Multiple-input Multiple-output Technology Research Articles

IEEE 802.11ax Meet Edge Computing: AP Seamless Handover for Multi-Service Communications in Industrial WLAN

IEEE 802.11ax, as a new generation of wireless local area network (WLAN) standard, has great development potential for multi-service access in industrial WLAN with its characteristics of low-cost, quick-deployment and high-efficiency. However, it still faces the problem of quick and efficient access point (AP) seamless handover for multi-service communications due to terminal mobility and channel degradation. To solve the problem, combining the characteristics of orthogonal frequency division multiple access (OFDMA) technology and multi-user multiple-input multiple-output (MU-MIMO) technology, this paper firstly proposes an edge computing based IEEE 802.11ax multi-service bearer mechanism by dynamically allocating channel resource units (RUs). Secondly, a multi-service AP seamless handover mechanism based on edge computing is proposed, which consists of a channel scanning delay optimization method based on virtual AP sentinel, a handover trigger judgment algorithm considering mobility and RU reallocation, a multi-objective optimized AP handover model considering load balancing, transmission rate optimization and handover cost minimization with service attributes. Finally, we propose a multi-service AP seamless handover algorithm based on improved particle swarm optimization (PSO) to get optimized handover making-decision. Simulation results show that the proposed handover mechanism can reduce the handover delay significantly while realizing seamless handover accurately in multi-service industrial WLAN.

5G Wireless Networks

Everybody loves speed and moreover speedy internet, so its no surprise that every major telecom in the world is working to make it even faster. Smartphones, watches, homes, and cars are increasingly requiring stable internet connections. In order to survive in the world where in every second the speed changes and where we urge for more and more technology, here comes the fifth generation technology: 5G. In future, i.e., a world beyond 4G, some of the prime objectives that need to be fulfilled are increased capacity, improved data rate, decreased latency, and quality service. To meet these demands, large scale improvement in the cellular architecture of 5G is required .This paper basically lays emphasis on the 5th generation i.e. 5G cellular network architecture and some of the essential emerging technologies that can prove fruitful in humanizing the architecture and summiting the demands of users. This paper is contented with the details related to 5g with the prime focus on the massive multiple input multiple output technology and device-to-device communication (D2D). A general credible 5G cellular network architecture is being proposed with the guideline taken from the internet books and by the detailed study of the topic

Future of 5G Wireless System

Every major telecom in the globe is attempting to make it even faster because everyone loves speed and, more specifically, fast internet. Smartphone’s, Stable internet connections are becoming more and more important for watches, houses, and vehicles. The fifth generation of technology, or 5G, is coming to help us survive in a world where pace is changing every second and where we need more and more technology. Some of the most important goals that must be achieved in the future, or in a world beyond 4G, are higher capacity, improved data rate, lower latency, and quality service. Large-scale improvements in the 5G cellular architecture are necessary to meet these expectations. Essentially, this study emphasizes the architecture of the fifth generation (5G) of mobile networks and some of the most important upcoming technologies that can help meet user demands while humanizing the architecture. The primary focus of this paper's coverage of 5G details is device-to-device communication and huge multiple input multiple output technologies (D2D). A general, believable 5G cellular network architecture is put out using guidelines from online sources and thorough research on the subject

Downlink Massive MIMO Systems: Reduction of Pilot Contamination for Channel Estimation with Perfect Knowledge of Large-Scale Fading

Massive multiple-input multiple-output (MIMO) technology is considered crucial for the development of future fifth-generation (5G) systems. However, a limitation of massive MIMO systems arises from the lack of orthogonality in the pilot sequences transmitted by users from a single cell to neighboring cells. To address this constraint, a proposed solution involves utilizing orthogonal pilot reuse sequences (PRS) and zero forced (ZF) pre-coding techniques. The primary objective of these techniques is to eradicate channel interference and improve the experience of end users who are afflicted by low-quality channels. The assessment of the channel involves evaluating its quality through channel assessment, conducting comprehensive evaluations of large-scale shutdowns, and analyzing the maximum transmission efficiency. By assigning PRS to a group of users, the proposed approach establishes lower bounds for the achievable downlink data rate (DR) and signal-to-interference noise ratio (SINR). These bounds are derived by considering the number of antennas approaches infinity which helps mitigate interference. Simulation results demonstrate that the utilization of improved channel evaluation and reduced loss leads to higher DR. When comparing different precoding techniques, the ZF method outperforms maximum ratio transmission (MRT) precoders in achieving a higher DR, particularly when the number of cells reaches 𝛶𝛶𝑝𝑝=7.

