As vehicle-to-everything (V2X) communication becomes essential for autonomous and connected vehicle ecosystems, enhancing performance through advanced multiple access techniques is increasingly vital. This paper introduces a novel cross-layer design integrating non-orthogonal multiple access (NOMA) in the physical (PHY) and medium access control (MAC) layers of cellular V2X (C-V2X) systems, with a focus on improving system throughput, reliability, and resource efficiency. Through analytical modeling and simulation, we evaluate the impact of NOMA-based resource allocation and user pairing strategies compared to traditional orthogonal multiple access (OMA) methods. Simulation results confirm that NOMA significantly boosts throughput and spectral efficiency, particularly in low-to-moderate user densities; however, as the number of users rises beyond 10, interference among far users and the complexity of successive interference cancellation (SIC) for near users present performance trade-offs in packet error rate (PER) and throughput. These findings highlight the need for advanced power allocation, interference management, and hybrid solutions to sustain NOMA's advantages in dense vehicular environments.

Physical-layer security (PLS) is examined in this paper for an underlay cognitive radio network (CRN). Two secondary users (SUs) interact through a relay that is equipped with multiple antennas and harvests energy from the SU transmitter's messages via a power splitting (PS) approach. Communication between the relay and SU destination is being intercepted by several eavesdroppers. Therefore, to diminish the eavesdroppers' interception capabilities, the SU destination gathers energy from relayed messages and exploits it to generate and broadcast jamming signals intended to mislead the eavesdroppers. Colluding and non-colluding eavesdroppers are both considered and contrasted as possible strategies for intercepting private information. Additionally, for a more realistic assumption, the connection between the relay and the legitimate SU receiver is assumed to follow the cascaded Rayleigh fading model. PLS is assessed in terms of the probability of non-zero secrecy capacity and the intercept probability.

The number of road accidents has remained stable in recent years. By using the latest technologies such as vehicle-to-vehicle communications, it is possible to improve road safety and reduce the number of road fatalities, especially for vulnerable road users (VRUs). There are two existing radio access technologies (RAT) for vehicle-to-everything (V2X) communications, i.e., Wi-Fi -based by IEEE (802.11p and its next-generation standard 802.11bd), and cellular-based by 3GPP (LTE-V2X and 5G NR-V2X). Although many works have evaluated and compared the performance of V2V RAT communications, very little work has been done to compare the performance of these technologies in the context of vehicle-VRU communications. In this paper, we present, to the best of our knowledge, the first work that evaluates the performance of each RAT in the context of vehicle-to-pedestrian (V2P) and vehicle-to-cyclist (V2C) communications. Using four performance metrics, namely packet error rate (PER), packet reception rate (PRR), throughput, and latency, we examined whether each RAT can meet the requirements of safety applications intended for implementation in urban areas. The answer to this question is yes. However, each RAT has its own performance profile. In terms of PER and PRR, 802.11bd has an advantage, while in terms of throughput and latency, 5G NR-V2X performs better.

Most research works on frequency-selective (FS) millimeter wave (mmWave) hybrid multiple-input multiple-output (MIMO) systems opted to use orthogonal frequency-division multiplexing (OFDM) waveform, while rare studies adopted filter bank based multicarrier (FBMC) waveform for such systems! Isn't FBMC compatible for mmWave hybrid MIMO systems? In this paper we investigate these inquiries. In which we design orthogonal matching pursuit based hybrid precoding and combining algorithms with limited feedback to adopt FBMC-offset quadrature amplitude modulation (OQAM) signaling for FS mmWave MIMO systems. Simulation results show that FBMC-OQAM can be a feasible candidate signaling waveform for mmWave hybrid MIMO systems.

