Multiple Antenna Systems Research Articles

End-to-End Communication With Task-Driven CSI Acquisition in Multiple-Antenna Systems

End-to-End Communication With Task-Driven CSI Acquisition in Multiple-Antenna Systems

Hybrid Beam-Forming Techniques for 6G Terahertz Communication: Challenges

The terahertz band is the main pillar of 6G wireless communication system. It is difficult to meet the high data rate of 1Tbps by millimeter frequency support systems. The terahertz band suffers huge propagation loss limiting wireless distance. Terahertz band imposes ultra massive multiple input multiple output antenna (UM-MIMO) systems which produce high array gain with narrow beamforming. The conventional methods for MIMO beamforming are Analog and Digital beamforming. The fully digital beamforming methods utilize dedicated structure of DAC/ADC and RF chains. These structures increase hardware complexity and are power hungry. The analog beamforming structures utilize ADC/DAC with phase shifters with less hardware complexity but support less data rates. As a result, a hybrid beamforming method can be adapted for UM-MIMO systems. This paper investigates challenges in hybrid beamforming architecture which will address the low spatial degrees of freedom (SDoF) limitation in Terahertz (THz) Communication. The flexible hardware connections are proposed, in order to switch the system in an adaptive manner so as to minimize the power requirements.

Exploiting FAS for Cooperative NOMA-based Full-duplex mmWave Networks with Imperfections

The primary constraints inherent in the millimeter wave (mmWave) technology manifest as high path loss and limited range. As a result, a line-of-sight environment is necessary for a seamless connection between source and destination nodes. At the same time, the prevalence of intervening obstacles becomes increasingly pronounced, owing to the escalating densification of contemporary wireless networks. We address these inherent challenges by exploring the aid of non-orthogonal multiple access (NOMA) and fluid antenna system (FAS) technologies. Our proposed approach centers around deploying an N-user NOMA network for optimizing the base station’s resources and facilitating cooperative full-duplex communication. Furthermore, the integration of L-port FAS elevates the quality-of-service by designing a flexible and compact antenna tailored to meet the needs of mobile users. Most works ignore the imperfections of transceiver hardware that is critical for high-rate communication systems. In this work, we have considered both ideal and non-ideal transceiver hardware to analyze the importance of practical systems. The findings indicate that ten-port FAS performs better than the selection-combining diversity. Still, it necessitates approximately 600 ports to surpass the capabilities of a four-antenna maximum-ratio-combining scheme. Ultimately, we formulate the expressions for outage probability, considering residual self-interference, residual transceiver hardware impairment noise, and interference, and corroborate these expressions through Monte Carlo simulations.

Modulated Frequency Selective Doubly Curved Sub-Reflector for a Dual-Band Multiple Spot Beam Communication Satellite Antenna System

Modulated Frequency Selective Doubly Curved Sub-Reflector for a Dual-Band Multiple Spot Beam Communication Satellite Antenna System

Spectrum sensing for dynamic primary user with multiple transitions under Rayleigh distributed channel attenuation in additive Laplacian noise

We propose a real-time scenario of dynamic behavior of the primary user (PU) with multiple transitions under the Rayleigh distributed channel attenuation (RDCA) for spectrum sensing. We assume Multiple access interference (MAI) as an additive noise which is modeled using Laplacian noise model. Apart from this, we consider higher order modulation scheme such as Quadrature Amplitude Modulation (QAM) with its modulation order M. The Markov chain models the transitions of the PU using transition probabilities (TPs) which are functions of the Markov Chain parameters (MCPs) ψ and ξ. The MCPs are assumed to be known at the receiver. In improved absolute value cumulation detection (i-AVCD) scheme, decision statistic is obtained when the absolute value of received observation at the cognitive radio (CR) is raised to an exponent P with P∈(0,2]. The AVCD and ED (energy detection) are special cases of i-AVCD at P=1 and P=2, respectively. The TPs are used with i-AVCD to get a modified detection scheme, referred to as Mr: i-AVCD. The Mr refers to the term ‘modified’ under the effect of MCPs. Special cases, referred to as Mr: AVCD and Mr: ED are formed for the Mr: i-AVCD scheme at P=1 and P=2, respectively. Further, we consider the case of a multiple antenna system at the receiver. We derive closed-form expressions of the detection probability (PD) and false alarm probability (PF). Finally, we present the results using receiver operating characteristics (ROC) and PD vs. average SNR (γ). Our analytical findings are corroborated using a close match between simulations and analytical results. Besides this, the modified schemes have been compared with the conventional schemes. In conventional schemes, no information on MCPs is available at the receiver a priori. We find that the modified detection schemes (MDS) outperform conventional schemes. Further, we observe that performance of MDS degrades as we increase the value of M. We also observe that the spatial diversity improves the performance of the MDS.