Advances in MIMO Antenna Design for 5G: A Comprehensive Review.

Multiple-input multiple-output (MIMO) technology has emerged as a highly promising solution for wireless communication, offering an opportunity to overcome the limitations of traffic capacity in high-speed broadband wireless network access. By utilizing multiple antennas at both the transmitting and receiving ends, the MIMO system enhances the efficiency and performance of wireless communication systems. This manuscript specifies a comprehensive review of MIMO antenna design approaches for fifth generation (5G) and beyond. With an introductory glimpse of cellular generation and the frequency spectrum for 5G, profound key enabling technologies for 5G mobile communication are presented. A detailed analysis of MIMO performance parameters in terms of envelope correlation coefficient (ECC), total active reflection coefficient (TARC), mean effective gain (MEG), and isolation is presented along with the advantages of MIMO technology over conventional SISO systems. MIMO is characterized and the performance is compared based on wideband/ultra-wideband, multiband/reconfigurable, circular polarized wideband/circular polarized ultra-wideband/circular polarized multiband, and reconfigurable categories. The design approaches of MIMO antennas for various 5G bands are discussed. It is subsequently enriched with the detailed studies of wideband (WB)/ultra-wideband (UWB), multiband, and circular polarized MIMO antennas with different design techniques. A good MIMO antenna system should be well decoupled among different ports to enhance its performance, and hence isolation among different ports is a crucial factor in designing high-performance MIMO antennas. A summary of design approaches with improved isolation is presented. The manuscript summarizes the various MIMO antenna design aspects for NR FR-1 (new radio frequency range) and NR FR-2, which will benefit researchers in the field of 5G and forthcoming cellular generations.

Compact Sub 6 GHz Dual Band Twelve-Element MIMO Antenna for 5G Metal-Rimmed Smartphone Applications.

In this paper, a twelve-antenna system is designed for 5G smartphones with metal frames. The system is compact and operates on dual bands within the sub-6 GHz frequency range using multiple-input multiple-output (MIMO) technology. Two sets of six-antenna units are included in the system, arranged in a diagonal mirror-image configuration, and positioned at the center of the circuit board's longer edges. The profile height of each of the six-antenna units is only 3 mm, and the overall array dimensions are 105 × 3 × 3.1 mm3. A single antenna unit is 15 × 3 × 3.1 mm3 (0.173 λ × 0.035 λ × 0.036 λ, where λ equals the free-space wavelength of 3450 MHz). The arrangement of the antennas in the six-antenna units is parallel, with a 3 mm separation between adjacent antennas. The antenna structure comprises of an inverted L-shaped feed branch and two inverted L-shaped short-circuit branches integrated into part of the metal frame. The proposed array can form multiple resonance paths, achieving dual-band operation at 3300-3600 MHz and 4800-5000 MHz. The measured isolation of this twelve-antenna system within the operating frequency band is over 10 dB, and the measured antenna efficiency is greater than 36%. Therefore, the system is suitable for use in smartphones with high screen-to-body ratios and metal frames.

A Tutorial on Holographic MIMO Communications—Part III: Open Opportunities and Challenges

Holographic multiple-input multiple-output (HMIMO) technology, which uses spatially continuous surfaces for signal transmission and reception, is envisioned to be a promising solution for improving the data rate and coverage of wireless networks. In Parts I and II of this three-part tutorial on HMIMO communications, we provided an overview of channel modeling and highlighted the state-of-the-art in holographic beamforming. In this part, we will discuss the unique properties of HMIMO systems, highlighting the open challenges and opportunities that arise as the transceiver array apertures become denser and electromagnetically larger. Additionally, we explore the interplay between HMIMO and other emerging technologies in next-generation networks.

Sum Rate Analysis for Massive MIMO-NOMA Uplink System With Group-Level Successive Interference Cancellation

The deep integration between non-orthogonal multiple access (NOMA) and massive multiple-input multiple-output (MIMO) technology is a promising way to achieve massive connectivity and high capacity in B5G/6G wireless communication system. In this letter, a novel signal processing framework for massive MIMO-NOMA data transmission is proposed based on group-level successive interference cancellation (GLSIC), in which the users are grouped according to the distances to the base station (BS) and NOMA is applied among different groups by employing GLSIC to reduce the inter-group interference. The uplink sum rate is derived for the proposed GLSIC-based massive MIMO-NOMA system with minimum mean square error channel estimator and maximal ratio combiner at BS, and the effects of channel estimation error, inter-group pilot contamination, and imperfect GLSIC are analytically quantified in the derivation. Theoretical analysis and simulation results show that, under the same conditions, the proposed GLSIC-based system achieves higher uplink rate than the existing cluster-based MIMO-NOMA system with user-level SIC.

