Linear Zero-forcing Equalizer Research Articles

Performance improvement of data transmission using a hybrid underwater and terrestrial system

AbstractIn this paper, we investigate and enhance the performance of data transmission using a hybrid underwater and terrestrial system with low‐complexity linear equalization. Due to the low speed, salinity, water depth, pH degree, and water temperature variations, underwater acoustic communication has become one of the most challenging technologies in the world. The most common linear equalizers are the Linear Zero Forcing (LZF), and Linear Minimum Mean Square Error (LMMSE) equalizers. The LZF equalizer suffers from the noise enhancement problem, while the LMMSE equalizer requires the value of the operating Signal‐to‐Noise Ratio (SNR) to work, correctly, which increases the computational complexity. In addition, this paper presents a low‐complexity equalization scheme to overcome the drawbacks associated with the LZF, and LMMSE equalizers. The proposed equalizer is called the Joint Low‐Complexity Regularized LZF equalizer, which depends on a fixed regularization parameter to minimize the noise enhancement phenomenon caused by the LZF equalizer. The proposed equalizer does not need the estimation of the SNR, and the computational complexity is reduced due to the utilization of the banded‐matrix approximation. The proposed equalizer is implemented based on the Single‐Input‐Single‐Output configuration for Orthogonal Frequency Division Multiplexing (OFDM) using the Discrete Cosine Transform. The obtained simulation results show that the proposed equalizer outperforms different equalizers for the same channel conditions.

Performance Analysis of Amplify-and-Forward Multiple-Relay MIMO Systems With ZF Reception

This paper deals with performance analysis of a cooperative multiple-input–multiple-output (MIMO) network with spatial multiplexing, wherein multiple half-duplex relays perform noncoherent (i.e., without channel state information) amplify-and-forward (AF) relaying, and the destination employs a linear zero-forcing equalizer. The correlation among the noise samples at the destination, the non-Gaussian nature of the dual-hop channel, and the fact that the relays are located in different positions significantly complicates the performance analysis of the system. In the high-signal-to-noise-ratio (SNR) regime, we derive a simple and accurate approximation of the symbol error probability (SEP) at the destination. In the special case of a relaying cluster, such a result allows discussion of the best placement of the relays and the performance gain of cooperation over the direct (i.e., without relaying) transmission. The theoretical analysis is validated by comparison with semianalytical Monte Carlo simulations.

An upper bound on the error probability in decision-feedback equalization

An upper bound on the error probability of a decision-feedback equalizer which takes into account the effect of error propagation is derived. The bound, which assumes independent data symbols and noise samples, is readily evaluated numerically for arbitrary tap gains and is valid for multilevel and nonequally likely data. One specific result for equally likely binary symbols is that if the worst case intersymbol interference when the first <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">J</tex> feedback taps are Set to zero is less than the original signal voltage, then the error probability is multiplied by at most a factor of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2^J</tex> relative to the error probability in the absence of decision errors at high <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S/N</tex> ratios. Numerical results are given for the special case of exponentially decreasing tap gains. These results demonstrate that the decision-feedback equalizer has a lower error probability than the linear zero-forcing equalizer when there is both a high <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S/N</tex> ratio and a fast roll-off of the feedback tap gains.