Error rate analyses of cooperative non-orthogonal multiple access (CNOMA) systems are of paramount importance to investigate the communication reliability for each user and facilitate the development of enhancement algorithms. Although CNOMA has recently attracted great attention, its error performance, particularly that of full-duplex cooperative NOMA (FD-CNOMA), is still underexplored in the literature. In this paper, we investigated the error performance of FD-CNOMA systems under imperfect successive interference cancellation (SIC) and residual self-interference (RSI), where new closed-form expressions of the exact bit error rates (BER) are derived for both users. Through the derived BER expressions, high-SNR analyses are conducted to show that FD-CNOMA has an error floor. Based on the derived expressions, we proposed a novel SINR-based selective FD-relaying, which minimizes the end-to-end (e2e) BER and improves the overall system performance. The analyses are extended to cover pulse-amplitude modulation (PAM) and quadrature-amplitude modulation (QAM) with arbitrary modulation orders. Monte Carlo simulations and numerical results are presented to corroborate the derived analytical expressions and give valuable insights into the error performance of FD-CNOMA systems.

Spectrum sensing (SS) is one of the most challenging and prominent operation in the emerging cognitive radio (CR) technology. It is viewed as one of the most intelligent method for enhancing spectrum usage efficiency. Therefore, versatile SS techniques have been proposed in literature. In this paper, we consider eigenvalue-based spectrum sensing (ESS) approaches, due to their strong competitive performances. An experimental assessment of a set of ESS algorithms is then provided. Our work is motivated by the high need to evaluate the performances of SS in near real-world scenarios, as a first step for industrial integration of this CR feature in existing and future wireless communication systems. Thus, we propose a real-time testbed that relies on the software-defined radio (SDR) platform: the national instrument (NI) 2954R universal software radio peripheral (USRP), as a physical medium for analog transmissions. The different processing modules of the developed testbed have been designed within a scalable and flexible architecture. It includes data acquisition, spectrum sensing, blind estimation of the noise power and performances reporting. Indeed, both of the ESS detection potential and sensing time have been explored. We show that, by conveniently selecting the ESS technique, the detection performances of a CR device can be improved (by 35%) while reducing sensing time (by 2) at relatively low SNR value (-12 dB).

In this paper, we investigate the impact of the covariance matrix (CM) size of the received signal on the performance of spectrum sensing methods. Our analysis is based on two well-known methods of spectrum sensing (SS), one based on the eigenvalues called maximum-to minimum eigenvalue (MME) and the other is based on the beamforming technique called maximum-to-minimum beam energy (MMBE). From an analytical development, we provide an explanation about the gap of detection performance between the two algorithms according to the size of the CM. Finally, we provide some simulations results to show the impacts of the smoothing factor and the number of antennas on the detection performance for both methods. These two parameters define the size of the CM of the received signal.

Here, the authors propose a robust blind digital modulation classification (BDMC) algorithm for space time block coding (STBC)‐based MIMO‐OFDM system in the presence of carrier frequency offset (CFO) and channel estimation errors. Previous papers published on the topic of modulation identification were limited to single‐carrier systems operating over frequency‐flat channels. The problem of joint channel and CFO estimation in conjunction with blind digital modulation classification for STBC‐OFDM in frequency selective channel and in the presence of the impulsive noise has not been addressed before to the best of their knowledge. To cope with performance degradation of BDMC due to CFO and channels errors, they propose joint semi‐blind CFO and channels estimation methods. Higher order statistics (HOS), used for feature extraction, are combined with pattern recognition methods to solve the modulation identification problem. The main contribution of their work is the development of estimators, the study of their impacts on the blind classification capability, and the use of simulations to demonstrate the superior performance of the proposed algorithms.

In this paper, a new spectrum sensing (SS) method, called maximum-to-mean energy detector (MMED), is proposed. Considering a wireless communication system with many angles of arrival (AoA), the suggested method is based on beamforming and the ratio of the maximum energy to the mean one of the received signal. The proposal is totally blind and it does not require the knowledge of the signal, the channel or the noise power. Theoretical development of the detection threshold and the performance analysis of the method are first provided. Then, simulation results show an interesting performance of MMED compared to the well-known blindly combined energy detection (BCED) under very low signal to noise ratio (SNR).

In this paper, we propose an analytical expression in order to fix the threshold of the spectrum sensing algorithm called maximum energy beamforming-output-to-input (MEBOI), that we have proposed recently. The threshold of MEBOI method was estimated using a heavy iterative algorithm. To avoid this issue, a theoretical development based on the probability of false alarm is provided here. Then, the validity of the expression is verified by simulations. After, the complexity order of the MEBOI technique is compared to the well-known maximum-to-minimum eigenvalue (MME) method based on eigenvalue decomposition. Finally, the performance of the proposal is evaluated and compared with existing state of the art algorithms. Simulation results show the ability of our approach to deal with the detection challenge under very low signal-to-noise ratio (SNR).

