Free space optics (FSO) has emerged as a key technology for high-data-rate wireless communication, thanks to the availability of mature transceiver designs and unlicensed spectrum. Although FSO links are highly directive, atmospheric turbulence introduces random scintillation effects analogous to RF multipath fading, degrading system performance. Traditional models often treat turbulence as an intensity-based stochastic process, providing limited insight into phase distortions and wavefront aberrations such as beam wander. While split-step propagation methods can capture these effects accurately, their computational cost is prohibitive for large-scale simulations. In this paper, we propose a single-phase screen channel model using Zernike polynomials, effectively representing the turbulence-induced phase aberrations without resorting to full multi-screen wave propagation. Because it preserves the full complex wavefront, the proposed method captures both phase and intensity distortions, enabling evaluation of beam-shaping and adaptive optics design and providing an accurate performance baseline for coherent FSO links. Simulation results prove the value of the proposed model, as interesting insights can be derived regarding the intensity distribution at the receiver and the impact of the receiver lens.

Localization is envisioned as a key enabler to satisfy the requirements of communications and context-aware services in the fifth/sixth generation (5G/6G) communication systems. User localization can be achieved based on delay and angle estimation using uplink/downlink pilot signals. However, hardware impairments (HWIs) (such as phase noise and mutual coupling) distort the signals at both the transmitter and receiver sides and thus affect the localization performance. While this impact can be ignored at lower frequencies with less severe HWIs, and less stringent localization requirements, modeling and analysis efforts are needed for high-frequency bands to assess degradation in localization accuracy due to HWIs. In this work, we model various types of impairments for a mmWave multiple-input-multiple-output communication system and conduct a misspecified Cramér-Rao bound analysis to evaluate HWI-induced performance losses in terms of angle/delay estimation and the resulting 3D position/orientation estimation error. We also investigate the effect of individual and overall HWIs on communications in terms of symbol error rate (SER). Our extensive simulation results demonstrate that each type of HWI leads to a different level of degradation in angle and delay estimation performance, and the prominent impairment factors on delay estimation will have a dominant negative effect on SER.

Hardware impairments in general and amplifier nonlinearity in particular severely limit the performance of communication links. This paper analytically provides statistical results on how a nonlinear amplifier affects the quality of signals in communication systems. In particular, we propose a statistical model that describes the nonlinear distortion as a function of the input signal’s average and instantaneous power and captures the pulse-shaping and matched filters’ effects. We show through simulations and complementary measurements that the proposed model can provide an authentic connection between the communication system parameters, power amplifier nonlinearity characteristics, and the communication system performance. It serves not only as a reliable model for nonlinear distortion analysis but also as a design tool that allows optimization of signal and filter characteristics with respect to nonlinear distortion.

We present a framework for joint estimation and compensation of three major oscillator impairments, namely sampling time error (STE), carrier frequency offset (CFO) and phase noise (PN). In particular, we model these impairments as Wiener processes and introduce a pilot-aided approach which facilitates their joint estimation. The proposed solution is carried out in two steps: first, an initial estimation of the transmitted symbols is acquired by applying an extended Kalman filter (EKF) on the pilot symbols and then, a second EKF is applied on the estimated symbols which yields an accurate tracking of STE, PN and CFO over an additive white Gaussian noise channel. Our numerical results demonstrate the efficacy of the proposed solution.

In this paper, we present a novel and effective linearization technique for nonlinear phased array antennas. For large phased arrays, linearization of the array using a single digital predistortion (DPD) is inevitable since one digital path is upconverted and feeds several RF transmission paths, each of which is connected to a power amplifier (PA) and an antenna element. However, a critical issue is that the PA characteristics can vary considerably within an array. Thus, linearizing individual PAs with one DPD is rather challenging. We formulate and solve an optimization problem that corresponds to jointly minimizing the maximum residuals between the input to the array and the output of individual PAs. We demonstrate that the proposed technique outperforms state-of-the-art linearization solutions while retaining the linear gain of the array.

We focus on transmit signal design for multiple- input single-output (MISO) wiretap channels with simultaneous wireless information and power transfer (SWIPT). Assuming that the channel inputs are drawn from standard constellation sets, we formulate secrecy rate maximization problems subject to power and harvested energy constraints. We tackle these problems under two different assumptions on the channel state information (CSI) at the transmitter. First, we consider a scenario in which the transmitter knows the CSI for both the information receiver and the energy receiver (potential eavesdropper), and we propose a precoder optimization approach. Then, we investigate the case where only perfect CSI of the information receiver is available along with the statistical CSI of the energy receiver. Our numerical results demonstrate the efficacy of the proposed solutions.

We propose a secure transmission scheme based on space shift keying (SSK) in which the indices associated with the transmit antennas are assigned dynamically according to the channel towards the legitimate receiver. We first derive an asymptotic secrecy rate under the perfect channel reciprocity assumption. Then, we study the impacts of imperfect reciprocity and presence of a nearby eavesdropper on the reliability and eavesdropping resilience of the proposed scheme. Finally, we introduce an enhanced antenna index assignment algorithm which is more robust to imperfect reciprocity, and is capable of preventing a nearby eavesdropper from acquiring the transmitted bits.

We propose transmit optimization techniques for multi-input multi-output (MIMO) wiretap channels with statistical channel state information (CSI) at the transmitter. We consider doubly correlated channels towards the legitimate receiver and the eavesdropper. The aim is to maximize the secrecy rates using the knowledge of the channel correlation matrices. We develop gradient-descent based optimization algorithms for obtaining the optimal transmit signals for both Gaussian and finite-alphabet inputs. Furthermore, we introduce a joint precoder and artificial noise (AN) design scheme. We demonstrate the efficacy of the proposed schemes via numerical examples.

We consider precoder and artificial noise (AN) design for multi-antenna wiretap channels under the finite-alphabet input assumption. We assume that the transmitter has access to the channel coefficients of the legitimate receiver and knows the statistics of the eavesdropper's channel. Accordingly, we propose a secrecy rate maximization algorithm using a gradient descent-based optimization of the precoder matrix and an exhaustive search over the power levels allocated to the AN. We also propose algorithms to reduce the complexities of direct ergodic secrecy rate maximization by: 1) maximizing a cut-off rate-based approximation for the ergodic secrecy rate, simplifying the mutual information expression, which lacks a closed-form and 2) diagonalizing the channels toward the legitimate receiver and the eavesdropper, which allows for employing a per-group precoding-based technique. Our numerical results reveal that jointly optimizing the precoder and the AN outperforms the existing solutions in the literature, which rely on the precoder optimization only. We also demonstrate that the proposed low complexity alternatives result in a small loss in performance while offering a significant reduction in computational complexity.

We propose a low complexity transmit signal design scheme for achieving information-theoretic secrecy over a MIMO wiretap channel driven by finite-alphabet inputs. We assume that the transmitter has perfect channel state information (CSI) of the main channel and also knows the statistics of the eavesdropper's channel. The proposed transmission scheme relies on jointly optimizing the precoder matrix and the artificial noise so as to maximize the achievable secrecy rates. In order to lower the computational complexity associated with the transmit signal design, we employ a design metric using the cut-off rate instead of the mutual information. We formulate a gradient-descent based optimization algorithm and demonstrate via extensive numerical examples that the proposed signal design scheme can yield an enhanced secrecy performance compared with the existing solutions in spite of its relatively lower computational complexity. The impacts of the modulation order as well as the number of antennas at the transmitter and receiver ends on the achievable secrecy rates are also investigated.