Performance analysis for MU-MIMO enabled LTE-U networks coexisting with D2D and WiFi network

LTE-Unlicensed (LTE-U) network is a type of cellular communication network operating the unlicensed spectrum. Offloading cellular traffic to WiFi or Device-to-Device (D2D) network can lead to interference among them. Applying Multiple-Input Multiple-Output (MIMO) technology in Cellular Base Station (CBS) and WiFi Access Point (WAP) can effectively reduce interference among D2D, WiFi and cellular networks. To our best knowledge, there is still no literature to explicitly study the characteristics of the traffic offloading in the Multiple-User MIMO (MU-MIMO) enabled network coexisting with D2D and WiFi networks. In this article, we thoroughly investigate the impact of D2D communication and MU-MIMO enabled WAP and CBS on the performance of the LTE-U network. More specifically, we derive the expressions of the downlink rates for cellular users, D2D users, and WiFi users with incomplete Channel State Information (CSI) feedback, and we validate our analysis through Monte-Carlo simulation. Numerous results illustrate the following conclusions. (i) Increasing the number of WiFi users, the length of CSI feedback, and the quantity of D2D pairs that reuse the channel with a single cellular user can increase the total throughput of the heterogeneous network. (ii) The total throughput decreases when more than two users are offloaded to D2D pairs, and increases as the number of offloaded users increases when less than six users are offloaded to WiFi network. (iii) Simultaneously offloading traffic to D2D pairs and WiFi network can obtain higher total throughput than offloading traffic to only one of them.

A Study of Mutual Coupling Suppression between Two Closely Spaced Planar Monopole Antenna Elements for 5G New Radio Massive MIMO System Applications

5G NR (new radio) introduces the concept of massive MIMO (multiple-input multiple-output) technology, in which a larger number of antenna arrays are installed on the transceiver. Due to the increased number of antenna elements allocated close to each other (approximately at a distance of half a wavelength), mutual coupling becomes a serious problem leading to performance degradation of the MIMO communication system. In this communication, two different configurations of closely spaced antenna array elements are studied. In order to reduce the mutual coupling, a combination of a metamaterial-based frequency-selective surface (FSS), a metallic strip, and a slot element in the ground plane is examined. It is found that the proposed technique significantly suppresses mutual coupling from −12 dB to −25 dB. Both designs are fabricated and experimentally validated. The simulation results are in good agreement with the measurements. The proposed mutual coupling reduction technique may be suitable for massive MIMO systems in fifth-generation (5G) new radio applications.

Massive MIMO Evolution Toward 3GPP Release 18

Since the introduction of fifth-generation new radio (5G-NR) in Third Generation Partnership Project (3GPP) Release 15, swift progress has been made to evolve 5G with 3GPP Release 18 emerging. A critical aspect is the design of massive multiple-input multiple-output (MIMO) technology. In this line, this paper makes several important contributions: We provide a comprehensive overview of the evolution of standardized massive MIMO features from 3GPP Release 15 to 17 for both time/frequency-division duplex operation across frequency range in (FR)-1 and FR 2-1. We analyze the progress on channel state information (CSI) frameworks, beam management frameworks and present enhancements for uplink CSI. We shed light on emerging 3GPP Release 18 problems requiring imminent attention. These include advanced codebook design and sounding reference signal design for coherent joint transmission (CJT) with multiple transmission/reception points (multi TRPs). We discuss advancements in uplink demodulation reference signal design, enhancements for mobility to provide accurate CSI estimates, and unified transmission configuration indicator framework tailored for FR 2-1 bands. For each concept, we provide system level simulation results to highlight their performance benefits. Via field trials in an outdoor environment at Shanghai Jiaotong University, we demonstrate the gains of multi-TRP CJT relative to single TRP at 3.7 GHz.

Maximum Exposure Evaluation for MIMO Based on Optimization Algorithm

IEC/IEEE FDIS 63195-2 requires the maximum exposure evaluation to determine if the product meets the radiation limit requirements specified by ICNIRP. The miniaturization and integration of millimeter wave antennas make it possible to deploy antenna arrays supporting Multiple-Input Multiple-Output (MIMO) technology in mobile terminals, which brings challenges to traditional exposure compliance testing. This is caused by the complex electromagnetic environment generated around the equipment by beam focusing technology and the difficulty in determining the maximum exposure of electromagnetic exposure dose by traditional measurement methods. However, mathematical model-based evaluation methods may produce overly conservative results, limiting the maximum allowable transmit power of 5G devices and resulting in wasted system performance. In this study, we take advantage of the optimization algorithm in searching for globally optimal solutions under multivariate constraints, and its search strategy is improved to evaluate the largest exposure of millimeter wave MIMO antenna arrays in the target region.

