Iterative channel estimation and turbo equalization for time-varying channels in a coded OFDM-LTE system for 16-QAM and 64-QAM

Abstract

The main targets for the next generation of mobile communication systems, with LTE as a main candidate, are increased data rates and improved spectrum efficiency. The transmission scheme for the LTE downlink is OFDM which enables the design of low complexity and high performance receivers, if the channel is time-invariant. However in highmobility scenarios, where the channel is time-variant, the receiver design is more challenging. Therefore in this paper the turbo equalizer presented in [1] is extended to 16-QAM and 64-QAM to compensate the effect of the time-varying channel. Furthermore an iterative pilot-assisted channel estimator based on DPS-BEM is presented. BER performance of the LTE downlink for the ITU Vehicular A channel shows that the improvement due to iterative processing is substantial.

Two-Tier Channel Estimation Aided Near-Capacity MIMO Transceivers Relying on Norm-Based Joint Transmit and Receive Antenna Selection

“…The challenge of approaching the optimal near-capacity MIMO performance again is the acquisition of accurate MIMO CSI without imposing an excessive pilot-overhead and an excessive channel estimation complexity [21]. The existing stateof-the-art solutions [22]- [31] combine the decision-directed (DD) CE (DDCE) solutions with powerful iterative detection and decoding schemes in order to form semi-blind joint CE and turbo detection-decoding, where only a modest training overhead is required for generating an initial MMSE CE or least squares CE. The most effective schemes [26]- [31] employ soft-decision aided CEs in the semi-blind joint CE and turbo detection-decoding process, which are more robust against error propagation than the hard-decision aided CE schemes.…”

“…The existing stateof-the-art solutions [22]- [31] combine the decision-directed (DD) CE (DDCE) solutions with powerful iterative detection and decoding schemes in order to form semi-blind joint CE and turbo detection-decoding, where only a modest training overhead is required for generating an initial MMSE CE or least squares CE. The most effective schemes [26]- [31] employ soft-decision aided CEs in the semi-blind joint CE and turbo detection-decoding process, which are more robust against error propagation than the hard-decision aided CE schemes. Consequently, these joint soft-decision based CE and turbo detection-decoding schemes are capable of achieving a better overall system performance than their hard-decision based counterparts.…”

Embedded Iterative Semi-Blind Channel Estimation for Three-Stage-Concatenated MIMO-Aided QAM Turbo Transceivers

“…The state-of-the-arts [1]- [16] can be represented by the conventional joint CE and three-stage turbo detector/decoder structure 3 depicted in Fig. 1.…”

“…The most effective schemes [10]- [13], [15], [16] employ soft-decision aided channel estimators, which are more robust against error propagation than the hard-decision aided CE schemes. Consequently, these joint soft-decision based CE and turbo detection/decoding schemes are capable of achieving better overall system-performance than their hard-decision based counterparts.…”

RS Codes for Downlink LTE System over LTE-MIMO Channel

“…The channel in mobile environments is divided into frequency and time selective fading; using OFDM will combat any Inter Symbol Interference (ISI) that occurs [5]. An orthogonal Frequency Division Multiplexing Access (OFDMA) is used in the transmission scheme for downlink LTE; this is a multi-user version of OFDM [7,8]. When time-invariance exists in the frequency selective channel, OFDM systems support using simple one-tap equalization [9].…”