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A novel E‐ and H‐plane beamwidth‐reconfigurable Multiple Input Multiple Output (MIMO) antenna is presented here. The antenna consists of four two‐dimensional directional reconfigurable antenna elements that utilizes Positive‐Intrinsic‐Negative (PIN) diodes to achieve stable beamwidth reconfiguration in both the E‐plane and the H‐plane. Simulated and testing results of the fabricated prototype demonstrate that the operating frequency of the antenna ranges from 2.52 to 2.68 GHz across four different states. The beamwidth can switch between approximately 65° and 95° in both planes. The isolation between units exceeds 25 dB, and the radiation performance is stable with high efficiency. This antenna is particularly suitable for applications in 5G indoor communications. 1. Beamwidth‐Reconfigurable 2. MIMO Antenna 3. 5G communications

Consisting of a large number of passive reflectors, reconfigurable intelligent surface (RIS) has gained traction as an approach to enhance communication quality. The specular reflection assumption is common when ideal conditions are considered. In this paper, an anomalous‐reflector model was found for each RIS reflection unit, deviating from the specular reflector assumption, and the impacts of the aperture area and radiation pattern of the RIS reflecting elements are taken into account. A three‐dimensional (3D) geometry‐based RIS‐assisted channel model is proposed for stochastic multiple‐input multiple‐output (MIMO) unmanned aerial vehicle (UAV)‐to‐ground communications. The RIS is deployed on an additional UAV in the proposed model, which assists the UAV transmitter for reflecting its own signals to the mobile receiver (MR) on the ground level, thereby boosting the quality of signal transmission. In order to achieve a perfect beam alignment towards the desired direction, the reflection phase is regulated by considering the propagation distances among UAV, RIS, and MR. In this paper, we propose a three‐dimensional geometry‐based reconfigurable intelligent surface (RIS)‐assisted channel model for stochastic multiple‐input multiple‐output (MIMO) unmanned aerial vehicle (UAV)‐to‐ground communications, and modeling each RIS reflecting element as an anomalous reflector. Important propagation properties are deduced and investigated.

In this article, we propose a light weight, low profile Multiple Input Multiple Output (MIMO) antenna system for compact 5th Generation (5G) mmwave devices. Using a RO5880 substrate that is incredibly thin, the suggested antenna is made up of circular rings stacked vertically and horizontally on top of one another. The single element antenna board has dimensions of 12 × 12 × 0.254 mm3 while the size of the radiating element is 6 × 2 × 0.254 mm3 (0.56λ0 × 0.19λ0 × 0.02λ0). The proposed antenna showed dual band characteristics. The first resonance showed a bandwidth of 10 GHz with a starting frequency of 23 GHz to an ending frequency point of 33 GHz followed by a second resonance bandwidth of 3.25 GHz ranging from 37.75 to 41 GHz, respectively. The proposed antenna is transformed into a four element Linear array system with size of 48 × 12 × 0.254 mm3 (4.48λ0 × 1.12λ0 × 0.02λ0). The isolation levels at both resonance bands were noted to be >20 dB which shows high levels of isolation among radiating elements. The MIMO parameters such as Envelope Correlation Co-efficient (ECC), Mean Effective Gain (MEG) and Diversity Gain (DG) were derived and were found to be in satisfactory limits. The proposed MIMO system model is fabricated and through validation and testing of the prototype, the results were found to be in good agreement with simulations.

A dual-band, compact, high-gain, simple geometry, wideband antenna for 5G millimeter-wave applications at 28 and 38 GHz is proposed in this paper. Initially, an antenna operating over dual bands of 28 and 38 GHz was designed. Later, a four-port Multiple Input Multiple Output (MIMO) antenna was developed for the same dual-band applications for high data rates, low latency, and improved capacity for 5G communication devices. To bring down mutual coupling between antenna elements, a parasitic element of simple geometry was loaded between the MIMO elements. After the insertion of the parasitic element, the isolation of the antenna improved by 25 dB. The suggested creation was designed using a Rogers/Duroid RT-5870 laminate with a thickness of 0.79 mm. The single element proposed has an overall small size of 13 mm × 15 mm, while the MIMO configuration of the proposed work has a miniaturized size of 28 mm × 28 mm. The parasitic element-loaded MIMO antenna offers a high gain of 9.5 and 11.5 dB at resonance frequencies of 28 GHz and 38 GHz, respectively. Various MIMO parameters were also examined, and the results generated by the EM tool CST Studio Suite® and hardware prototype are presented. The parasitic element-loaded MIMO antenna offers an Envelop Correlation Coefficient (ECC) < 0.001 and Channel Capacity Loss (CCL) < 0.01 bps/Hz, which are quite good values. Moreover, a comparison with existing work in the literature is given to show the superiority of the MIMO antenna. The suggested MIMO antenna provides good results and is regarded as a solid candidate for future 5G applications according to the comparison with the state of the art, results, and discussion.

