An iterative receiver for a multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system is considered to jointly decode the transmitted bits and estimate the channel state. The receiver consists of the a posteriori probability (APP) algorithm, the repeat-accumulate (RA) decoder, and the least-squares (LS) channel estimator. An obvious problem, with more than two blocks in an iterative receiver, is to find the optimal activation schedule of the different blocks. This paper proposes to use extrinsic information transfer (EXIT) charts to characterize the behavior of the receiver blocks and find out the optimal activation schedule for them. A semi-analytical expression of the EXIT function is derived for the decision directed LS channel estimator. An algorithm is proposed to generate the EXIT function of the APP algorithm as a function of channel estimate mutual information (MI). Surface fitting is used to get closed form expressions for the EXIT functions of the APP algorithm and the RA decoder. Trellis search based algorithms are shown to find the convergence with the lowest possible complexity using the EXIT charts. With the proposed concept, the activation scheduling can be adapted to prevailing channel circumstances and unnecessary iterations will be avoided.

An iterative receiver for a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system is considered to jointly decode the transmitted bits and estimate the channel state. The receiver consists of the a posteriori probability (APP) algorithm, the repeat-accumulate (RA) decoder, and the least-squares (LS) channel estimator. An obvious problem, with more than two blocks in an iterative receiver, is to find the optimal activation schedule of the different blocks. This paper proposes to use extrinsic information transfer (EXIT) charts to characterize the behavior of the receiver blocks and find out the optimal activation schedule for them. An analytical expression of the EXIT function is derived for the LS channel estimator. An algorithm is proposed to generate the EXIT function of the APP algorithm as a function of channel estimate mutual information (MI). Surface fitting is used to get closed form expressions for the EXIT functions of the APP algorithm and the RA decoder. A trellis search based algorithm is shown to find the convergence with the lowest possible complexity using the EXIT charts. With the proposed concept, the activation scheduling can be adapted to prevailing channel circumstances and unnecessary iterations will be avoided.

A decision directed (DD) channel estimation is considered for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system to improve the spectral efficiency. Unlike in the pilot based channel estimation, the least-squares (LS) channel estimator operating in the DD mode for MIMO-OFDM requires a matrix inversion. The size of the matrix to be inverted depends on the number of transmit antennas and the length of the channel impulse response. The frequency domain (FD) space-alternating generalized expectation-maximization (SAGE) channel estimator calculates the LS estimate iteratively avoiding the matrix inversion with a constant envelope modulation. The drawback with the FDSAGE channel estimator is the required matrix inversion with a non-constant envelope modulation. The size of the matrix to be inverted depends on the length of the channel impulse response. However, it is considerably less complex than the LS channel estimator in the DD mode. In this paper, a time domain (TD) SAGE channel estimator is derived to avoid the matrix inversion in DD channel estimation for MIMO-OFDM systems when using non-constant envelope modulation. The derived TDSAGE channel estimator is shown to offer the same performance as the FD-SAGE channel estimator with reduced complexity.

An iterative receiver design using a space-alternating generalized expectation-maximization (SAGE) based list detection and channel estimation for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system is considered. A new SAGE based list detection algorithm is proposed to operate as a receiver front-end to approximate the MAP algorithm with reduced complexity and with minor losses in the performance. The receiver front-end, a decoder, and a channel estimator constitute an iterative receiver to jointly decode the transmitted bits and to estimate the channel state. The proposed receiver front-end shows a good performance when compared to the other MAP approximation, i.e., to the K-best list sphere detector (LSD) and a linear front-end. Furthermore, the whole iterative receiver performs well with the low pilot overhead despite the fast fading channel.

Multiple-input multiple-output (MIMO) communications based on multiple transmit and receive antennae will be applied to enhance the data rates of the third generation (3G) cellular systems or wideband code division multiple access (WCDMA) and in particular, their high speed downlink packet access (HSDPA) services. This causes both spatial multiplexing interference (SMI) and downlink multiple access interference (MAI). In this paper, we derive an improved linear minimum mean square error (LMMSE) detector approximation suitable for MIMO-WCDMA systems. We also propose a new two-stage receiver architecture to suppress the effects of both MAI and SMI in HSDPA communications. SMI often dominates MAI, since it does not benefit from spreading gain. Therefore, a spatial maximum a posteriori (MAP) detector is used to suppress SMI, and a LMMSE based channel equalizer is applied as its front- end. The performance of the resulting LMMSE-MAP receiver structure is studied via Monte Carlo computer simulations with assumptions very realistically mimicking those of the HSDPA specification. The results show that it clearly outperforms the rake receiver or the improved LMMSE equalizer approximation, which, on the other hand, is also shown to be superior to the more conventional LMMSE equalizers.

Expectation-maximization (EM) based joint decoding and channel parameter estimation for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system is considered. A new iterative receiver structure is proposed to operate together with space-frequency turbo coded modulation (SFTuCM) using decoder outputs to refine the channel parameter estimates. The proposed receiver performs well with low pilot overhead despite the fast changing channel state. The proposed receiver improves not only the error probability performance but remarkable improvement is achieved in the channel parameter estimation accuracy when compared to pilot based estimation with the same overhead