Navigating The Complexity Overcoming Mobility Obstacles in Massive MIMO Systems with MIMO Antennas.

This research investigates the synergy between Massive Multiple Input, Multiple Output (MIMO) systems and mobility challenges, with a focus on the pivotal role played by Multiple Antenna Systems (MIMO antennas). Employing a sophisticated experimental setup featuring a 3.5 GHz Massive MIMO base station equipped with 64 MIMO antennas, mobile terminals on motorized platforms, and advanced RF measurement tools, the study explores adaptive beamforming, spatial multiplexing, and diversity techniques. Results from 100 experiments, each lasting 10 minutes, reveal that adaptive beamforming dynamically improves user tracking in response to mobility-induced channel variations. Spatial multiplexing and diversity techniques enhance throughput and reliability, especially in high user mobility scenarios. The quantitative findings align with existing literature, providing practical insights for the deployment of MIMO antennas. The study addresses limitations and proposes avenues for future research, enhancing our understanding of MIMO antenna applications and contributing to the evolution of wireless communication technologies in dynamic environments.

On the capacity of multiple antenna systems

On the capacity of multiple antenna systems

Mathematical modeling method based on heterogeneous cellular network algorithm and computer multi-dimensional space

Due to the rapid development of services such as computer multi-dimensional space, traditional cellular networks are quantified and diversified, and it is difficult to meet the future connection needs of green network users. The heterogeneous cellular network algorithm places multiple microcells and relay nodes under the macrocell. This multi-layer network architecture can not only shorten the data transmission link, but also reduce the energy consumption of base stations and terminals. In addition, through spectrum space reuse Capability and spectrum efficiency improve the efficiency of the system, but this also increases the number of base stations and network construction costs, and significantly increases energy consumption and operating costs of operators' electricity expenditures. In addition, in order to achieve parallel transmission of data, placing multiple millimeter wave input and output antenna systems in heterogeneous network microcells can meet the high-speed data needs of indoor users, but the antenna array requires many RF links to drive, which increases the hardware implementation. Complexity, cost and energy consumption. According to the above-mentioned problems, a reconfigurable modular robot is established based on the multi-dimensional computer space. It is composed of modules with the same interface and can be assembled into different configurations according to different tasks. Compared with the original robot, the reconfigurable modular robot is more adaptable to the work and environment, and flexible. Then the basic and core technologies such as kinematics, type synthesis, scale synthesis, error and control of the reconfigurable modular robot are mathematically modeled, so as to effectively apply and promote the reconfigurable modular robot in practice, and make it has theoretical and practical value.

Design and Fabrication of a 2-Port Multiple Antenna System for mmWave Application

The next-generation wireless communication technology heading towards the mmWave band requires multiple antenna systems to achieve high diversity, high data rates, and reliability. The design of multiple antenna systems is always associated with the problem of mutual coupling between antenna elements. In order to achieve better system performance, the mutual coupling between the elements has to be minimized. This work basically aims to minimize the mutual interaction among the antenna elements. A 2-port multiple antenna system is presented, with the defected ground structure as a decoupling technique, in order to minimize the mutual coupling. The single microstrip patch antenna is initially designed to operate at 24 GHz; later, it is transformed into a 2-port multiple antenna system. The transformed 2-port multiple antenna is loaded with the defective ground structure. The designed antenna system is fabricated, and practical measurements are carried out. The isolation achieved with defective ground structure through simulation is −27dB, and the practical measured value is −40dB. The 2-port multiple antenna system performance is assessed through the following metrics: Envelope Correlation Coefficient(ECC), Diversity Gain(DG), and Channel Capacity Loss(CCL). For the proposed 2-port multiple antenna the obtained values of ECC, DG and CLL are 0.004, 9.99dB and 0.4 bit/s/Hz. The results of the simulated structure are in good agreement with the fabricated structure. The result shows that defective ground is the better technique to achieve isolation between the closely placed antennas. The defective ground structure is the simplest technique in comparison with other techniques, such as metamaterial, energy band gap etc. The major novelty of the work includes, the design of a 2-port multiple antenna system with single slot and achieving the isolation more than −47dB without affecting the antenna resonating frequency.