The review focuses on the emergence of 5G wireless communication and the need for multiple-input multiple-output antennas to support high-speed communication systems. The article discusses the advantages of MIMO antennas, including increased channel capacity and the ability to focus radio frequency energy on specific users. However, the challenges of creating compact MIMO antennas with ideal isolation are addressed, including short wavelengths, connection losses, constrained bandwidth, and path losses in the millimeter-wave range. Design techniques and methods to enhance the performance of conventional antennas for 5G applications are discussed, along with potential solutions for upcoming challenges. The article provides an overview of MIMO antennas for 5G applications, covering frequency bands, system architecture, advantages, challenges, advancements, performance enhancement techniques, design techniques, and state-of-the-art developments.

A low-profile planar multiple-input multiple-output (MIMO) antenna consisting of four elements with isolation improvement is proposed for 5G mm Wave (24–40) GHz applications. Each radiating element of the MIMO antenna comprises of a microstrip-fed tilted spade-shaped radiator with four asymmetrical slots and a partial ground plane. The antenna is optimized to resonate at 35 GHz covering a wide impedance bandwidth from 23.9 to 40.1 GHz. Two cross lines are then loaded between the antenna elements to improve the isolation >−30  dB. The MIMO structure with the decoupling lines is fabricated and tested. The measured results are in good correlation with the simulated results. Other MIMO performance metrics such as the envelope correlation coefficient (ECC), channel capacity loss (CCL), diversity gain (DG), and total active reflection coefficient (TARC) are examined, and the results are found to be satisfactory for the device to be used for mm-wave 5G MIMO applications. Also, the antenna’s performance metrics such as radiation efficiency, gain, and radiation patterns over the operating band are presented.

This paper presents a compact 5G wideband antenna designed for body-centric networks (BCN. The single element antenna design includes a simple T-shaped radiator patch with ring shaped ground plane and transformer impedance feedline. First, the antenna was simulated in free-space, and its resonant frequency is found to be 27 GHz, falling within 5G’s n261 band. The proposed single radiator antenna has a size of 23.375 mm 3 , and it offers a wide impedance bandwidth of 2.0 GHz (26–28 GHz). Parametric studies demonstrated that by increasing the length of slots in patch, the antenna frequency can be reduced further. Single radiator antenna is used as 8-element MIMO structure. Parallel adjacent antenna in X-direction has minimal coupling effect, whereas antenna placed in Y-direction has high coupling effect. Thus, coupling is reduced by etching a wall of slots in ground plane. It alters the surface current interference in Y-direction and limits the coupling effect. The antenna is investigated to use in body area network applications. To evaluate its on-body performance, an equivalent body model is virtually developed. The on-body performance is assessed by placing the antenna in close proximity to body model. Stable and robust performance is achieved for the on-body operation. At the resonant point, the antenna exhibits a reflection coefficient of -30 dB (free space) and -40 dB (on-body), high isolation of above 20 dB between adjacent radiators and above 30 dB for other radiators. Antenna has stable performance for different body tissues and on the non-planar structures. Bidirectional radiation pattern with gain of 2.53 dB and broadside type orientations with gain of 4.64 dB are achieved for free space and on body operations respectively. low specific absorption rate makes antenna safe for health care devices. Further, diversity performance is measured in terms of envelope correlation coefficient (ECC), and diversity gain (DG). Maximum Value of ECC is 0.005 and minimum value DG is 9.97 at 27 GHz which confirms the excellence of antenna for MIMO applications.

