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This study investigates the performance of cooperative relaying-based non-orthogonal multiple access (NOMA) with simultaneous wireless information and power transfer. Assuming the batteryassisted non-linear energy harvesting (NL-EH) in which the near user (NU) works as a relay for the far user (FU) to convey data from the base station (BS); two scenarios are examined: (1) No direct link (NDL) between the BS and the FU, and (2) direct link (DL) between the BS and the FU. The DL at the FU is evaluated in two scenarios: as an optimal combination to the signal from the NU and as an interfering link to the signal from the NU. Considering the power splitting relaying (PSR) protocol with an NL-EH model and assuming imperfect successive interference cancellation (i-SIC) at the NU, we derive closed-form expressions for the NU and FU outage probability and throughput. The throughput of the FU is greatly increased by supplementing the harvested energy with a small quantity of battery energy. Furthermore, an optimal combination of the FU signals relayed from the BS and the NU considerably improves the throughput of the FU. It reduces the energy consumption at the battery compared to the scenario when there is NDL. We obtain the diversity order by deriving high signal-to-noise ratio approximations for the NU and FU outage probability in NDL and DL scenarios. Unlike linear energy harvesting, we show NL-EH leads to a loss of diversity, making it even more important to use the DL. We have formulated an equation to measure energy efficiency using the derived throughput expressions for the NDL and DL scenarios. We have also shown that selecting the optimal combination of battery energy and PS parameter is essential to achieve the highest possible throughput and energy efficiency. The residual interference generated by i-SIC significantly impacts the outage probability of the NU while having a negligible effect on the performance of the FU. Moreover, we have discovered that performance deteriorates when interference from the DL is present. We explain how the system’s performance is affected by the selection of energy harvesting parameter, power allocation coefficient, saturation threshold, self-loop interference, variable node distances and battery energy. Monte Carlo simulations have verified the accuracy of the resulting expressions.

Terahertz (THz) wireless communication has emerged as a promising technology for high-speed, ultra-broadband, and low-latency data transmission. However, the performance of THz systems is significantly affected by various channel and system parameters. Existing literature often models THz transmission links using $\alpha -\mu $ fading with pointing error, which is suitable for optical communication systems or a specific type of THz antennas. A new pointing error model designed for THz antennas has recently been proposed. The fluctuating two-ray (FTR) fading model emerges as a very suitable choice for THz transmission, as it considers the line-of-sight components and their random phase distributions, in addition to multipath and non-linearity of the propagation medium. In this paper, we model a THz transmission link considering FTR short-term fading, channel path loss, and the recently proposed pointing error, with two standard uniform $N \times N$ THz antenna arrays, one mounted at the unstable transmitter and one at the unstable receiver (instability accounts for the dynamic nature of drone-to-drone communication scenarios, particularly, dynamic drones fluctuating in yaw, roll, and pitch directions). Novel exact analytical closed-form expressions for the probability density function, the cumulative distribution function, and moment generating function of the received instantaneous signal-to-noise ratio are derived for the aforementioned system using standard mathematical functions. Next, closed-form expressions for performance metrics, namely, the outage probability, the average bit error rate, and the average channel capacity, are derived. Furthermore, the $n$ th moment of the received instantaneous signal-to-noise ratio and diversity order of the system are derived. The effects of various channel and system parameters on the system performance are studied, and the accuracy of the derived analytical expressions is confirmed by simulation results.

Utilizing derivations for the properties of a symmetric Toeplitz matrix, we obtain analytical expressions for the performance evaluation of wireless communication systems using multiple antennas at the transmitter and/or the receiver, including those for keyhole channels, beamforming, and noncoherent detection. Our derivations of the analytical expressions are based upon closed form expressions we have obtained for the eigenvalues and eigenvectors of the $L \times L$ symmetric Toeplitz matrix whose element in the $i$ th row and the $j$ th column is given by $C^{i-j}+C^{j-i}$ , where $C \in \mathbb {C} \setminus \{-1,0,1\}$ , with $\mathbb {C}$ denoting the set of complex numbers. Each element of this matrix can be expressed as a polynomial in $C + 1/C$ . Furthermore, the special cases of real nonzero $C$ and of complex $C$ with magnitude one are discussed. Using these new results, analytical expressions for the performance of wireless communication systems using multiple antennas at the transmitter and/or the receiver can be obtained.

