Emerging technologies such as dynamic time division duplexing (D-TDD) in 5G and full-duplex (FD), both considered for 6G, promise higher spectral efficiency and lower latency. D-TDD flexibly allocates uplink and downlink resources to match traffic, while FD enables simultaneous transmission and reception on the same band, boosting capacity. These gains, however, introduce new interference: cross-link interference (CLI) in D-TDD and self-interference (SI) in FD, both of which threaten network robustness. Extra-large multiple-input multiple-output (XL-MIMO) with its near-field (NF) visibility-region (VR) concept offers a promising solution. The core idea in this work is to exploit VRs jointly in space and temporal domain to build a comprehensive interference-management framework. By modeling VR characteristics across spatial and temporal domains, we develop strategies that selectively activate antennas and suppress dominant interferers. We propose a VR-aware antenna-selection method that evaluates overlap and delay structure to minimize CLI and SI without sacrificing desired signal power. Simulation results validate the approach, showing substantial interference reduction and improved reliability and efficiency in XL-MIMO-based cellular systems.

When using ultra-wideband signaling on massive multiple-input multiple-output (mMIMO) systems, the electromagnetic wave incurs an extra delay (across the array elements) comparable to or larger than the symbol duration, which translates into a shift in beam direction known as the beam squint effect. The beam squinting problem degrades the array gain and reduces the system capacity. This paper proposes a novel transceiver design based on lens antenna subarray and analog subband filters to compensate for the beam squinting effect. Specifically, the proposed design chunks the wideband signal from the phase shifters into groups of narrowband signals and controls their squints through an exhaustive search-based switching/precoding mechanism under the lenses. Furthermore, a simplified, thresholded search-based precoding algorithm is proposed, which demonstrates good performance while significantly minimizing complexity. The proposed system is analyzed in terms of beam gain, complexity, power consumption, and capacity. The numerical results demonstrate significant performance enhancement for the proposed system design as compared to the conventional mMIMO system with an uncompensated beam squinting problem.

Physical Layer Authentication (PLA) is a topic of considerable interest in ensuring strong security for upcoming wireless networks. However, existing PLA methods face challenges in maintaining performance in dynamic environments. To overcome this, we propose a novel tracking-based PLA approach, utilizing properties of the beamspace multiple-input multiple-output (MIMO) channel in narrowband millimeter-wave (mmWave) networks. Specifically, In particular, the proposed technique involves extracting a distance signature vector from the positions of the principal components within the beamspace MIMO channel representation. These components are then sorted in descending order based on their indices. To address mobility concerns in dynamic settings, a tracking filter is introduced. This filter allows the authentication system to continuously track and update the stored signature, enhancing overall authentication performance. Additionally, the proposed technique is extended to ultra-wideband signaling. In this extension, the richness of the derived signature is further improved by exploiting the beam squint effect, contributing to a more robust authentication process. Simulation results demonstrate that our approach overcomes the limitations of previous methods, resulting in improved authentication performance measured by detection and false alarm rates.

In multicarrier wideband millimeter-wave (mmWave) communications, as the size of antenna array increases, as in massive multiple-input multiple-output (MIMO), an additional propagation delay of the electromagnetic wave at each antenna element is introduced comparable to (or greater than) the symbol duration, resulting in producing a displacement in beam direction at each subcarrier frequency or as it calls beam squinting. With multi-beam transmission in massive MIMO systems, due to beam squinting effect, an additional inter-beam interference (IBI) can be introduced to the system which significantly decreases the overall system capacity. Therefore, in this paper, IBI under beam squint effect is modeled for different subcarrier frequencies and beam angles in a multi-beam mmWave massive MIMO system. In addition, the impact of this IBI model on the system capacity is evaluated. The analysis results show that beam squinting causes a significant increase in IBI level, even when transmitting with orthogonal beams. Moreover, the results provide the optimal number of beams for a given antenna array size to maximize the system’s capacity considering beam squinting phenomena.

A traditional array (TA) multiple-input multiple-output (MIMO) architecture in mmWave with hybrid beamforming suffers from high power consumption and hardware overhead. Therefore, a lens antenna subarray (LAS)-MIMO architecture has been recently proposed as a promising technology for a power-efficient system and reducing hardware cost and complexity. Additionally, the LAS-MIMO can offer spectral efficiency (SE) performance close to TA-MIMO and higher than single-lens antenna array (SLA)-MIMO. In this paper, we propose a hybrid precoding algorithm for the LAS-MIMO in mmWave to efficiently control the LAS design. The precoding problem is formulated as a sparse reconstruction problem due to the sparse behavior of mmWave channel. The proposed algorithm is an iterative process developed jointly using artificial bee colony (ABC) optimization with orthogonal matching pursuit (OMP) algorithms. In each iteration, the algorithm first selects the switches for each lens randomly using ABC and then uses OMP to approximate optimal unconstrained precoders. This process continues until achieving maximum SE. The simulation results show that LAS has around a 30% increase in SE compared to SLA while providing a significant gain in energy efficiency (EE) for single radio-frequency (RF) chain and multi RF chain scenarios.

Massive multiple-input multiple-output (mMIMO) systems implementing wideband signaling have been found to suffer from beam squinting problem. In multicarrier systems, beam squint causes spreading of the beam to multiple undesired directions, thereby degrading system capacity. This paper proposes user scheduling and precoding techniques that controls and exploit the beam squinting phenomenon to serve multiple users and improve the overall system capacity. The proposed techniques are based on the lens antenna subarray (LAS) mMIMO system. The proposed system design is explained and numerically evaluated in terms of beam gain and capacity with different number of users and RF chains. The simulation results exhibit significant performance enhancement in terms of beam gain and capacity, corroborating the idea of exploiting the beam squinting phenomenon to serve multiple spatially separated groups of users.

Reconfigurable intelligent surface (RIS) has recently drawn significant attention in wireless communication technologies. However, identifying, modeling, and estimating the RIS channel in multiple-input multiple-output (MIMO) systems are considered challenging in recent studies. In this paper, a disassembled channel estimation framework for the RIS-MIMO system is proposed based on the eigenvalue decomposition (EVD) concept to separate the cascaded channel links and estimate each link separately. This estimation is based on modeling the RIS-MIMO channel as a keyhole MIMO system model. Numerical results show that the proposed estimation method has a low estimation time overhead while providing less estimation error.