Showing papers on "Multi-user MIMO published in 2023"

A Review on Massive MIMO Antennas for 5G Communication Systems on Challenges and Limitations

Abstract: High data rate transfers, high-definition streaming, high-speed internet, and the expanding of the infrastructure such as the ultra-broadband communication systems in wireless communication have become a demand to be considered in improving quality of service and increase the capacity supporting gigabytes bitrate. Massive Multiple-Input Multiple-Output (MIMO) systems technology is evolving from MIMO systems and becoming a high demand for fifth-generation (5G) communication systems and keep expanding further. In the near future, massive MIMO systems could be the main wireless systems of communications technology and can be considered as a key technology to the system in daily lives. The arrangement of the huge number of antenna elements at the base station (BS) for uplink and downlink to support the MIMO systems in increasing its capacity is called a Massive MIMO system, which refers to the vast provisioning of antenna elements at base stations over the number of the single antenna of user equipment. Massive MIMO depends on spatial multiplexing and diversity gain in serving users with simple processing signal of uplink and downlink at the BS. There are challenges in massive MIMO system even though it contains numerous number of antennas, such as channel estimation need to be accurate, precoding at the BS, and signal detection which is related to the first two items. On the other hand, in supporting wideband cellular communication systems and enabling low latency communications and multi-gigabit data rates, the Millimeter-wave (mmWave) technology has been utilized. Also, it is widely influenced the potential of the fifth-generation (5G) New Radio (NR) standard. This study was specifically review and compare on a few designs and methodologies on massive MIMO antenna communication systems. There are three limitations of those antennas were identified to be used for future improvement and to be proposed in designing the massive MIMO antenna systems. A few suggestions to improve the weaknesses and to overcome the challenges have been proposed for future considerations.

Leveraging Deep Neural Networks for Massive MIMO Data Detection

Abstract: Massive multiple-input multiple-output (MIMO) is a key technology for emerging next-generation wireless systems. Utilizing large antenna arrays at base-stations, massive MIMO enables substantial spatial multiplexing gains by simultaneously serving a large number of users. However, the complexity in massive MIMO signal processing (e.g., data detection) increases rapidly with the number of users, making conventional hand-engineered algorithms less computationally efficient. Low-complexity massive MIMO detection algorithms, especially those inspired or aided by deep learning, have emerged as a promising solution. While there exist many MIMO detection algorithms, the aim of this magazine article is to provide insight into how to leverage deep neural networks (DNN) for massive MIMO detection. We review recent developments in DNN-based MIMO detection that incorporate the domain knowledge of established MIMO detection algorithms with the learning capability of DNNs. We then present a comparison of the key numerical performance metrics of these works. We conclude by describing future research areas and applications of DNNs in massive MIMO receivers.

Massive MIMO Communication With Intelligent Reflecting Surface

Abstract: This paper studies the feasibility of deploying intelligent reflecting surfaces (IRSs) in massive multiple input multiple-output (MIMO) systems to improve the performance of users in the service dead zone. One question of paramount importance is as follows: if the overhead of channel training and the computational complexity of algorithm design arising from the huge number of IRS reflecting elements and base station (BS) antennas have to be controlled, can we provide reasonable performance to the users with weak direct channels? This paper provides an affirm answer to this question. Specifically, to reduce the channel training overhead, we consider an appealing protocol for the uplink communication in the IRS-assisted massive MIMO systems. Under this protocol, the IRS reflection coefficients are optimized based on the channel covariance matrices, which are generally fixed for many coherence blocks, to boost the long-term performance. Then, given the IRS reflecting coefficients, the BS beamforming vectors are designed in each coherence block based on the effective channel of each user, which is the superposition of its direct and reflected user-IRS-BS channels, to improve the instantaneous performance. Since merely the user effective channels are estimated in each coherence block, the training overhead of this protocol is the same as that in the legacy wireless systems without IRSs. Moreover, in the asymptotic regime that the numbers of IRS elements and BS antennas both go to infinity with a fixed ratio, we manage to first characterize the minimum mean-squared error (MMSE) estimators of the user effective channels and then quantify the closed-form user achievable rates as functions of channel covariance matrices with channel training overhead and estimation error taken into account. Interestingly, it is shown that the properties of channel hardening and favorable propagation still hold for the user effective channels, and satisfactory user rates are thus achievable even if simple BS beamforming solutions, e.g., maximal-ratio combining, are employed. Finally, thanks to the rate characterization, we design a low-complexity algorithm to optimize the IRS reflection coefficients based on channel covariance matrices.

