Brain-computer interfaces (BCIs) establish a direct communication channel between the human brain and external devices. Among various methods, electroencephalography (EEG) stands out as the most popular choice for BCI design due to its non-invasiveness, ease of use, and cost-effectiveness. This paper aims to present and compare the accuracy and robustness of an EEG system employing one or two channels. We present both hardware and algorithms for the detection of open and closed eyes. Firstly, we utilize a low-cost hardware device to capture EEG activity from one or two channels. Next, we apply the discrete Fourier transform to analyze the signals in the frequency domain, extracting features from each channel. For classification, we test various well-known techniques, including Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Decision Tree (DT), or Logistic Regression (LR). To evaluate the system, we conduct experiments, acquiring signals associated with open and closed eyes, and compare the performance between one and two channels. The results demonstrate that employing a system with two channels and using SVM, DT, or LR classifiers enhances robustness compared to a single-channel setup and allows us to achieve an accuracy percentage greater than 95% for both eye states.

In this work, we develop open source hardware and software for eye state classification and integrate it with a protocol for the Internet of Things (IoT). We design and build the hardware using a reduced number of components and with a very low-cost. Moreover, we propose a method for the detection of open eyes (oE) and closed eyes (cE) states based on computing a power ratio between different frequency bands of the acquired signal. We compare several real- and complex-valued transformations combined with two decision strategies: a threshold-based method and a linear discriminant analysis. Simulation results show both classifier accuracies and their corresponding system delays.

This work proposes an Hybrid Precoding (HP) method in a Multiple-Input/Multiple-Output (MIMO) system with the objective of reducing the computational complexity inherent to nonlinear precoding methods. We show that linear precoders work better for low Signal-to- Noise Ratio (SNR) while nonlinear precoders, as in the case of the nonlinear Tomlinson-Harashima (TH) precoders, are more adequate for high SNRs. For medium scenarios, we propose a decision scheme where the transmitter decides to implement either linear or TH precoding depending on the speed of channel variations. Therefore, if the channel is bad, i.e. channel variations are significant compared to a given threshold parameter, the transmitter decides to use TH precoding for pre-equalizing channel effects. Otherwise, in case of good channel conditions, i.e. slow channel variations according to such threshold, linear precoding is enough to ensure good performance with the advantage of avoiding the complexity inherent to TH precoding. The overall performance is evaluated considering the transmission of several images.

ABSTRACT We propose the use of low‐rate layered serially concatenated low‐density generator matrix (SCLDGM) codes in interleave‐division multiple access (IDMA) systems to approach the multiuser capacity. We study the behavior of the soft interference cancellation (SIC) detector employed in IDMA systems and design the channel codes using EXtrinsic Information Transfer (EXIT) evolution, aiming at optimizing the system performance. Simulation results show that the designed codes approach the theoretical limits and outperform previous IDMA schemes based on Turbo‐Hadamard codes. Copyright © 2010 John Wiley & Sons, Ltd.

Recently, the use of analog joint source-channel coding for the transmission of data samples at high rates over AWGN channels has been proposed in the literature. Simulation results have shown that this analog scheme performs close to the theoretical limits for several source distributions and transmission rates. In this paper we study the performance of such a system in comparison with optimized capacity approaching digital Bit Interleaved Coded Modulation (BICM) schemes. We show that in practical situations the analog transmission performs better than the digital scheme with a much lower encoding and decoding complexity when considering Gaussian and Laplacian source distributions.

Recently, analog joint source-channel coding has been proposed as a means of achieving near-optimum performance for high data rates with a very low complexity. However, no experimental evaluation showing the practical feasibility of this scheme has been performed to date. In this paper, we describe a software-defined radio implementation of an analog joint source-channel coded wireless transmission system. Experimental evaluation carried out in an indoor environment making use of a wireless testbed show that the performance perfectly matches that originally reported by simulations in additive white Gaussian noise channels for signal-to-noise ratio values below 20 dB.

We study the ability of low-rate Serially-Concatenated Low Density Generator Matrix (SCLDGM) codes to approach theoretical limits. Although two layer SCLDGM codes approach capacity for medium rates (0.25 <; R <; 0.9), they do not perform adequately for lower rates. In this case, substantial performance improvements are obtained using three layers.