Optimization of the Compressive Measurement Matrix in a Massive MIMO System Exploiting LSTM Networks

Massive multiple-input multiple-output (MIMO) technology, which is characterized by the use of a large number of antennas, is a key enabler for the next-generation wireless communication and beyond. Despite its potential for high performance, implementing a massive MIMO system presents numerous technical challenges, including the high hardware complexity, cost, and power consumption that result from the large number of antennas and the associated front-end circuits. One solution to these challenges is the use of hybrid beamforming, which divides the transceiving process into both analog and digital domains. To perform hybrid beamforming efficiently, it is necessary to optimize the analog beamformer, referred to as the compressive measurement matrix (CMM) here, that allows the projection of high-dimensional signals into a low-dimensional manifold. Classical approaches to optimizing the CMM, however, are computationally intensive and time consuming, limiting their usefulness for real-time processing. In this paper, we propose a deep learning based approach to optimizing the CMM using long short-term memory (LSTM) networks. This approach offers high accuracy with low complexity, making it a promising solution for the real-time implementation of massive MIMO systems.

Random Time Division Multiplexing Based MIMO Radar Processing with Tensor Completion Approach

Automotive radar pursues low cost and high performance, and especially hopes to improve the angular resolution under the condition of a limited number of multiple-input–multiple-output (MIMO) radar channels. Conventional time division multiplexing (TDM) MIMO technology has a limited ability to improve the angular resolution without increasing the number of channels. In this paper, a random time division multiplexing MIMO radar is proposed. First, the non-uniform linear array (NULA) and random time division transmission mechanism are combined in the MIMO system, and then a three-order sparse receiving tensor of a range-virtual aperture-pulse sequence is obtained during echo receiving. Next, this sparse three-order receiving tensor is recovered by using tensor completion technology. Finally, the range, velocity and angle measurements are completed for the recovered three-order receiving tensor signals. The effectiveness of this method is verified via simulations.

Generalized Index Modulation for MIMO-OTFS Transmission

Recently, the combination of multiple-input multiple-output technology with orthogonal time frequency space modulation (MIMO-OTFS) has drawn extensive attention with the advantage of exploring the additional transmit diversity or spatial multiplexing of the MIMO scheme. Motivated by the potential spectral efficiency of multi-domain index modulation, in this paper, we propose a generalized index modulation based MIMO-OTFS (GIM-MIMO-OTFS) to convey extra information with the aid of the spatial and delay-Doppler indices. To reduce the supreme complexity of maximum likelihood (ML) detection with a large size of look-up table in GIM-MIMO-OTFS, a two stage index detector based on power information is presented. Furthermore, the analytical expression of average bit error probability (ABEP) is derived to evaluate the performance of the proposed scheme. Simulation results demonstrate the enhanced performance of the proposed scheme in high-mobility scenarios, and highlight the complexity and outperformance of the proposed detector compared to ML detector.

A Novel Approach to Increase Data Transfer Rate in WIFI Network

Due to the proliferation of devices and the rise of applications that rely heavily on data, the demand for high-speed data transfer in WiFi networks has been rising rapidly in recent years. However, due to their limitations in terms of data transfer rate and capacity, conventional WiFi networks have prompted the investigation of novel strategies to address these issues. By combining beamforming techniques with Multiple Input Multiple Output (MIMO) technology, this study proposes a novel strategy for increasing the data transfer rate in WiFi networks. Multiple data streams can be transmitted simultaneously using MIMO technology, effectively increasing bandwidth and data transfer rate. The proposed approach explains the potential of using a hybrid LiFi-WiFi network was also explored to further increase the data transfer rate in WiFi networks. LiFi technology uses light waves instead of radio waves to transmit data and has the potential to provide faster data transfer rates than WiFi networks. The research was motivated by the limitations of conventional approaches and the rising demand for high-speed data transfer in WiFi networks. The new solution proposed in this approach has the potential to address these limitations and significantly increase the rate of data transfer.

