MIMO-OFDM channels is also addressed. By disclosing and using a relationship between the positions of the most significant taps (MST) of the sparse channel and the lags of nonzero correlation matrices of the received signal, a novel estimation approach consisting of the MST detection and the sparse channel estimation, both in a semi-blind fashion, is developed. An intensive simulation study of all the proposed nulling-based methods with comparison to some existing techniques is conducted, showing a significant superiority of the new methodologies. The second part of the dissertation is dedicated to the development of two signal-perturbation-free (SPF) semi-blind channel estimation algorithms based on a novel transmit scheme that bears partial information of the second-order statistics of the transmitted signal to receiver. It is proved that the new transmit scheme can completely cancel the signal perturbation error in the noise-free case, thereby improving largely the estimation accuracy of correlation matrix for channel estimation in noisy conditions. It is also shown that the overhead caused by the transmission of the 8PF data is negligible as compared to that of regular pilot signals. By using the proposed transmit scheme, a whitening rotation (WR)-based algorithm is first developed for frequency-domain MIMO-OFDM channel estimation. It is shown through both theoretical analysis and simulation study that the new WR-based algorithm significantly outperforms the conventional WR-based method and the nulling-based semi-blind method. By using MIMO linear prediction, the new WR-based algorithm utilizing the 8PF transmit scheme is then extended for time-domain MIMO-OFDM channel estimation. Computer simulations show that the proposed signal-perturbation-free LP-based semi-blind solution performs much better than the LP semi-blind method without using the proposed transmit scheme, the LS method as well as the nulling-based semi-blind method in terms of the MSE of the channel estimate