Clustered Cell-Free Multi-User Multiple-Antenna Systems With Rate-Splitting: Precoder Design and Power Allocation

Clustered Cell-Free Multi-User Multiple-Antenna Systems With Rate-Splitting: Precoder Design and Power Allocation

Orthogonal Time Frequency Space and Predictive Beamforming-Enabled URLLC in Vehicular Networks

To fulfill the requirements of future intelligent transportation system in 6G era, ultra-reliable and low-latency vehicular communications is of great importance. In high-mobility scenarios, the conventional orthogonal frequency division multiplexing (OFDM) modulation may fail to work due to high Doppler spreads. Moreover, the dynamic network topology imposes challenges on aligning the beams in multiple antenna systems. In this context, this article introduces a new orthogonal time frequency space (OTFS) and sensing-assisted predictive beamforming framework for supporting reliable and low-latency vehicular communications. In particular, we will first overview the OTFS modulation scheme, which performs data transmission in the delay-Doppler (DD) domain and discuss its superiority in improving communication reliability in vehicular networks. Then the sensing-assisted predictive beamforming scheme will be introduced, which does not rely on dedicated pilots for beam pairing, leading to very low overhead and latency. Benefiting from the DD channel representation, we briefly discuss the potential of channel prediction. Lastly, the challenges and future research directions are summarized.

Multiple Antenna Systems in Mobile 6G: Directional Channels and Robust Signal Processing

In mobile communications, the trend since later fourth generation systems has been toward significantly larger numbers of antennas and higher carrier frequencies. This has led to numerous refinements and extensions of the channel models used, to account for newly encountered propagation characteristics. With increasing antenna numbers, the acquisition of channel state information (CSI) becomes more challenging, such that robust multiple antenna signal processing is required to cope with CSI imperfections. This article discusses important wireless channel characteristics and modeling aspects of fifth and sixth generation (6G) mobile, examines how these developments impact corresponding CSI acquisition techniques, addresses recent robust multiple antenna signal processing approaches, and specifically highlights features and potentials of 6G technologies.

Structured channel covariance estimation from limited samples for large antenna arrays

In massive multiuser multiple antenna systems, the knowledge of the users’ channel covariance matrix is crucial for minimum mean square error channel estimation in the uplink and it plays an important role in several multiuser beamforming schemes in the downlink. Due to the large number of base station antennas, accurate covariance estimation is challenging especially in the case where the number of samples is limited and thus comparable to the channel vector dimension. As a result, the standard sample covariance estimator may yield a too large estimation error which in turn may yield significant system performance degradation with respect to the ideal channel covariance knowledge case. To address such problem, we propose a method based on a parametric representation of the channel angular scattering function. The proposed parametric representation includes a discrete specular component which is addressed using the well-known MUltiple SIgnal Classification (MUSIC) method, and a diffuse scattering component, which is modeled as the superposition of suitable dictionary functions. To obtain the representation parameters, we propose two methods, where the first solves a nonnegative least-squares problem and the second maximizes the likelihood function using expectation–maximization. Our simulation results show that the proposed methods outperform the state of the art with respect to various estimation quality metrics and different sample sizes.