Classifiers, such as artificial neural networks non‐linear equaliser (ANN‐NLE), Wiener–Hammerstein non‐linear equaliser, Volterra non‐linear equaliser (Volterra‐NLE) and support vector machine non‐linear equaliser (SVM‐NLE), can play a significant role in compensating non‐linear imperfections in the optical communications context. Using classifiers to mitigate the non‐linear effects in coherent optical orthogonal frequency division multiplexing (CO‐OFDM) systems is an interesting idea to be investigated. In this study, a novel support vector machine robust version, specifically adapted to a 100 Gb/s CO‐OFDM data structure for long haul distance, is proposed. Firstly, the authors demonstrate that SVM‐NLE upgrades the system performance by about 10 −1 in terms of bit‐error rate compared to Volterra‐NLE at optical signal‐to‐noise ratio equal to 14 dB. Then, they show that it can double the transmission distance up to 1600 km over single mode fibre channel. Furthermore, a performance comparison is performed using 16 quadrature amplitude modulation and 40 Gb/s bit rate for SVM‐NLE, ANN‐NLE and inverse Volterra series transfer function non‐linear equaliser, respectively.

Modulation recognition is crucial for a good environmental awareness required by cognitive radio systems. In this study, the authors design and compare models of four among the most commonly used classifiers for feature‐based automatic modulation classification (FB‐AMC) algorithms. Classifiers whose models will be designed are classification tree, K ‐nearest neighbours, artificial neural networks (ANNs), and support vector machines. In this study, they apply some statistical pattern recognition techniques in the context of blind FB‐AMC over multiple‐input–multiple‐output channels. Comparison criteria are classification accuracy and computational complexity. To improve the impartiality of this comparison, each classifier is optimally deployed by selecting its optimal model with respect to their context. Model selection for the classifiers is done using the ‘ k ‐fold cross‐validation’ model validation technique. The comparison study, within the considered context, shows that ANN classifiers have the best performance/complexity tradeoff.

In this paper, we study the performance of time hopping pulse position modulation for impulse radio ultra-wideband. We consider relay network applying decode-and-forward protocol. The channels between nodes adopt the IEEE 802.15.4a norms. The bit error rate performance is analyzed considering the effect of interference. Our results show significant improvement due to the diversity gain provided by the relay nodes. However, the performance is limited when multiple access interference (MAI) is present. To combat the MAI effect and further improve the detection reliability, we propose to use antenna selection at the relay. The relay receiver is assumed to be equipped with multiple antennas, and only the best antenna is selected. This is shown to improve the performance in the presence of MAI and improve the diversity gain

Early detection of primary users presence is one of the most important tasks for cognitive communication. Also, in cognitive settings cognitive nodes may receive signals from primary users and from other cognitive users simultaneously. For such scenario, we propose primary user signal detection using modulation class identification method. We consider multiple transmit and multiple receive antennas for cognitive nodes. We employ Artificial Neural Network (ANN) for the modulation identification purpose. The proposed algorithm works as higher order moments and cumulants are calculated from the received signal samples at each of the receiving branches of cognitive nodes. After this step, these features are fed to the ANN to determine the presence of primary users. Final identification decision is drawn using the decision from all receiving branches. We also present numerical results of our algorithm and compare these results with the theoretical results of the energy detection algorithm.

In this study, under imperfect channel state information in Rayleigh fading channels, the authors analyse a previously proposed distributed turbo coded cooperative scheme based on parallel concatenated convolutional codes and soft‐decode‐and‐forward mode. For coherent binary phase shift keying over independent Rayleigh fading channels, the authors assume that the imperfect estimation errors are Gaussian distributed having a variance equal to a fraction of the variance of normalised Rayleigh distribution. Using the transfer function approach, the authors define an upper bound of the pairwise error probability to compute the average union upper bound for the bit error probability.

