Performance Of Linear Equalizers Research Articles

Neural Network-Based Joint Spatial and Temporal Equalization for MIMO-VLC System

The limited bandwidth of white light-emitting diode (LED) limits the achievable data rate in a visible light communication (VLC) system. A number of techniques, including multiple-input-multiple-output (MIMO) system, are investigated to increase the data rate. The high-speed optical MIMO system suffers from both spatial and temporal cross talks. The spatial cross-talk is often compensated by the MIMO decoding algorithm, while the temporal cross talk is mitigated using an equalizer. However, the LEDs have a non-linear transfer function and the performance of linear equalizers are limited. In this letter, we propose a joint spatial and temporal equalization using an artificial neural network (ANN) for an MIMO-VLC system. We demonstrate using a practical imaging/non-imaging optical MIMO link that the ANN-based joint equalization outperforms the joint equalization using a traditional decision feedback as ANN is able to compensate the non-linear transfer function as well as cross talk.

Diversity Analysis for Linear Equalizers over ISI Channels

It has been shown in the literature that, with zero-padding prefix (ZPP), the optimum diversity gain of frequency selective channels can be obtained by uncoded signals and zero forcing (ZF) equalizers. In this paper, we derive two important results about linear equalizers over frequency selective channels: 1) With cyclic prefix and any rate-1 unitary precoding, which includes the uncoded/coded-OFDM/SCFDMA systems as special cases, linear equalizers can only obtain order-1 diversity; and 2) Although linear equalizers can achieve the optimum diversity order with zero-padding prefix and uncoded signals, the required SNR (signal-to-noise ratio) is an increasing function of the symbol-length. The second result implies that we may not be able to take advantage of the diversity gain in practice due to the high SNR requirements. Special cases are also investigated to gain some physical insights about the effects of different prefixes on the performance of linear equalizers. The results in this paper can be utilized in the design of up/down-link LTE systems with linear equalizers.

Lattice-reduction aided equalization for OFDM systems

Orthogonal frequency division multiplexing (OFDM) is an effective technique to deal with frequency-selective channels since it facilitates low complexity equalization and decoding. Many existing OFDM designs successfully exploit the multipath diversity offered by frequency-selective channels. However, most of them require maximum likelihood (ML) or near-ML detection at the receiver, which is of high complexity. On the other hand, empirical results have shown that linear detectors have low complexity but offer inferior performance. In this paper, we analytically quantify the diversity orders of linear equalizers for linear precoded OFDM systems, and prove that they are unable to collect full diversity. To improve the performance of linear equalizers, we further propose to use a lattice reduction (LR) technique to help collect diversity. The LR-aided linear equalizers are shown to achieve maximum diversity order (i.e., the one collected by the ML detector), but with low complexity that is comparable to that of conventional linear equalizers. The theoretical findings are corroborated by simulation results.