IMeP: Impedance Matching Enhanced Power-Delivered-to-Load Optimization for Magnetic MIMO Wireless Power Transfer System

Recently, multiple-input multiple-output (MIMO) technology has been introduced into magnetic resonant coupling (MRC) enabled wireless power transfer (WPT) systems for concurrent charging of multiple devices. However, impedance mismatching phenomena caused by strong TX-RX, TX-TX, or RX-RX coupling greatly affect the power delivered to load (PDL) in practical charging systems. To solve this issue, we propose an effective scheduling algorithm for Impedance Matching–enhanced PDL optimization in MIMO MRC-WPT systems (called IMeP ), which integrates the transmitter scheduling together with the impedance matching techniques, i.e., adjusting TX coils for tuning TX-RX/TX-TX coupling and grouping RXs to separate strongly coupled RX pairs. We formulate this as a joint optimization problem and decouple it into three sub-problems, i.e., current scheduling, coil adjustment, and RX grouping. We then solve them through alternating direction method of multipliers–based, randomized beamforming–based, and graph clique cover–based algorithms, respectively. Extensive experiments are performed on a prototype testbed, and the results demonstrate the effectiveness of our solution. Compared with the state-of-the-art power transfer efficiency maximization solution, the proposed algorithm IMeP achieves a 74.7× performance improvement of PDL on average.

Multi-Access Edge Computing (MEC) Based on MIMO: A Survey.

With the rapid development of wireless communication technology and the emergence of intelligent applications, higher requirements have been put forward for data communication and computing capacity. Multi-access edge computing (MEC) can handle highly demanding applications by users by sinking the services and computing capabilities of the cloud to the edge of the cell. Meanwhile, the multiple input multiple output (MIMO) technology based on large-scale antenna arrays can achieve an order-of-magnitude improvement in system capacity. The introduction of MIMO into MEC takes full advantage of the energy and spectral efficiency of MIMO technology, providing a new computing paradigm for time-sensitive applications. In parallel, it can accommodate more users and cope with the inevitable trend of continuous data traffic explosion. In this paper, the state-of-the-art research status in this field is investigated, summarized and analyzed. Specifically, we first summarize a multi-base station cooperative mMIMO-MEC model that can easily be expanded to adapt to different MIMO-MEC application scenarios. Subsequently, we comprehensively analyze the current works, compare them to each other and summarize them, mainly from four aspects: research scenarios, application scenarios, evaluation indicators and research issues, and research algorithms. Finally, some open research challenges are identified and discussed, and these indicate the direction for future research on MIMO-MEC.

Novel Method to Achieve Temperature-Stable Microwave Dielectric Ceramics: A Case in the Fergusonite-Structured NdNbO4 System.

Microwave dielectric ceramics with permittivity (εr) ∼ 20 play an important role in massive multiple-input multiple-output (MIMO) technology in 5G. Although fergusonite-structured materials with low dielectric loss are good candidates for 5G application, tuning the temperature coefficient of resonant frequency (TCF) remains a problem. In the present work, smaller V5+ ions (rV = 0.355 Å, with coordination number (CN) = 4) were substituted for Nb5+ (rNb = 0.48 Å with CN = 4) in the Nd(Nb1-xVx)O4 ceramics, which, according to in situ X-ray diffraction data, lowered the fergusonite-to-scheelite phase transition (TF-S) to 400 °C for x = 0.2. The thermal expansion coefficient (αL) of the high-temperature scheelite phase was +11 ppm/°C, whereas for the low-temperature fergusonite phase, it was + 14 < αL < + 15 ppm/°C. The abrupt change in αL, the associated negative temperature coefficient of permittivity (τε), and the minimum value of εr at TF-S resulted in a near-zero TCF ∼ (+7.8 ppm/°C) for Nd(Nb0.8V0.2)O4 (εr ∼ 18.6 and Qf ∼ 70,100 GHz). A method to design near-zero TCF compositions based on modulation of τε and αL at TF-S is thus demonstrated that may also be extended to other fergusonite systems.

Green NOMA based MU-MIMO transmission for MEC in 6G Networks

Mobile edge computing (MEC) is a distributed computing paradigm that brings computing and data storage closer to the network’s edge. This paper considers a multiple-input multiple-output (MIMO) uplink scenario where non-orthogonal multiple access (NOMA) users partially offload their data to a MEC server. The objective of this study is to minimize the total energy consumption during local computing, task offloading, and MEC computing. To this end, the base station optimizes power allocation vectors and task assignment coefficients under time and power constraints. The generalized singular value decomposition-based linear beamforming method integrates NOMA, MIMO, and MEC technologies. Due to the non-convex nature of the problem, a successive convex optimization (SCA) and alternation optimization (AO) based low-complex solution is proposed. The impact of the delay tolerance, the size of the offloaded task, and the distance of the users are investigated concerning energy consumption. The simulation results show that the proposed method achieves better energy performance than the orthogonal multiple access (OMA) schemes. More importantly, the performance gap increases when the data size is large, and the delay requirement is stringent, as 6G networks require.