Telecommunication Systems最新文献

Abstract

In this paper, we present analytical results on the effective capacity (EC) for a dual-hop cooperative network employing non-orthogonal multiple access and the decode-and-forward half-duplex relaying protocol. Assuming that wireless propagation is modelled by the Nakagami-m distribution, novel analytical results for the EC are deduced. These analytical results are further extended to the generalized fading channels, modeled by a mixture gamma distribution. Our proposed analysis is validated by numerical results and Monte-Carlo simulations. Besides, the numerically evaluated results have demonstrated the impact of various system-level parameters on the performance of the considered system, including the impact of fading, the power allocation coefficient and the delay constraints.

Abstract

In order to further improve the transmission and spectral efficiency of the MC-DCSK system, a novel security system called Joint Mapping Multi-Carrier Differential Chaos Shift Keying (JM-MC-DCSK) is proposed in this paper. A novel joint mapping scheme is designed which consists of two parts: matrix reshaping mapping and combination mapping. Moreover, in order to correctly demodulate the information bits in the index obtained through Maximum Likelihood Estimation (MLE), we propose a new index mapping algorithm to match this joint mapping scheme. The information bits are first mapped into U mutually orthogonal matrices in the matrix reshaping mapping structure. In this structure, we employ segmental shifts of the orthogonal submatrices instead of cyclic shifts to eliminate intra-signal interference, which contributes to the reliability of the system. Then, in the combination mapping structure, the information bits are modulated by N orthogonal carriers after being replicated U times. In each carrier signal, we arbitrarily select two sequences from the U orthogonal chaotic sequences to be superimposed. This scheme can map more information symbols and the randomness of the combination selection provides more flexibility for the mapping algorithm. The Bit Error Rate is derived and analyzed under Additive White Gaussian Noise and Rayleigh Fading Channel by Gaussian approximation method and central limit theorem, and numerical simulations are conducted to verify the correctness of theory. Additionally, the simulation results demonstrate that the system also has lower BER and Peak-to-Average Power Ratio, reflecting its significant theoretical and practical engineering value.

The purpose of this article is to investigate the viability of Multi-Carrier Modulation (MCM) systems based on the Fast Walsh Hadamard Transform (FWHT). In addition, a nonlinear Joint Low-Complexity Optimized Zero Forcing Successive Interference Cancellation (JLCOZF-SIC) equalizer is proposed. To that end, general equations for the number of flops of the proposed equalizer and various other equalizers are given. This article discusses the use of Banded Matrix Approximation (BMA) as a technique for reducing complexity. The proposed equalizer uses BMA to accomplish both equalization and co-Carrier Frequency Offset (co-CFO) corrections. In addition, three cases involving the proposed equalizer were investigated. In the first case, diagonal compensation is used. In the second case, BMA compensation is used. In the third case, complete matrix compensation is used. In the presence of frequency offset, noise, and frequency-selective Rayleigh fading environments, analysis and simulation results show that the OFDM-FWHT system with the proposed equalizer outperforms the conventional OFDM system with various linear and nonlinear equalizers.

Abstract

Atmospheric turbulence channels experience quasi-static fading, which makes it relatively straightforward to utilize feedback information for link adaptive transmission. Applying adaptive modulation to MIMO systems can effectively mitigate the degradation of Free-Space Optical (FSO) signals under adverse turbulence conditions. In this paper, the joint influence of pointing error and Malaga distribution turbulence fading on the probability density function (PDF) of the received light intensity of a MIMO channel employing maximal ratio combining (MRC) is considered. The PDF of MRC combined channel is derived based on the moment generation function. Then, using the cumulative density function (CDF)-based method, we analyze the asymptotic spectral efficiency (SE) and average bit error rate (BER) performance of the adaptive MPSK-MIMO system under different turbulence intensities, beam waist radius, jitter standard deviation, and the number of transmit/receive apertures. In addition, we also compare the average BER performance of adaptive and non-adaptive MIMO systems with MRC receivers. Monte Carlo simulation further verifies our analysis. The derived results help quantify the diversity order of the systems we are considering.

This paper studies a multiuser multiple-input multiple-output simultaneous wireless information and power transfer cognitive radio system with the aid of an active intelligent reflecting surface (IRS). Considering the scenario that nonlinear energy harvesting models and power splitting (PS) protocols are adopted at energy receivers and that channel state information (CSI) imperfections of the channels to the primary users (PUs) are taken into consideration, we aim at designing the secondary base station (SBS) transmit precoding matrices, the IRS reflection coefficient matrix, and the secondary user (SU) PS ratios. The design objective is to maximize the system sum-rate (SR) under the transmit power constraints at the SBS, amplification power constraints at the IRS, amplitude constraints on IRS reflection elements, robust interference power (IP) constraints at the PUs, and minimum harvested energy constraints at the SUs. The formulated optimization problem is intractable to directly solve since the design variables are nonlinearly coupled, the objective function and constraints are highly nonconvex, and robust IP constraints are semi-infinite. To tackle the mathematical challenges, we derive the amenable surrogate functions and constraints while to handle the semi-infinite robust IP constraints, we transform them into linear matrix inequalities. Then, to find optimized solutions to the considered design problem, we exploit alternating optimization frames to derive an efficient iterative algorithm (IA). The convergence and computational complexity of the developed IA are shown. Simulation results illustrate the performance gains of the designed problem and robustness of IP constraints against CSI imperfections. Additionally, the numerical results show that the active IRS-aided systems exhibit superior SR performance over the passive IRS-aided systems.

