Correlated Block Fading Research Articles

Joint estimation-decoding approach based on factor graph expectation maximization algorithm over correlated block fading channels

To deal with the channel uncertainty of the correlated block fading channels,a joint estimation-decoding approach based on Factor Graph Expectation Maximization(FGEM) algorithms was proposed.In the receiver,a message passing method on factor graph was adopted to jointly estimate the channel and decode the message.EM algorithm was used to remove the effect of loops on the convergence of message passing.It also solved the calculation problem of Gaussian mixture message.The calculation of message passing was simplified by the Kalman forward-backward algorithm,which resulted in reduced complexity in joint estimation-decoding.The simulation results show that the proposed algorithm can improve the accuracy of the channel estimation and improve the decoding performance.

Application layer ARQ for protecting video packets over an indoor MIMO-OFDM link with correlated block fading

The quality of experience (QoE) of IP-packetized streaming video is affected by both packet loss and packet delay variations. When the network delivering the video content contains a wireless link, occasional deep fades give rise to bursts of packet losses. In order to maintain a sufficient video QoE at the end user, video packets must be protected against losses by means of a suitable form of error control. In this contribution, we consider an indoor radio MIMO-OFDM transceiver operating over a Rayleigh block-fading channel with arbitrary correlation in the time and frequency dimensions, which makes use of an application layer Automatic Repeat reQuest (ARQ) protocol to provide additional protection of the video content against packet loss. We analyze the resulting residual packet loss performance, under a latency constraint imposed by the requirement of a small TV channel switching delay. This analysis makes direct use of the fading characterization (correlation functions in time and frequency dimensions) of the indoor environment, rather than relying on a Markov model that only approximately describes the packet loss process. Numerical results are obtained by Monte Carlo integration combined with an efficient importance sampling technique devised for the problem at hand. Assuming a 2.4 GHz wireless link, we point out how to select the system parameters (number of antennas, number of retransmissions) in order to achieve a residual packet loss performance yielding a satisfactory QoE for HDTV transmission.

A New Union Bound on the Error Probability of Binary Coded OFDM Systems in Wireless Environments

Orthogonal Frequency Division Multiplexing (OFDM) systems are commonly used to mitigate frequency-selective multipath fading and provide high-speed data transmission. In this paper, we derive new union bounds on the error probability of a coded OFDM system in wireless environments. In particular, we consider convolutionally coded OFDM systems employing single and multiple transmit antennas over correlated block fading (CBF) channels with perfect channel state information (CSI). Results show that the new union bound is tight to simulation results. In addition, the bound accurately captures the effect of the correlation between sub-carriers channels. It is shown that as the channel becomes more frequency-selective, the performance get better due to the increased frequency diversity. Moreover, the bound also captures the effect of multi-antenna as space diversity. The proposed bounds can be applied for coded OFDM systems employing different coding schemes over different channel models.

Training-based estimation of correlated MIMO fading channels in the presence of colored interference

In this paper, training-based estimation of correlated block fading channels in a multiple-antenna, multi-user environment is considered. The linear minimum mean squared error (LMMSE) estimator is presented first. The problem of optimally designing the training data set, so as to minimize the mean squared channel estimation error subject to a total transmit power constraint, is then addressed. The design is based on the assumption of the availability of the channel and interference second-order statistics at the transmitter. It is shown that the optimal transmission directions are dictated jointly by the eigen-decompositions of the channel and interference covariance matrices. Their roles, in the channel estimation and interference suppression tasks, respectively, are revealed in the optimal transmit beamformer structure. The simulation results demonstrate that the gain in the estimation performance from using the optimal training sequence increases considerably with increasing spatial fading correlation, especially in strong interference environments.