Efficient implementation of optical scanning holography in cancelable biometrics.

This paper presents a new trend in biometric security systems, which is cancelable multi-biometrics. In general, traditional biometric systems depend on a single biometric for identification. These traditional systems are subject to different types of attacks. In addition, a biometric signature may be lost in hacking scenarios; for example, in the case of intrusion, biometric signatures can be stolen forever. To reduce the risk of losing biometric signatures, the trend of cancelable biometrics has evolved by using either deformed or encrypted versions of biometrics for verification. In this paper, several biometric traits for the same person are treated to obtain a single cancelable template. First, optical scanning holography (OSH) is applied during the acquisition of each biometric. The resulting outputs are then compressed simultaneously to generate a unified template based on the energy compaction property of the discrete cosine transform (DCT). Hence, the OSH is used in the proposed approach as a tool to generate deformed versions of human biometrics in order to get the unified biometric template through DCT compression. With this approach, we guarantee the possibility of using multiple biometrics of the same user to increase security, as well as privacy of the new biometric template through utilization of the OSH. Simulation results prove the robustness of the proposed cancelable multi-biometric approach in noisy environments.

Optical wireless communication performance enhancement using Hamming coding and an efficient adaptive equalizer with a deep-learning-based quality assessment.

Optical wireless communication (OWC) technology is one of several alternative technologies for addressing the radio frequency limitations for applications in both indoor and outdoor architectures. Indoor optical wireless systems suffer from noise and intersymbol interference (ISI). These degradations are produced by the wireless channel multipath effect, which causes data rate limitation and hence overall system performance degradation. On the other hand, outdoor OWC suffers from several physical impairments that affect transmission quality. Channel coding can play a vital role in the performance enhancement of OWC systems to ensure that data transmission is robust against channel impairments. In this paper, an efficient framework for OWC in developing African countries is introduced. It is suitable for OWC in both indoor and outdoor environments. The outdoor scenario will be suitable to wild areas in Africa. A detailed study of the system stages is presented to guarantee the suitable modulation, coding, equalization, and quality assessment scenarios for the OWC process, especially for tasks such as image and video communication. Hamming and low-density parity check coding techniques are utilized with an asymmetrically clipped DC-offset optical orthogonal frequency-division multiplexing (ADO-OFDM) scenario. The performance versus the complexity of both utilized techniques for channel coding is studied, and both coding techniques are compared at different coding rates. Another task studied in this paper is how to perform efficient adaptive channel estimation and hence equalization on the OWC systems to combat the effect of ISI. The proposed schemes for this task are based on the adaptive recursive least-squares (RLS) and the adaptive least mean squares (LMS) algorithms with activity detection guidance and tap decoupling techniques at the receiver side. These adaptive channel estimators are compared with the adaptive estimators based on the standard LMS and RLS algorithms. Moreover, this paper presents a new scenario for quality assessment of optical communication systems based on the regular transmission of images over the system and quality evaluation of these images at the receiver based on a trained convolutional neural network. The proposed OWC framework is very useful for developing countries in Africa due to its simplicity of implementation with high performance.

MIMO Self-Heterodyne OFDM Using Band Selection Technique.

The 5G technology is a promising technology to cope with the increasing demand for higher data rate and quality of service. In this paper, two proposed techniques are implemented for multiple input multiple output (MIMO) self-heterodyne OFDM system to enhance data rate and minimize the bit error rate (BER). In both of the two proposed techniques, Band Selection (BS) approach is used, once with Space Time Block Coded (STBC) for the first proposed technique (BS- STBC), and once again with Frequency Space Time Block Coded (FSTBC) for the second proposed technique (BS-FSTBC). The use of the BS in the proposed techniques helps to choose the sub-band with better subchannels gains for sending the information and consequently, minimize the BER. Moreover, the use of the FSTBC instead of STBC helps to use the spectral efficiently and hence increase data rate. The simulation results show that the proposed techniques BS-STBC and BS-FSTBC, for the MIMO self-heterodyne OFDM system, provide a great enhancement in the BER performance when compared to the conventional techniques. Moreover, the simulation results show that the first proposed technique BS-FSTBC outperform the second propose technique BS-STBC in term of the BER performance.

Two Novel Space-Time Coding Techniques Designed for UWB MISO Systems Based on Wavelet Transform.

In this paper two novel space-time coding multi-input single-output (STC MISO) schemes, designed especially for Ultra-Wideband (UWB) systems, are introduced. The proposed schemes are referred to as wavelet space-time coding (WSTC) schemes. The WSTC schemes are based on two types of multiplexing, spatial and wavelet domain multiplexing. In WSTC schemes, four symbols are transmitted on the same UWB transmission pulse with the same bandwidth, symbol duration, and number of transmitting antennas of the conventional STC MISO scheme. The used mother wavelet (MW) is selected to be highly correlated with transmitted pulse shape and such that the multiplexed signal has almost the same spectral characteristics as those of the original UWB pulse. The two WSTC techniques increase the data rate to four times that of the conventional STC. The first WSTC scheme increases the data rate with a simple combination process. The second scheme achieves the increase in the data rate with a less complex receiver and better performance than the first scheme due to the spatial diversity introduced by the structure of its transmitter and receiver. The two schemes use Rake receivers to collect the energy in the dense multipath channel components. The simulation results show that the proposed WSTC schemes have better performance than the conventional scheme in addition to increasing the data rate to four times that of the conventional STC scheme.

Blind multichannel reconstruction of high-resolution images using wavelet fusion.

We developed an approach to the blind multichannel reconstruction of high-resolution images. This approach is based on breaking the image reconstruction problem into three consecutive steps: a blind multichannel restoration, a wavelet-based image fusion, and a maximum entropy image interpolation. The blind restoration step depends on estimating the two-dimensional (2-D) greatest common divisor (GCD) between each observation and a combinational image generated by a weighted averaging process of the available observations. The purpose of generating this combinational image is to get a new image with a higher signal-to-noise ratio and a blurring operator that is a coprime with all the blurring operators of the available observations. The 2-D GCD is then estimated between the new image and each observation, and thus the effect of noise on the estimation process is reduced. The multiple outputs of the restoration step are then applied to the image fusion step, which is based on wavelets. The objective of this step is to integrate the data obtained from each observation into a single image, which is then interpolated to give an enhanced resolution image. A maximum entropy algorithm is derived and used in interpolating the resulting image from the fusion step. Results show that the suggested blind image reconstruction approach succeeds in estimating a high-resolution image from noisy blurred observations in the case of relatively coprime unknown blurring operators. The required computation time of the suggested approach is moderate.