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With possible new use cases and demanding requirements of future 5th generation (5G) and beyond cellular networks, the future of mobile communications sounds promising. However, the propagation medium has been considered a randomly acting agent between the transmitter and the receiver. With the advent of the digital age of wireless communications, the received signal quality is degrading due to the uncontrollable interactions of the transmitted radio waves with the surrounding artifacts. This paper presents a comprehensive literature review on reconfigurable intelligent surfaces (RISs) and assisted application areas. With the RIS, the network operators can control radio waves’ scattering, reflection, and refraction characteristics by resolving the harmful properties of environmental wireless propagation. Further, the RIS can effectively control the wavefront, such as amplitude, phase, frequency, and even polarization, without requiring complex encoding, decoding, or radio wave processing techniques. Motivated by technological advances, the metasurfaces, reflectarrays, phase shift, and liquid crystals are potential candidates for implementing RIS. Thus, they can be considered the front runner for realizing the 5G and beyond network. Furthermore, the current research activities in the evolving field of wireless networks operated by RIS are reviewed and discussed thoroughly. Finally, to fully explore the potential of RISs in wireless networks, the fundamental research issues to be addressed have been discussed.

Computer Systems Performance Evaluation and Prediction bridges the gap from academic to professional analysis of computer performance.This book makes analytic, simulation and instrumentation based modeling and performance evaluation of computer systems components understandable to a wide audience of computer systems designers, developers.

In this paper, we present a new algorithm to generate two-dimensional (2D) permutation vectors’ (PV) code for incoherent optical code division multiple access (OCDMA) system to suppress multiple access interference (MAI) and system complexity. The proposed code design approach is based on wavelength-hopping time-spreading (WHTS) technique for code generation. All possible combinations of PV code sets were attained by employing all permutations of the vectors with repetition of each vector weight (W) times. Further, 2D-PV code set was constructed by combining two code sequences of the 1D-PV code. The transmitter-receiver architecture of 2D-PV code-based WHTS OCDMA system is presented. Results indicated that the 2D-PV code provides increased cardinality by eliminating phase-induced intensity noise (PIIN) effects and multiple user data can be transmitted with minimum likelihood of interference. Simulation results validated the proposed system for an agreeable bit error rate (BER) of 10−9.

Optical code division multiple access (OCDMA) shows limitations in terms of the inefficient bandwidth utilization and low spectral density with one-dimensional (1D) codes. To overcome these limitations, a novel design is presented using a two dimensional (2D) spectral/spatial multiwavelength coding scheme. The proposed code is constructed using a 1D balanced incomplete block design (BIBD) technique. Theoretical and analytical results indicate that the proposed code provided improvement in the number of simultaneous users, code construction, and cross-correlation and minimized noise. Moreover, the bandwidth requirements can be minimized, and it can provide flexibility in addressing code sequences. Finally, results were compared with existing spectral-spatial 2D codes such as diagonal eigenvalue unity (DEU) and 2D diluted perfect difference (DPD). It was observed that the 2D-BIBD code fulfilled optical transmission needs with minimum effective source power (Psr = −27.5 dBm) when compared to 2D-DEU (−26.5 dBm) and 2D-DPD (−25.5 dBm) codes. Overall, our results suggested that the performance of BER for the proposed code was 72% and 22% higher than the existing 2D-DPD and 2D-DEU codes, respectively.

Extracting parameter estimates from noisy observations of an underlying signal is a common problem in many fields. Time delay estimation (TDE) is essential for many areas, such as localization, array processing, and radar. The performance of any estimator is often evaluated via the mean square error (MSE) that can then be compared to analytical MSE lower bounds. In this paper, we first analyze a maximum likelihood (ML) estimator based on the knowledge of noisy second order statistics of the channel. We investigate lower bounds for the time delay estimation error for ultra-wideband ranging systems operating in realistic multipath environments. Based on the Cramer-Rao lower bound (CRLB), we derive analytically a lower bound of the time delay estimation calculated using the Karhunen–Loève decomposition of the estimated channel autocorrelation matrix. Also, we investigate the practical implementation (based on energy detection) of the time delay estimator. In the second part of the paper, we have analyzed the time delay estimation performances with the energy maximization receiver. Simulations are evaluated using a simulated UWB underground mine channel. This can be considered as the first step for a global positioning system for use mining industry.

