A MIMO-OFDM channel estimation approach using time of arrivals

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].…”

Channel estimation for MIMO-OFDM systems in Fast Time-Varying Environments

“…Since the number of samples to estimate Lv is greater than the number of observation equations N R N , it is not efficient to estimate the time-variation of the complex gains, using directly the observation model in (1). Thus, we need to reduce the number of parameters to estimate.…”

“…Various OFDM channel estimation schemes have been proposed in the literature, mostly for single antenna systems [8] [12] [14] [9] [10]. For MIMO-OFDM systems, most of the channel estimation schemes have focused on pilot-assisted approaches [1] [3] [4], based on a quasi-static fading model that allows the channel to be invariant within a MIMO-OFDM block. However, in fast fading channels, the time-variation of the channel within a MIMO-OFDM block results in a loss of subcarrrier orthogonality which leads to intercarrier interference (ICI) [8] [2].…”

Near-Instantaneously Adaptive HSDPA-Style OFDM Versus MC-CDMA Transceivers for WIFI, WIMAX, and Next-Generation Cellular Systems

“…Sun et al [137] contrived CFO estimation assisted expectation maximization (EM) based iterative receivers for MIMO OFDM systems, which may also be further developed for TVTBR-AOFDM systems. Wang et al [138] also Hanzo and Choi: Near-Instantaneously Adaptive HSDPA-Style OFDM Versus MC-CDMA Transceivers considered the MIMO OFDM channel estimation problem, which is quite challenging, since each MIMO link's FDCHTF has to be estimated. For example, for a 6 Â 6-element adaptive MIMO OFDM system a total of 64 FDCHTFs has to be determined.…”