Abstract

This article delves into the investigation of parameters and associated issues in the context of a Bayesian game theory-based approach for selecting the target channel for secondary users in a licensed heterogeneous cognitive radio network. In such networks, cognitive or secondary users can enhance their activity within a licensed spectrum by dynamically selecting an available spectrum, thereby addressing the scarcity issue in the radio spectrum. The study adopts a game model where each user is treated as a network player, with the channel payoff or utility function serving as a crucial parameter for target channel selection. The game theory approach assumes that each player possesses knowledge of other players’ payoffs, although this assumption may only hold for some games. In auction-based games, for instance, other players’ payoffs or profits are unknown, introducing uncertainty. This type of game model falls under the Bayesian game model. The article presents the Bayesian battle of the sexes approach to address uncertainty in other players’ payoffs or profits and proposes possible causes for channel selection. The best response for secondary users and channel payoffs is computed using this approach. The Bayesian Nash equilibrium calculates the average payoff, taking into account various spectrum handoff parameters like waiting time and inactive probability. This comprehensive analysis aims to calculate the overall network characteristics in the given heterogeneous cognitive radio environment.

An electrically small multiband planar antenna is presented by using rectangular split ring resonator (RSRR) metamaterial element for LTE, WiMAX and WLAN applications. The designed antenna possesses asymmetric coplanar strip (ACS)-fed Hilbert Curve Fractal Antenna (HCFA) loaded with RSRR metamaterial for multiband radiation at 1.44 GHz, 3.76 GHz and 5.27 GHz. ACS-fed HCFA is responsible for creating the first (at 1.44 GHz) and second (at 3.76 GHz) resonance frequencies owing to the coupling between ACS-fed HCFA and ground plane. Moreover, the RSRR yields upper resonance at 5.27 GHz owing to the metamaterial transmission line. The stop band and pass band nature of the RSRR and its negative permeability characteristics are described using an effective medium theory. An equivalent circuit model of the proposed antenna is investigated with the help of Agilent ADS to validate the operating frequencies. Also, the geometrical parameters have been optimized using the artificial neural network (ANN), which is performed by MATLAB. The proposed antenna has been fabricated on a 18 × 16.5 × 1.6 mm³ FR-4 dielectric having ({upvarepsilon }_{{text{r}}}) = 4.4 and (tan {updelta }) = 0.02. It provides multiband response at 1.4 GHz, 4.4 GHz and 5.3 GHz with a − 10 dB impedance bandwidth of 330 MHz, 570 MHz, and 340 MHz, respectively, which is usable for LTE, WiMAX and WLAN band applications.

Wireless sensor networks (WSNs) and Internet of Things (IoT) are essential for numerous applications. WSN nodes often operate on limited battery capacity, so energy efficiency is a significant problem for clustering and routing. In addition to these limitations, one of the primary issues of WSNs is achieving reliability and security of transmitted data in vulnerable environments to prevent malicious node attacks. This work aims to develop a secure and energy-efficient routing protocol for fault data prediction to enhance WSNs network lifespan and data reliability. The proposed technique has three major phases: cluster construction, optimal route selection, and intrusion detection. The adaptive shark smell optimization (ASSO) technique was initially used with three input parameters for CH selection. These parameters are the residual energy, the distance to the BS, and the node density. After clustering, salp swarm optimization (SSO) is used to select the optimum path for data transmission between clusters, resulting in an energy-efficient WSN. Finally, to ensure the security of cluster-based WSNs, an effective intrusion detection system based on a modified Elman recurrent neural network (MERNN) is implemented to detect the presence of intrusions in the network. The experimental results show that it outperforms the competing methods in various performance metrics. The performance results of quality of service (QoS) parameters are expressed as dispersion value (0.8072), packet delivery rate (98%), average delay (160 ms), network lifetime (3200 rounds), and the accuracy of this method is 99.2%. Compared to the SVM, ELM, HMM, and MK-ELM protocols, the proposed protocol increases network lifetime by 77%, 60%, 45.4%, and 14.2%, respectively.

We show that the scheme (Telecommun Syst 78:539–557, 2021) is flawed. It uses a symmetric key encryption to transfer data between vehicles and the grid. But the specified symmetric key is easily retrieved by an adversary, which results in the loss of data confidentiality, and makes it vulnerable to impersonation attack, man-in-the-middle attack, and replay attack. We also present a method to fix this flaw and remove some superfluous communications in its registration phase.

According to the theory of single channel blind source separation (SCBSS), the algorithm based on virtual channel expansion must be established in a known source number, and most algorithms can only separate two source signals. When separating multiple source signals, the performance will deteriorate sharply. Since the existing methods of this kind use only a single algorithm for virtual channel expansion, they cannot retain all the source signals’ valuable information and effectively separate the multiple source signals. From the perspective of making the constructed virtual multi-channel signal contain enough information of the source signals as much as possible, this paper proposes a SCBSS algorithm based on improved wavelet packet and variational mode decomposition (IWP-VMD-SCBSS). Firstly, the source number is estimated according to the interval sampling method and the minimum description length (MDL) criterion. Secondly, the signal reconstruction method based on improved wavelet packet decomposition (IWPD) is used to reconstruct multiple purer virtual signals. Then the virtual signals are combined with the first intrinsic mode function (IMF) of two-level variational mode decomposition (VMD) and the original single-channel observed signal to constitute a virtual multi-channel signal. Finally, the joint approximate diagonalization of eigen-matrices (JADE) algorithm is used to process the virtual multi-channel observed signal to achieve BSS and obtain estimated source signals. The simulation results indicate that the IWP-VMD-SCBSS algorithm can achieve a lower symbol error rate (SER) than existing algorithms and lower computational complexity. It can solve the SCBSS problem of multiple communication signals effectively under an unknown source number.