Quantum key distribution (QKD) can provide unconditional security to next-generation communication networks guaranteed by the laws of quantum physics. This article studies the secret key rate (SKR) of a continuous variable QKD (CV-QKD) system using multiple-input multiple-output (MIMO) transmission and operating at terahertz (THz) frequencies. Distinct from previous works, we consider a practical “restricted” eavesdropping scenario in which Eve can collect only a fraction of photons lost in the environment. We propose a system model for the MIMO THz CV-QKD system that accounts for restricted eavesdropping via a lossy wireless channel between Alice and Eve. We derive for this system new SKR expressions for both coherent-state-based and squeezed-state-based CV-QKD protocols. Our results show that previous analysis assuming unrestricted eavesdropping leads to overly pessimistic SKRs, and that in practice, the achievable SKR can be significantly increased under restricted eavesdropping. The increase in the SKR is quantified by the simplified SKR expansions derived in this article. Our results also reveal that squeezing is beneficial for improving the SKR only for unrestricted eavesdropping. However, in a practical setting with restricted eavesdropping, increased squeezing leads to a reduction in the SKR.

In this article, we propose a machine-learning framework for parameter estimation of single-mode Gaussian quantum states. Under a Bayesian framework, our approach estimates parameters of suitable prior distributions from measured data. For phase-space displacement and squeezing parameter estimation, this is achieved by introducing expectation–maximization (EM)-based algorithms, while for phase parameter estimation, an empirical Bayes method is applied. The estimated prior distribution parameters along with the observed data are used for finding the optimal Bayesian estimate of the unknown displacement, squeezing, and phase parameters. Our simulation results show that the proposed algorithms have estimation performance that is very close to that of “Genie Aided” Bayesian estimators, which assume perfect knowledge of the prior parameters. In practical scenarios, when numerical values of the prior distribution parameters are not known beforehand, our proposed methods can be used to find optimal Bayesian estimates from the observed measurement data.

In this paper, we consider the uplink (UL) communication of a massive multi-user (MU) multiple-input multiple-output (MIMO) hybrid beamforming system (HBFS) in which the transmitting user-equipments are affected by IQ imbalance (IQI). We first show that if the transmitter IQI is not compensated, it will result in a finite ceiling of the UL achievable sum-rate at high signal-to-noise ratio, which only depends on the transmitter IQI matrices and is independent of the propagation channel and the choice of the hybrid combining matrices. This justifies the need for transmitter IQI compensation in massive MU-MIMO HBFS. Therefore, we propose a novel zero-forcing based transmitter IQI compensation algorithm to be implemented at the base station which effectively mitigates the undesired effects of transmitter IQI and is applicable for any channel model and any choice of the number of RF chains. For uncorrelated Rayleigh fading channel, we derive an approximate closed-form expression of the UL sum-rate achieved by the massive MU-MIMO HBFS with the proposed transmitter IQI compensation. Finally, numerical results are presented which confirm the effectiveness of the proposed transmitter IQI compensation algorithm in mitigating the undesired effects of transmitter IQI in different channel environments.

We consider a cognitive radio (CR) network with simultaneous wireless information and power transfer (SWIPT) system having one base station (BS) with multiple antennas that acts as a secondary transmitter, one desired information receiver (IR) acting as secondary receiver, multiple primary users (PUs) having licenses band of spectrum, and multiple energy harvesting receivers (EHRs). The EHRs harvests energy from the BS and eavesdrop the information from signal. In order to extract the information and then harvest energy from that signal, power splitting is considered in each EHR. On the basis of an imperfect channel state information (CSI) in IR, selection of the best transmit antenna at the BS is made. The effect of path loss on the system is also considered. The derivation of analytical expression in closed-form is provided for the exact secrecy outage probability (SOP) of the network. The derived expression highlights the variation in the secrecy outage of the considered CR SWIPT system relying on imperfect CSI with respect to the system parameters, which is depicted through numerical analysis. Furthermore, we derive the asymptotic SOP and study the effects of different system parameters on the secrecy diversity order and secrecy array gain.

This paper presents an application of power-line communication (PLC) as a viable solution for frequency regulation in a smart microgrid. The microgrid under consideration comprises a diesel generator with a frequency controller and another synchronous generator operating in the constant power mode. Frequency regulation is achieved in the microgrid by communicating the frequency deviation (information) from the control center to the diesel generator using PLC. The information received at the other end is used for frequency regulation. A simple yet effective M -ary amplitude-shift keying (ASK) modulation-based PLC system is proposed for information transmission. A comparative analysis of M -ary ASK and M -ary frequency-shift keying (FSK)-based PLC systems is also presented. Approximate closed-form expressions for the average symbol error rate and the average achievable rate are derived for both the PLC systems, assuming that the PLC channel coefficients and the additive impulsive noise samples are derived from a log-normal distribution and a Bernoulli-Gaussian process, respectively. The results show that M -ary ASK is a better choice for PLC than M -ary FSK. Furthermore, the delay introduced in the control loop while using the proposed PLC system is negligible, and therefore, the stability of the microgrid is also ensured.