In this paper, we investigate a cross-layer approach for optical multiple input multiple output (O-MIMO) systems, using mode group diversity multiplexing (MGDM). More specifically, by adapting the selection criteria of the sub-optimal antenna used in MIMO radio systems, we propose a new strategy to improve the protocol performance in indoor optical networks. By using the Bell Laboratories Layered Space-Time (BLAST) architecture (Physical layer) and the application of Go-Back-N (at link layer), we show a significant increase of the link throughput, compared with that of the capacity based algorithm. The simulation results show that the combination of transmitters according to the criterion of selection increases the total data rate of the system using multi mode fibers (MMF).

In this paper, we consider the problem of sensing a primary user in a cognitive radio network by employing multiple antennas at the secondary user. Among the many spectrum-sensing methods, the predicted eigenvalue threshold (PET) based method is a promising non-parametric blind method that can reliably detect the primary users without any prior information. Then, a simplified PET sensing method, which needs to compare only one eigenvalue to its threshold, is introduced. Compared with the original PET sensing algorithm, the simplified algorithm significantly reduces the computational complexity without any loss in performance. A performance comparison between the proposed method and other existing methods is provided.

In this paper, we consider the problem of sensing a primary user in a cognitive radio network by employing multiple-antennas at the secondary user. Among the many spectrum-sensing methods, the predicted eigenvalue threshold (PET) based method is a promising non-parametric blind method that can reliably detect the primary users without any prior information. Also, a simplified PET sensing method, which needs to compare only one eigenvalue to its threshold, is introduced. A performance comparison between the proposed method and other existing methods is provided. Spatial antenna correlation at the secondary user is a crucial factor for practical systems. The effect of the spatial correlation presence on the different sensing methods is investigated.

Modulation type is one of the most important characteristics used in signal waveform identification and classification. Spatial correlation is a crucial factor for practical multiple-input multiple-output (MIMO) systems. This paper addresses the problem of blind digital modulation identification in spatially-correlated MIMO systems. The proposed algorithm is verified using higher order statistical moments and cumulants of the received signal. The purpose is to discriminate among different M-ary shift keying linear modulation schemes without any priori signal information. This study employs several MIMO techniques to identify the modulation with and without channel state information (CSI). The proposed classifier shows a high identification performance in acceptable signal-to-noise ratio (SNR) range.

Abstract In this paper, we investigate the performance of a cross‐layer (physical and MAC) design for multiple‐input multiple‐output (MIMO) system that aims at maximizing the throughput of ad hoc networks by selecting the optimum antenna combination. Employing this cross‐layer design is shown to improve the overall network performance relative to the case where no antenna selection (AS) is used. To solve the node blocking problem associated with the IEEE 802.11 medium‐access control (MAC) protocol, the proposed protocol leverage the available degrees of freedom offered by the MIMO system to allow neighboring nodes to simultaneously communicate using the zero‐forcing (ZF) Bell‐labs layered space‐time (BLAST) architecture. Using the cross‐layer design, neighboring nodes share their optimum antenna selection (AS) information through control messages. Given this shared information, nodes set their decisions on the number of selected antennas based on the available spatial channels that guarantees collision‐free transmissions. At the destination node, the ZF receiver is employed to extract the desired user data while treating the data from neighboring users as interference. The performance of the proposed cross‐layer design is examined through simulations, where we show that the network throughput is significantly improved compared to conventional MAC protocols. Copyright © 2010 John Wiley & Sons, Ltd.

We investigate the performance of cooperative diversity when employed in convolutionally coded direct-sequence code-division multiple-access (DS-CDMA) systems over frequency-selective fading channels. The performance of the coded system is evaluated through bit error rate upper bounds and compared with simulations. In our analysis, we obtain closed form expressions for the bit error rate upper bounds for multi-relay cooperative systems employing multiuser detection at both the relay and base station receivers. We show that the full benefits of cooperative diversity cannot be achieved if no interference suppression is employed at both the cooperative user and base station receiver. Both simulation and analytical results are presented to validate and demonstrate the performance gain with different system parameters.

