High Data Rate Wireless Transmission Research Articles

Diversity-Enabled and Power-Efficient Transceiver Designs for Peak-Power-Limited SIMO-OFDM Systems

Orthogonal frequency division multiplexing (OFDM) has been widely adopted for high data rate wireless transmissions. By deploying multiple receiving antennas, single-input multiple-output- (SIMO-) OFDM can further enhance the performance with spatial diversity. However, due to the large dynamic range of OFDM signals and the nonlinear nature of analog components, it is pragmatic to model the transmitter with a peak-power constraint. A natural question to ask is whether SIMO-OFDM transmissions can still enjoy the antenna diversity in this case. In this paper, the effect of the peak-power limit on the error performance of uncoded SIMO-OFDM systems is studied. In the case that the receiver has no information about the transmitter nonlinearity, we show that full antenna diversity can still be collected by carefully designing the transmitters, while the receiver performs a maximum ratio combining (MRC) method which is implemented the same as that in the average power constrained case. On the other hand, when the receiver has perfect knowledge of the peak-power-limited transmitter nonlinearity, zero-forcing (ZF) equalizer is able to collect full antenna diversity. In addition, an iterative method on joint MRC and clipping mitigation is proposed to achieve high performance with low complexity.

Robust and Improved Channel Estimation Algorithm for MIMO-OFDM Systems

Multiple-input multiple-output (MIMO) system using orthogonal frequency division multiplexing (OFDM) technique has become a promising method for reliable high data-rate wireless transmission system in which the channel is dispersive in both time and frequency domains. Due to multiple cochannel interferences in a MIMO system, the accuracy of channel estimation is a vital factor for proper receiver design in order to realize the full potential performance of the MIMO-OFDM system. A robust and improved channel estimation algorithm is proposed in this paper for MIMO-OFDM systems based on the least squares (LS) algorithm. The proposed algorithm, called improved LS (ILS), employs the noise correlation in order to reduce the variance of the LS estimation error by estimating and suppressing the noise in signal subspace. The performance of the ILS channel estimation algorithm is robust to the number of antennas in transmit and receive sides. The new algorithm attains a significant improvement in performance in comparison with that of the regular LS estimator. Also, with respect to mean square error criterion and without using channel statistics, the ILS algorithm achieves a performance very close to that of the minimum mean square error (MMSE) estimator in terms of the parameters used in practical MIMO-OFDM systems. A modification of the ILS algorithm, called modified ILS (MILS), is proposed based on using the second order statistical parameters of channel. Analytically, it is shown that the MILS estimator achieves the exact performance of the MMSE estimator. Due to no specific data sequences being required to perform the estimation, in addition to the training mode, the proposed channel estimation algorithms can also be extended and used in the tracking mode with decision-aided method.

LDPC-based space-time coded OFDM systems: Turbo-EM receiver design with channel state information guessing algorithms

In this paper we study some turbo receiver architectures employing low-density parity check (Ldpc) codes together with orthogonal frequency division multiplexing (Ofdm) for high data rate wireless transmissions. Different demodulation schemes based on expectation-maximization (Em) algorithm are studied along with the channel impulse response (Em) algorithms. We studied differentCir guessing algorithms including the EM-based algorithms such as a space-alternating generalized expectation-maximization algorithm (Sage). It is shown that the proposed turbo-Em receiver employing a soft maximum a posteriori (Map)Em demodulator and a belief propagationLdpc decoder can perform within 1 dB from the ergodic capacity of the studiedMimo ofdm channels. Besides, we find that a suboptimum structure based on a soft interference cancellationMmse filtering demodulator exhibits negligible loss in non-correlated fadingMimo channels but suffer extra performance loss in highly correlatedMimo channels.

Broadband MIMO-OFDM wireless communications

Orthogonal frequency division multiplexing (OFDM) is a popular method for high data rate wireless transmission. OFDM may be combined with antenna arrays at the transmitter and receiver to increase the diversity gain and/or to enhance the system capacity on time-varying and frequency-selective channels, resulting in a multiple-input multiple-output (MIMO) configuration. The paper explores various physical layer research challenges in MIMO-OFDM system design, including physical channel measurements and modeling, analog beam forming techniques using adaptive antenna arrays, space-time techniques for MIMO-OFDM, error control coding techniques, OFDM preamble and packet design, and signal processing algorithms used to perform time and frequency synchronization, channel estimation, and channel tracking in MIMO-OFDM systems. Finally, the paper considers a software radio implementation of MIMO-OFDM.

Performance Analysis and Design Optimization of LDPC-Coded MIMO OFDM Systems

We consider the performance analysis and design optimization of low-density parity check (LDPC) coded multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems for high data rate wireless transmission. The tools of density evolution with mixture Gaussian approximations are used to optimize irregular LDPC codes and to compute minimum operational signal-to-noise ratios (SNRs) for ergodic MIMO OFDM channels. In particular, the optimization is done for various MIMO OFDM system configurations, which include a different number of antennas, different channel models, and different demodulation schemes; the optimized performance is compared with the corresponding channel capacity. It is shown that along with the optimized irregular LDPC codes, a turbo iterative receiver that consists of a soft maximum a posteriori (MAP) demodulator and a belief-propagation LDPC decoder can perform within 1 dB from the ergodic capacity of the MIMO OFDM systems under consideration. It is also shown that compared with the optimal MAP demodulator-based receivers, the receivers employing a low-complexity linear minimum mean-square-error soft-interference-cancellation (LMMSE-SIC) demodulator have a small performance loss (< 1dB) in spatially uncorrelated MIMO channels but suffer extra performance loss in MIMO channels with spatial correlation. Finally, from the LDPC profiles that already are optimized for ergodic channels, we heuristically construct small block-size irregular LDPC codes for outage MIMO OFDM channels; as shown from simulation results, the irregular LDPC codes constructed here are helpful in expediting the convergence of the iterative receivers.