We present a small and lightweight fully wireless optogenetic headstage capable of optical neural stimulation and electrophysiological recording. The headstage is suitable for conducting experiments with small transgenic rodents, and features two implantable fiber-coupled light-emitting diode (LED) and two electrophysiological recording channels. This system is powered by a small lithium-ion battery and is entirely built using low-cost commercial off-the-shelf components for better flexibility, reduced development time and lower cost. Light stimulation uses customizable stimulation patterns of varying frequency and duty cycle. The optical power that is sourced from the LED is delivered to target light-sensitive neurons using implantable optical fibers, which provide a measured optical power density of 70 mW/mm2 at the tip. The headstage is using a novel foldable rigid-flex printed circuit board design, which results into a lightweight and compact device. Recording experiments performed in the cerebral cortex of transgenic ChR2 mice under anesthetized conditions show that the proposed headstage can trigger neuronal activity using optical stimulation, while recording microvolt amplitude electrophysiological signals.

Large cities’ expanding populations are causing traffic congestion. The maintenance of the city’s road network necessitates ongoing monitoring, growth, and modernization. An intelligent vehicle detection solution is necessary to address road traffic concerns with the advancement of automatic cars. The identification and tracking vehicles on roads and highways are part of intelligent traffic monitoring while driving. In this paper, we have presented how You Only Look Once (YOLO) v5 model may be used to identify cars, traffic lights, and pedestrians in various weather situations, allowing for real-time identification in a typical vehicular environment. In an ordinary or autonomous environment, object detection may be affected by bad weather conditions. Bad weather may make driving dangerous in various ways, whether due to freezing roadways or the illusion of low fog. In this study, we used YOLOv5 model to recognize objects from street-level recordings for rainy and regular weather scenarios on 11 distinct classes of vehicles (car, truck, bike), pedestrians, and traffic signals (red, green, yellow). We utilized freely available Roboflow datasets to train the proposed system. Furthermore, we used real video sequences of road traffic to evaluate the proposed system’s performance. The study results revealed that the suggested approach could recognize cars, trucks, and other roadside items in various circumstances with acceptable results.

This paper analyzes the error probability performance of low‐density parity‐check (LDPC) coded generalized frequency division multiplexing (GFDM) systems over Rayleigh fading and additive white Gaussian noise (AWGN) channels. The initial log‐likelihood ratio (LLR) expressions used in the sum‐product algorithm (SPA) decoder are first derived for the system model presented in this paper. Based on the decoding threshold of the system, the frame error rate (FER) in the low Eb/N0 $E_b/N_0$region is estimated by modeling the channel variations using the observed bit error rate (BER). Then, a lower bound based on the absorbing sets is proposed for FER when quantized SPA decoders are used. For AWGN channels, the lower bound can act as an estimate of the FER in the error‐floor region if the absorbing set is dominant and its multiplicity is known. For Rayleigh channels, the lower bound can still be used to estimate the FER performance of selected codes. The estimation approach for the FER in the low Eb/N0 $E_b/N_0$region and the lower bound on the FER in the high Eb/N0 $E_b/N_0$region can be used as practical tools for evaluating different designs of GFDM‐based systems in terms of the error probability performance. The quantization scheme has an important impact on the FER and BER performances. Randomly constructed and array‐based LDPC codes are used to obtain numerical results that show the system performance and the accuracy of the proposed FER estimations.

In this paper, low-complexity channel estimators and precoders are proposed for massive multiple-input multiple-output generalized frequency division multiplexing (MIMO-GFDM) systems. In order to combat the effect of non-orthogonality in GFDM, interference-free pilots are used in frequency-domain minimum mean square error (MMSE) channel estimation. Polynomial expansion is used to approximately compute the matrix inverses in the conventional MMSE estimation and precoding, consequently reducing the cubic computational complexity to square order. The degree of the matrix polynomial can be properly selected to get a required trade-off between complexity and estimation/precoding performance. Different weights can be assigned to the terms in the polynomial expansion and be optimized to achieve a minimal mean square error (MSE). Derived limits on the MSE of the proposed estimators can predict their performance in the high E s / N 0 region. Then, we derive a Cramér-Rao lower bound (CRLB) and use it as a benchmark for the estimators. In addition, the related computational complexity and the impacts of the polynomial degree are also investigated. Numerical results show the accuracy of the proposed channel estimators and precoders.

In this paper, a union bound on the bit error rate (BER) for multiple input multiple output generalized frequency division multiplexing (MIMO-GFDM) systems is derived based on exact pairwise error probabilities. The moment-generating function is used to calculate the exact pairwise error probability under the assumption that a maximum likelihood detector is used at the receiver. A realistic multipath MIMO channel environment is investigated in which the spatial correlation between antennas and the channel estimation errors are included. The Kronecker model and an additive model are used to describe the spatial correlation and channel estimation errors, respectively. The impacts of the spatial correlation and the channel estimation errors on the derived bound are investigated. The performances of MIMO-GFDM systems using different modulation techniques are also examined. Numerical calculations of the union bound and computer-based Monte-Carlo simulations of BER are carried out to verify the derived bound. Numerical results show that the derived union bound is a tight upper bound on the BER for MIMO-GFDM systems in a reasonable E s / N 0 region.