In this study, multi-relay decode-and forward (DAF) cooperative networks employing convolutional coding are studied for asynchronous direct-sequence code-division multiple-access (DS-CDMA) systems over frequency-selective slow fading channels. The authors show that the full benefits of coded cooperative diversity cannot be achieved if no multi-user interference suppression is employed at the cooperative end. The authors consider two scenarios; perfect and imperfect inter-user channels. In that, the bit-error-rate performance of the cooperative system is investigated for an uplink transmission where a decorrelator detector is used at both the relay and base station receivers. Both simulation and analytical results are presented to demonstrate the diversity gains of the convolutionally coded cooperative network.

Modulation type is one of the most important characteristics used in signal waveform identification and classification. In this paper, an algorithm for blind digital modulation identification for multiple-input multiple-output (MIMO) systems is proposed. The suggested algorithm is verified using higher order statistical moments and cumulants of the received signal. A multi-layer neural network trained with resilient backpropagation learning algorithm is proposed as a classifier. The purpose is to discriminate among different M-ary shift keying linear modulation types and the modulation order without any priori signal information. This study covers different MIMO systems with and without channel state information (CSI). The proposed classifier is evaluated through the probability of identification where we show that our proposed algorithm is capable of identifying the modulation scheme with high accuracy in excellent signal-to-noise ratio (SNR) range.

The performance of a cross-layer (physical and MAC) design for multiple-input multiple-output (MIMO) system that maximizes the throughput of ad-hoc networks by selecting the optimum antenna combination is investigated. This cross-layer design is shown to improve the overall network performance relative to the case with no antenna selection. To further improve the overall network throughput, we minimize the effect of node blocking in the IEEE 802.11 medium-access control (MAC) protocol. The proposed protocol leverage the available degrees of freedom offered by the MIMO system to allow neighboring nodes to simultaneously communicate using the zero-forcing Bell-labs layered space-time (BLAST) architecture. The performance of the proposed cross-layer design is examined through simulations to show the throughput advantage relative to conventional MAC protocols.

In this work, we have studied chromatic and modal dispersion of silica graded-index optical fibers as a function of mode depending parameters and a launching condition in local area network (LAN) context. We have investigated mode-depending parameters, namely modal delay, modal attenuation and mode-coupling effects as a function of wavelength. We have proved that the number of excited mode groups depend on spot radius beam when the fiber is excited with a Gaussian input beam. On the other hand, we have demonstrated that we can get a good frequency response of system with a proper wavelength value and under an optimal launching condition in order to decrease the modal dispersion effects of multimode optical fiber. Finally, we have investigated the transfer function of MMF with taking into account chromatic and modal dispersion and considering two structured of studied optical fiber.

In this paper, the performance of cooperative networks introduced in the literature is analyzed for asynchronous direct sequence code-division-multiple-access (DS-CDMA) systems in frequency-selective slow fading environment. We show that the full benefits of cooperative diversity cannot be achieved if no multiuser interference suppression is employed at the cooperative end. We consider two scenarios; perfect and imperfect inter-user channel. The bit-error-rate performance of the cooperative system is investigated for an uplink transmission where a decorrelator detector is used at both the relay and base station receivers. The proposed receiver has the advantage of mitigating the effects of multipath fading and multiple-access interference. Both simulation and analytical results are presented to demonstrate the diversity gains of cooperative networks.

A new global fractionally spaced blind equalization approach based on the use of pattern search optimization and two new constant modulus fourth order asymmetrical modulations schemes is proposed. Simulation results in terms of intersymbol interference and a new performance measure show that the proposed approach achieves perfect global convergence behavior together with correction of the random phase rotation of the constellation. The propagation environment is a frequency selective channel in the presence of Gaussian noise.

A receiver based on parallel cancellation of multiple access interference (PIC) by bias compensation is considered here for a direct sequence unipolar optical code division multiple access (DS-OCDMA) system. This receiver is dedicated to Multi access Interference (MAI) mitigation. Error on null data occur when a conventional receiver is used. The principle of our proposed receiver consists in reducing the previews output error by amplification of the interfering signals. We also develop the PIC compensated theoretical error probability expression and we show the performance improvement due to this receiver. The performance of such a technique is analyzed in a synchronous network using orthogonal optical codes (OOC) and the results are compared with those for different receivers.