Full-duplex (FD) communication is becoming a key technology for future wireless systems, offering the potential to significantly improve spectral efficiency (SE) and overall system performance. This study explores how hardware impairments (HWIs) impact the performance of FD multiple-input multiple-output (MIMO) systems. We develop models to evaluate the achievable data rates for both uplink (UL) and downlink (DL) communications in the presence of hardware imperfections. Additionally, we address the challenge of optimizing power allocation to maximize FD SE using the Karush-Kuhn-Tucker (KKT) conditions. Our approach not only boosts system performance but also compensates for HWIs, even outperforming ideal systems operating at maximum power. Finally, extensive simulations validate our theoretical findings.

This work outlines a framework for full-duplex (FD) multiple-input multiple-output (MIMO) communication systems considering practical conditions, such as imperfect channel state information (CSI) and hardware impairments (HWIs). We analyze the performance of FD multi-user (MU) MIMO systems, specifically studying the effects of practical channel estimation errors and HWIs on the spectral efficiency (SE) performance of FD MU-MIMO systems. Maximum ratio combining/maximum ratio transmission (MRC/MRT) and zero-forcing reception/zero-forcing transmission (ZFR/ZFT) linear detectors/precoders are considered at the base station (BS). Moreover, linear minimum mean square error (LMMSE) and least square (LS) error estimation are used to estimate the channel at the BS. Mathematical derivations for the lower bounds of uplink (UL) and downlink (DL) SEs are presented in the context of imperfect CSI and HWIs. Computer simulations validate the analytical derivations. The results demonstrate the tightness of the obtained bounds.

This paper investigates the threat of passive eavesdropping on downlink cell-free massive MIMO (CF-MaMIMO) systems, examining in a particular system under the effects of imperfect channel estimation. Physical layer security (PLS) techniques and power allocation algorithms are typically adopted to deteriorate the quality of eavesdropped signals. In the downlink stream, artificial noise (AN) is broadcasted simultaneously with the users’ data streams, with the aim of jamming the eavesdropper’s signal without sacrificing the quality of service (QoS). However, imperfect channel estimation results in AN leakage to legitimate users. Our work considers this condition, and the power allocation algorithms we present determine the minimum power that is needed to maintain the user’s Qos even in the presence of leaked AN. We first propose the cooperative PLS algorithm (COP), which facilitates AN broadcasting via access point (AP) cooperation. Unfortunately, this cooperation wastes some of the power used to send the AN and, in most cases, increases the computational complexity. We then present the independent PLS algorithm (IND), where the goal is to regain this power by allowing each AP to broadcast AN independently. However, to meet the feasibility criterion, this occurs at the cost of increasing the number of used antennas. This technique reduces the power allocation complexity but increases the computational complexities of the precoder design and the channel estimation process. Our results reveal that the proposed algorithms enhance the security performance of CF-MaMIMO. We evaluate such performance from numerous angles including the number of users, number of APs, QoS, beamforming, AN leakage, and channel estimation techniques.

Full-duplex (FD) communications have been recognized as one of the promising wireless transmission candidates for the future of wireless communication and networking technologies, thanks to their ability to greatly improve spectral efficiency (SE) and dramatically enhance energy efficiency (EE). In this paper, we study the influence of hardware impairments (HWIs) on single-input single-output (SISO) FD access point (AP). More precisely, we study the EE when the system's terminals have impaired transceivers. Optimization problem for EE maximization is formulated to fulfill quality of service (QoS) and power budget constraints. We propose an algorithm to solve the optimization problem by using the fractional programming theory and Karush-Kuhn-Tucker (KKT) conditions technique. The results unveil that excellent power allocation is crucial in FD communication networks and the proposed algorithm outperforms the maximum power transmission scheme. The results also reveal that HWIs degrade both EE and SE performance. Moreover, at high power region, no further improvements can be obtained by increasing the transmission power. Finally, we assume that all fading channels demonstrate Nakagami-m distribution.

This work studies unmanned aerial vehicles (UAVs) as supporters of future wireless networks. We focus on channel assignment and study it as a joint optimization problem, where we pick from a pool of channels provided by a main core network. We find an optimal solution for the association problem between the wireless access points (WAPs) and UAVs, and this way we can maximize the total weighted sum rate by formulating a max-min optimization problem. This formulation is subject to quality of service (QoS), to a maximum number of links from the pool channel, and to available bandwidth constraints. The formulated problem is an NP-hard problem and requires exponential time to be solved as the number of WAPs increases. We propose a low-complexity centralized algorithm to solve the association problem. Our results demonstrate that the solution of the proposed algorithm approaches that of the exhaustive search technique with much less computational complexity.

Ful1-duplex (FD) communication stands out as a game-player for future wireless communication systems by the ability to increase spectral efficiency (SE) and improve system performance. In this paper, we study the effects of hardware impairments (HWIs) on the FD multiple-input multiple-output (MIMO) communication system’s performance. Mathematical frameworks for the lower bound of uplink (UL) and downlink (DL) SE are derived under imperfect hardware conditions. Furthermore, power allocation optimization problem is formulated to maximize the FD SE and then solved using the Karush-Kuhn-Tucker (KKT) conditions technique. Interestingly, using the proposed solution achieves a remarkable improvement. Moreover, it can compensate the impaired system, which can outperform the ideal system that transmits with maximum power. Finally, extensive computer simulations were conducted to validate the theoretical derivations.