Millimeter-wave massive multiple-input multiple-output (MIMO) employs a lens antenna array for minimizing the radio frequency (RF) chains count, yet it remains as a challenge since the RF chain count is lesser when compared to the antennas. The beamspace channel estimation is defined as a sparse signal recovery problem through the exploitation of sparsity of beamspace channels. In the case of multi-user millimeter wave (mmWave) MIMO-OFDM systems, the critical task to lessen the cost as well as the complexity is the hybrid precoding attaining an adequate sum-rate. The conventional approaches related to the hybrid precoding works on the basis of the greedy or optimization techniques. These techniques suffer from higher complexity or contain sub-optimum performance. The main intent of this paper is to plan for the adaptive deep learning strategy for sparse channel estimation and hybrid precoding in millimeter-wave massive MIMO-OFDM communication system. The proposed methodology covers two main phases (a) uplink channel estimation, and (b) hybrid precoding for downlink data transmission. In the first phase, an adaptive deep neural network (ADNN) is used for performing the uplink channel estimation. Here, the benchmark dataset is used for training the information to be predicted at base station regarding the channel. Here, the ADNN-based channel estimation covers both channel amplitude estimation and channel reconstruction. Once the channel reconstruction is done, hybrid pre-coding performs the downlink data transmission that involves both digital and analog pre-coders. Here, the adaptive long short term memory (ALSTM) is used for performing the hybrid pre-coding, in which the estimated channel vectors is used for training. For both sparse channel estimation and hybrid-precoding, the trial-based red deer algorithm (T-RDA) is used for improvising the ADNN and ALSTM, in which it optimizes or tunes the training hidden neurons. The main objective of tuning the hidden neurons in both phases of T-RDA is to maximize the accuracy. When SNR equals 15 dB, the NMSE of the T-RDA-ADNN is 40%, 25%, 37.5%, and 34.78% improved than RDA-ADNN, SFO-ADNN, GWO-ADNN, and PSO-ADNN for channel estimation. Similarly, at SNR 20 dB, the spectral efficiency of T-RDA-ADNN is 37.5%, 43.48%, 22.22%, and 94.12% advanced than RDA-ADNN, SFO-ADNN, GWO-ADNN, and PSO-ADNN for hybrid precoding. Thus, the simulation outcomes show that the developed sparse channel estimation and hybrid pre-coding in mmWave massive MIMO-OFDM communication system has attained lesser error and high spectral efficiency when differentiated over the existing approaches.

A paradigm shift from Channel State Information (CSI)-dependent architectures to intelligent, AI-native air interfaces is required as 6G wireless systems advance. Conventional Multi-User Multiple-Input Multiple-Output (MU-MIMO) systems have substantial pilot overhead and computational complexity since they rely on explicit CSI for beamforming and interference management. This study suggests a novel Deep Unfolding Successive Over-Relaxation (DU-SOR) paradigm to overcome these constraints. In contrast to conventional end-to-end learning techniques that operate as \"black boxes,\" DU-SOR combines iterative residual refining with a sparse Graph Transformer. The network can intuitively solve the inverse problem without explicit channel matrix inversion thanks to this novel architecture, which uses graph priors to condition the signal estimation. Extensive empirical analyses show that the proposed framework accomplishes three main goals: (i) near-optimal performance, confirmed by a mutual information score of 0.98 at 20 dB SNR; (ii) mathematically proven scalable complexity, reducing the scaling order from [Formula: see text] to [Formula: see text] via sparse attention mechanisms; and (iii) robust generalisation across various channel conditions (Rayleigh, Rician, 3GPP UMi). This work offers a scalable foundation for sustainable AI-native 6G receivers by combining sparse-graph efficiency with CSI-free operation.

This work presents a small four-port multiple-input multiple-output (MIMO) antenna for Ultra Wideband (UWB) applications. Four monopole radiating components make up the suggested antenna. Every monopole is positioned perpendicularly to the components that surround it. This compact antenna, 40 mm × 40 mm, is printed on a single layer substrate (FR4) with a thickness of 1.6 mm and an ε r = 4.4. This antenna features an isolation of less than −14 dB and an impedance bandwidth (S11 < −10 dB) of 2.57–12.20 GHz. The average gain is 4.7 dBi and the envelope correction coefficient (ECC) is less than 0.15. The suggested antenna is a good option for UWB applications because of its Ultra Wide bandwidth and small footprint.