A Semi-Blind Channel Estimation Method for Multiuser Multiantenna OFDM Systems

Abstract

A subspace-based blind method is proposed for estimating the channel responses of a multiuser and multiantenna orthogonal frequency division multiplexing (OFDM) uplink system. It gives estimations to all channel responses subject to a scalar matrix ambiguity and does not need precise channel order information (only an upper bound for the orders is required). Furthermore, the scalar ambiguity matrix can be easily resolved by using only one pilot OFDM block, given that the number of users is smaller than the number of symbols in the pilot symbol block. Equalization methods are discussed based on the estimated channels. By using partial knowledge of the channels, a multipath subspace method is proposed that reduces the computational complexity. Simulations show that the methods are effective and robust.

Precoder Detection for Cooperative Decode-and-Forward Relaying in OFDMA Systems

“…Furthermore, we explored the use of blind and "semi-blind" MIMO channel estimation techniques to estimate the channel and the precoder matrices combined such as [24][25][26], and then recover the signals. Likewise, we also explored a semi-BSS approach developed for a MIMO-OFDM communication system [27].…”

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

“…For example, Li et al [286] proposed an approach of exploiting both transmitter diversity and the delay profile characteristics of typical mobile channels, which was further simplified and enhanced in [142], [145], and [287], respectively. Other schemes employed MMSE [136], [288], constrained least-squares (CLS) [209], iterative LS [143], [185], QRD-M [184], [289] as well as second-order statistics (SOS)-based subspace estimation [168] or techniques based on the received signal's time-of-arrival (TOA) [190], etc. Some researchers have focused their attention on designing optimum training patterns or structures [142], [144], [290].…”

“…Furthermore, various joint approaches combining channel estimation with data symbol detection at the receiver were also proposed for CDMA [289], [291], SISO OFDM [292] and MIMO OFDM [184], [293] systems. However, in the context of BLAST or SDMA type multiuser MIMO OFDM systems, all channel estimation techniques found in the literature were developed under the assumption of either the underloaded [143], [168], [227], [238], [285], [288], [294] or the fully loaded [144], [184], [190], [209], [261], [293], [295] scenario mentioned above. Unsurprisingly, in rank-deficient MIMO OFDM systems the task of channel estimation becomes extremely challenging, since the associated significant degradation of the rank-deficient MUD's performance will inevitably result in a further degraded performance of the associated channel estimators, especially in decisiondirected type receivers, which are quite sensitive to error propagation [1].…”

Statistical covariance-matching based blind channel estimation for zero-padding MIMO–OFDM systems

“…Blind channel estimation is a technique that alleviates the need for training sequences to identify the unknown channel impulse response from the received signal. Since the requirement of extra bandwidth for training overhead is reduced, this technique has received great research interest [3] and many blind estimation algorithms have been developed for various transmission systems [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. In this article, we will focus on blind estimation of ZP-based MIMO-OFDM systems.…”

“…*Correspondence: yischen@fcu.edu.tw 1 Feng Chia University, Taichung, Taiwan Full list of author information is available at the end of the article For ZP-based single-input single-output (SISO) OFDM systems, a subspace algorithm is proposed to blindly identify the channels in [20], and is then generalized to MIMO cases [21]. However, this approach is known to suffer a sever performance degradation when the signal-to-noise ratio (SNR) is low or moderate [5].…”