Reconfigurable intelligent surfaces (RISs) are a recent yet revolutionary development in communications systems. Particularly applicable to millileter wave (mmWave) systems, these surfaces can increase localization performance and decrease vulnerability to environmental influences, all by adjusting the incoming signals’ phase. At the same time, manufacturing ideal hardware to be deployed at the transceivers is not feasible nor practical. These non-linearities in hardware, collectively known as hardware impairments (HWIs), cause signal degradation and adversely affect localization. In this paper, the effect of HWIs on RIS-aided localization is examined. Towards that, the mean squared error (MSE) of the user’s position is found through a maximum likelihood estimator (MLE) and its functionality is verified by the position error bounds (PEB), derived from Cramér-Rao lower bounds (CRLB). Our numerical results show that active RISs mitigate the deteriorating effect of HWIs on the user’s PEB. Based on our outcome, increasing the inter-RISs space generally creates more resolvable paths and leads to improved localization.

Reconfigurable Intelligent Surface-based Space Shift Keying (RIS-SSK) was recently proposed as a promising transmission technique. In order to design strategic radio environments, this system takes advantage of RIS-based communication and adjusts the propagation channels. Furthermore, using SSK as a special case of the Spatial Modulation (SM) reduces the detection complexity by using only the index of the active antenna to transmit the data. However, when considering an effective RIS-SSK system, the transmit antenna is modeled by spatial constellation points with different weights. This requires the knowledge of Channel State Information (CSI), including the index of the activated antenna at each transmission which is impractical. In contrast, blind RIS-SSK does not require this information, decreasing its complexity and increasing its practicality. In this paper, a blind RIS-SSK system without phase-adjusting is studied in the presence of hardware impairments and compared to the standard SSK. Additionally, analytically error probability expressions based on the Maximum Likelihood (ML) detector are developed and proven with simulations. The results illustrate the negative effects of modeling the hardware impairments for robust RIS-SSK system implementation.

This paper investigates visible light positioning (VLP) systems in the presence of signal-dependent shot noise (SDSN). We consider both synchronous and asynchronous down-link communications when evaluating the Cramér–Rao lower bounds (CRLBs) of the distancing error. Performance assessment is based on time-of-arrival (TOA), received signal strength (RSS), and hybrid (TOA/RSS) based distance estimations. The results demonstrate that SDSN has a critical impact on the distancing bounds in all considered cases. Moreover, the level of degradation observed at higher SDSN levels is not uniform among all cases.

Location-awareness is expected to be one of the main services in 5G millimeter-wave (mmWave) communication systems. In mm-Wave, multiple-input multiple-output (MIMO) systems will be used, leading to the deployment of antenna arrays in both transmitter and receiver. Hardware components being used in transceiver are commonly modeled as linear filters; but practically, this linearity is not fully satisfied. Power amplifiers and filters applied in antennas mostly show nonlinear behavior, causing loss in spectral efficiency (SE) and signal quality. This non-linearity is referred to hardware impairments (HWIs). Under HWIs model at both the transmitter and receiver, 2D localization performance is examined. Towards that, we derive position and orientation error bounds and study the effect of HWIs on the derived bounds. The numerical results reveal that HWIs have a significant effect on localization and it causes more than 100% degradation in both the transmitter and receiver. Also, the rate of degradation stays the same for both position and orientation error bounds except for the oriented UE.

Large Intelligent Surfaces (LIS) are promising in terms of what they can offer to 6G and beyond communication networks. As such, they have recently attracted considerable attention in the research community. This technique allows the operators to control the environment in a strategic way so as to improve the communication system performance. This work studies the effect of hardware impairments (HWIs) on the LIS-Aided wireless communication system under correlated channel conditions. In specific, we look at the impact on the system performance. We also give a deterministic approximation function of the average bit error rate (ABER) for a large number of reflectors and a tight approximation of the outage probability (OP). Extensive Monte Carlo simulations are provided to verify the analytical results, which show that the system performance saturates at a high signal-to-noise ratio (SNR) due to the HWIs. Moreover, this degradation is exacerbated when the channels demonstrate strong correlation conditions. However, the HWIs have a dominant effect and the correlation impact diminishes with a larger number of reflectors.

Space shift keying (SSK) has many advantages through its unique transmission manner as compared to other multiple-input multiple-output (MIMO) techniques. Nevertheless, the practicality of SSK in the presence of real-time imperfections such as channel estimation errors and hardware impairments (HWIs) is still an open research problem. On the other hand, the effects of HWIs are assumed as zero-mean circularly-symmetric complex Gaussian random variable (RV) in the literature. However, this model does not reflect the asymmetric characteristics of different HWIs. Therefore, the aim of this paper is to shed light on the joint effect of improper Gaussian noise (IGN) and imperfect channel state information (ICSI) on the performance of SSK receiver. Particularly, an optimal maximum likelihood (ML) detector is designed, and pairwise error probability (PEP) expression is derived. Additionally, an exact closed-form Cramer-Rao bound expression is calculated for evaluating the channel estimation accuracy under the effect of IGN. The results obtained by using computer simulations prove that the proposed optimal detector is superior to the traditional ML detector in the presence of IGN and ICSI.

In this paper, we have designed an optimal detector for the space shift keying (SSK) receiver in the presence of the improper Gaussian noise (IGN) with multiple antennas mounted the transmitter and receiver nodes. We have analyzed this optimal detector by finding the error probability and comparing the performance of this receiver with the suboptimal one which uses the traditional maximum-likelihood (ML) detector to detect the IGN as if it is a proper Gaussian noise (PGN). The analytical expressions obtained can be used under general complex fading channels. The analytically derived results have been validated using the simulation, where it is demonstrated that the importance of using the optimal receiver, in addition to the importance of considering the IGN over the (PGN) at the receiver.