Abstract We analyze Multiple‐Input Multiple‐Output (MIMO) coded modulation systems where either Bit‐Interleaved Coded Modulation (BICM) with spatial multiplexing or concatenation of channel coding and Space‐Time Block Codes (STBCs) is used at transmission, assuming iterative Turbo‐like decoding at reception. We optimize Serially‐Concatenated Low‐Density Generator Matrix (SCLDGM) codes (a subclass of LDPC codes) for each system configuration, with the goal of assessing its ability to approach the capacity limits in either ergodic or quasi‐static channels. Our focus is on three relevant STBCs: the Orthogonal Space‐Time Block Codes (OSTBCs) for two transmit antennas (i.e., the Alamouti code), which enables optimum detection with low complexity; the Golden code, which provides a capacity increase with respect to the input constellation; and Linear Dispersion (LD) codes, which enable practical detection in asymmetrical antenna configurations (i.e., more transmit than receive antennas) for cases in which optimum detection is infeasible. We conclude that BICM without concatenation with STBCs is in general the best option, except for Alamouti‐coded 2×1 and Golden‐coded 2×2 MIMO systems. Copyright © 2009 John Wiley & Sons, Ltd.

Design of MIMO capacity-approaching codes relies on matching the extrinsic information transfer (EXIT) functions of the code and the detector. We focus on list sphere detection (LSD) because it presents the best performance/complexity tradeoff. We obtain the EXIT functions of the most representative LSDs: maximum likelihood (ML) and maximum a posteriori (MAP). We then utilize these EXIT functions to design good IRA and SCLDGM codes that perform close to the capacity limits.

Low density generator matrix (LDGM) codes are a particular class of low density parity check (LDPC) codes with very low encoding complexity. Single LDGM codes present high error-floors, which can be substantially reduced with the serial concatenation of two LDGM (SCLDGM) codes. We propose a technique to obtain good SCLDGM codes using extrinsic information transfer (EXIT) functions in a novel way. Although the optimization is performed for AWGN channels with binary signaling, the resulting codes are also optimal for AWGN and perfectly-interleaved Rayleigh fading channels with non-binary signaling and perfect CSI at reception, provided that Gray mapping is utilized. Optimized regular and irregular SCLDGM codes outperform heuristically-designed LDGM codes existing in the literature, and have a performance similar to or better than that of irregular repeat accumulate (IRA) codes.

We investigate the ability of serially-concatenated low density generator matrix (SCLDGM) codes to approach the capacity of ergodic multiple-input multiple-output (MIMO) channels. First, we explain how to design good SCLDGM codes using extrinsic information transfer (EXIT) analysis and optimum detection. However, optimum detection becomes unfeasible in many cases of practical interest where the number of transmitting antennas and/or the number of bits per constellation symbol is large. In this case, we resort to list sphere detection (LSD), considering two versions: maximum likelihood (ML) and maximum a posteriori (MAP). Again, we use EXIT analysis to obtain good SCLDGM codes for these specific LSD versions. We provide examples of optimized rate 1/2 SCLDGM codes and show that they perform within 1 dB from the theoretical capacity limit for a large number of antenna configurations and modulation formats. Finally, we discuss how to iteratively improve channel estimation using the soft information computed during the decoding process. We also show how the complexity of channel estimation is reduced by utilizing the candidate list calculated by the LSD.

In this work we study the ability of regular serially concatenated low-density generator matrix (SCLDGM) codes to approach the capacity of MIMO channels with two transmit antennas. We focus on two schemes: spatial multiplexing in a BICM fashion and concatenation with the Alamouti code. We show that good SCLDGM codes designed for SISO channels also approach MIMO capacity in the Alamouti concatenated scheme. These codes, however, do not perform adequately in spatial multiplexing and, in this case, have to be specifically designed for each antenna configuration and modulation format. Decoding complexity in spatial multiplexing is larger but the performance is in general better because the Alamouti code reduces the MIMO channel capacity when there is more than one receiving antenna