A Powerful Joint Modulation and STBC Identification Algorithm for Multiuser Uplink SC-FDMA Transmissions

Owing to the rapid development and broad adoption of multiple antenna communication systems over the past few years, space-time block coding (STBC) identification has emerged as a crucial responsibility for smart radios. The majority of previous analysis of STBC identification assumed that the utilized modulation schemes for single-user and uncoded broadcasts were known. This paper investigates the challenge of joint STBC and modulation identification for uplink transmissions with numerous users in single-carrier frequency division multiple access (SC-FDMA) systems using coded transmissions. Multi-user channel estimation brings us one step closer to implementing the proposed design in real-world systems. We additionally employ the channel decoder’s deliverables, which are common in many real-world systems, to enhance the identifying and estimating procedures. Mathematical findings prove that a recursive approach can be utilized to tackle the maximum likelihood (ML) problem of simultaneous STBC and modulation identification with channel estimation. Distinguishing the superimposed signals that originate at the base-station (BS) is accomplished with the use of the space-alternating generalized expectation-maximization (SAGE) algorithm. After that, an expectation-maximization (EM) engine is deployed to make the necessary adjustments to the parameters being considered for each user. The success of the above-mentioned architecture for usage in practical applications is demonstrated by the simulation results obtained under various conditions.

Comprehensive Analysis of Wireless Capsule Endoscopy Radio Channel Characteristics Using Anatomically Realistic Gastrointestinal Simulation Model

This paper presents a comprehensive study of radio channels related to capsule endoscopy communications in ultra wideband wireless body area networks (UWB-WBAN) utilizing multiple antenna systems. The research includes 363 channel realizations, obtained through simulations using an anatomically realistic voxel model and a capsule model. A capsule position is modelled in such a way that it moves throughout the entire intestinal tract. The study examines the frequency and time domain characteristics of the channels in various capsule locations, including the most challenging positions deep inside the tissues or far away from most of the antennas. Additionally, the propagation characteristics inside the abdominal tissue are studied by calculating the most obvious propagation paths based on power flow illustrations and reflecting the results with the channel impulse response analysis. The impact of capsule rotation is also studied. It is shown how small changes in capsule location can greatly impact on the channel characteristics if the thickness of the tissues between the capsule and the on-body antenna changes significantly. The paper concludes with statistical analysis of the channel data, including path loss and root mean square (RMS) delay spread. The results provide valuable insight into how the signal propagates inside different parts of the gastrointestinal tract. They show that channel attenuation remains moderate along most of the gastrointestinal tract, and that even the deepest locations in the small intestine area can be resolved with the use of directional on-body antennas and receivers with higher sensitivity.

Joint Precoding and Phase Shift Design in Reconfigurable Intelligent Surfaces-Assisted Secret Key Generation

Physical layer key generation (PLKG) is a promising technique to establish symmetric keys between resource-constrained legitimate users. However, PLKG suffers from a low key rate in harsh environments where channel randomness is limited. To address the problem, reconfigurable intelligent surfaces (RISs) are introduced to reshape the channels by controlling massive reflecting elements, which can provide more channel diversity. In this paper, we design a channel probing protocol to fully extract the randomness from the cascaded channel, i.e., the channels through reflecting elements. We derive the analytical expressions of the key rate and design a water-filling algorithm based on the Karush-Kuhn-Tucker (KKT) conditions to find the upper bound. To find the optimal precoding and phase shift matrices, we propose an algorithm based on the Grassmann manifold optimization methods. The system is evaluated in terms of the key rate, bit disagreement rate (BDR) and randomness. Simulation results show that our protocols significantly improve the key rate as compared to existing protocols. Compared to multiple-antennas systems without a RIS, our proposed method achieves an average 9.51 dB performance gain when the side length of an element is 1/4 wavelength and the Rician factor is 0 dB.

Dual-Band Shared-Aperture Multiple Antenna System With Beam Steering for 5G Applications

This brief presents a high-efficiency shared-aperture multiple antenna system. Unlike general shared-aperture antennas, the proposed antenna system with the size of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.384 {\times } 0.384 {\times } 0.171 {\mathrm {\lambda }} ^{3}$ </tex-math></inline-formula> makes high reuse the aperture in the two respective frequency bands, and the antenna structures of the two bands can each generate positive mutual enhancement for their radiating characteristics in the two bands. The flat Luneburg lens can realize beam steering capability for mm-wave antenna from 25.5 to 29.5 GHz with the gain of 19.3 dBi and improve the wide-angle scanning matching impedance for the Sub-6 GHz antenna from 3.2 to 3.45 GHz with the gain of 6.2 dBi. Meanwhile, as the radiating patch of the Sub-6 GHz antenna, the meta-surface can reduce the focal distance of the lens and maintain the high gain of the mm-wave antenna. Hence, a compact antenna system can achieve beam steering capabilities (up to 112°) in the Sub-6 GHz band and (up to 56°) mm-wave band with high gain, respectively. And the port isolation of the proposed antenna system between two frequency bands is generally better than 25 dB and even up to 40 dB at the Sub-6 GHz band. As reported in the simulated and measured results in a linear array, the antenna system shows good radiating performance with a dual-polarization state. Hence, the proposed multiple antenna system is a good candidate for 5G applications because of the high-efficiency, beam steering with high gain and full 5G band.

Discrete Phase Shifts of Intelligent Reflecting Surface Systems Considering Network Overhead.

In this study, the performance of intelligent reflecting surfaces (IRSs) with a discrete phase shift strategy is examined in multiple-antenna systems. Considering the IRS network overhead, the achievable rate model is newly designed to evaluate the practical IRS system performance. Finding the optimal resolution of the IRS discrete phase shifts and a corresponding phase shift vector is an NP-hard combinatorial problem with an extremely large search complexity. Recognizing the performance trade-off between the IRS passive beamforming gain and IRS signaling overheads, the incremental search method is proposed to present the optimal resolution of the IRS discrete phase shift. Moreover, two low-complexity sub-algorithms are suggested to obtain the IRS discrete phase shift vector during the incremental search algorithms. The proposed incremental search-based discrete phase shift method can efficiently obtain the optimal resolution of the IRS discrete phase shift that maximizes the overhead-aware achievable rate. Simulation results show that the discrete phase shift with the incremental search method outperforms the conventional analog phase shift by choosing the optimal resolution of the IRS discrete phase shift. Furthermore, the cumulative distribution function comparison shows the superiority of the proposed method over the entire coverage area. Specifically, it is shown that more than 20% of coverage extension can be accomplished by deploying IRS with the proposed method.

Multimodality in mmWave MIMO Beam Selection Using Deep Learning: Datasets and Challenges

The increasing availability of multimodal data holds many promises for developments in millimeter-wave (mmWave) multiple-antenna systems by harnessing the potential for enhanced situational awareness. Specifically, inclusion of non-RF modalities to complement RF-only data in communications-related decisions like beam selection may speed up decision making in situations where an exhaustive search, spanning all candidate options, is required by the standard. However, to accelerate research in this topic, there is a need to collect real-world datasets in a principled manner. This article presents an experimentally obtained dataset, composed of 23 GB of data, which aids in beam selection in vehicle-to-everything mmWave bands, with the goal of facilitating machine learning (ML) in the wireless communication required for autonomous driving. Beyond this specific example, the article describes methodologies of creating such datasets that use time synchronized and heterogeneous types of LiDAR, GPS, and camera images, paired with the RF ground truth data of selected beams in the mmWave band. While we use beam selection as the primary demonstrator, we also discuss how multimodal datasets may be used in other ML-based PHY-layer optimization areas, such as beamforming and localization.

Capacity-Oriented Envelope Correlation Coefficient for Multiple Antennas of Mobile Devices

In this article, a capacity-oriented envelope correlation coefficient (ECC) that incorporates a preferred channel model for assessing a multiple antenna system of a multiple-input-multiple-output (MIMO) mobile device is proposed. Originated from the rudimentary law of ergodic channel capacity, the ECC for multiple antennas (ECC-M) is proven to holistically reflect the impact of radiation patterns and total efficiencies of multiple antennas on channel capacity. The closed-form ECC-M expressions for Rayleigh fading channel model and ray-based spatial channel model are studied, leading to an easy-to-use ECC-M expression that approximately incorporates a realistic channel model. The correlation of the proposed ECC-M to the channel capacity is demonstrated through the Monte Carlo (MC) simulation of three four-element MIMO antenna testbeds in two channel models, showing that the antenna total efficiency and a realistic channel model involved in the ECC-M play an important role in assessing the performance of multiple antennas. It is justified that the difference in channel capacities of two multiple antenna systems is highly relevant to their ECC-Ms at high signal-to-noise ratios (SNRs). The proposed ECC-M is also experimentally validated through over-the-air (OTA) throughput measurement, revealing that the ECC-M can effectively assess the OTA performance of multiple antenna systems for MIMO terminal devices.