A Comprehensive Survey on MIMO Visible Light Communication: Current Research, Machine Learning and Future Trends

Abstract: Visible light communication (VLC) has contributed new unused spectrum in addition to the traditional radio frequency communication and can play a significant role in wireless communication. The adaptation of VLC technology enhances wireless connectivity both in indoor and outdoor environments. Multiple-input multiple-output (MIMO) communication has been an efficient technique for increasing wireless communications system capacity and performance. With the advantages of MIMO techniques, VLC can achieve an additional degree of freedom. In this paper, we systematically perform a survey of the existing work based on MIMO VLC. We categorize the types of different MIMO techniques, and a brief description is given. Different problem-solving approaches are given in the subsequent sections. In addition, machine learning approaches are also discussed in sufficient detail. Finally, we identify the future study direction for MIMO-based communication in VLC.

MIMO-OFDM Techniques for Wireless Communication System: Performance Evaluation Review

Abstract: The use of multiple antennas in wireless communication systems has resulted in multiple channels that facilitate the speed of data transfer and improved channel capacity. This technique that basically involves multiple input and multiple output (MIMO) antennas helps to improve system performance by reducing bit error rate (BER) while increasing signal to noise ratio (SNR). Also, the use of orthogonal frequency division multiplexing (OFDM) has helped in mitigating inter-symbol interference (ISI). A combination of MIMO and OFDM produces the MIMO-OFDM scheme. This paper reviewed the performance of BER in MIMO-OFDM system considering various digital modulation techniques. An empirical review of previous studies on MIMO-OFDM system regarding BER performance evaluation was carried out. The study demonstrated the performance of digital modulation schemes in OFDM system with respect the Quadrature Amplitude Modulation (QAM). The results of the simulation based on MATLAB code revealed that lower order modulation yielded better BER performance than higher order. Furthermore,MIMO-OFDM system was modeled in MATLAB/Simulink and simulated to show that the use of multiple antennas at the transmitter and receiver helps in improving the performance of wireless communication system by reducing BER while increasing SNRconsidering two multipath channels – Rayleigh and Rician.

Design, Challenges and Developments for 5G Massive MIMO Antenna Systems at Sub 6-GHz Band: A Review

Abstract: Massive multiple-input multiple-output (mMIMO) is a wireless access technique that has been studied and investigated in response to the worldwide bandwidth demand in the wireless communication sector (MIMO). Massive MIMO, which brings together antennas at the transmitter and receiver to deliver excellent spectral and energy efficiency with comparatively simple processing, is one of the main enabling technologies for the upcoming generation of networks. To actualize diverse applications of the intelligent sensing system, it is essential for the successful deployment of 5G—and beyond—networks to gain a better understanding of the massive MIMO system and address its underlying problems. The recent huge MIMO systems are highlighted in this paper’s thorough analysis of the essential enabling technologies needed for sub-6 GHz 5G networks. This article covers most of the critical issues with mMIMO antenna systems including pilot realized gain, isolation, ECC, efficiency, and bandwidth. In this study, two types of massive 5G MIMO antennas are presented. These types are used depending on the applications at sub-6 GHz bands. The first type of massive MIMO antennas is designed for base station applications, whereas the most recent structures of 5G base station antennas that support massive MIMO are introduced. The second type is constructed for smartphone applications, where several compact antennas designed in literature that can support massive MIMO technology are studied and summarized. As a result, mMIMO antennas are considered as good candidates for 5G systems.

Joint Communication and Sensing Toward 6G: Models and Potential of Using MIMO

Abstract: The sixth-generation (6G) network is envisioned to integrate communication and sensing functions, so as to improve the spectrum efficiency and support explosive novel applications. Although the similarities of wireless communication and radio sensing lay the foundation for their combination, there is still considerable incompatible interest between them. To simultaneously guarantee the communication capacity and the sensing accuracy, the multiple-input and multiple-output (MIMO) technique plays an important role due to its unique capability of spatial beamforming and waveform shaping. However, the configuration of MIMO also brings high hardware cost, high power consumption, and high signal processing complexity. How to efficiently apply MIMO to achieve balanced communication and sensing performance is still open. In this survey, we discuss joint communication and sensing (JCAS) in the context of MIMO. We first outline the roles of MIMO in the process of wireless communication and radar sensing. Then, we present current advances in both communication and sensing coexistence and integration in detail. Three novel JCAS MIMO models are subsequently discussed by combining cutting-edge technologies, i.e., cloud radio access networks (C-RANs), unmanned aerial vehicles (UAVs), and reconfigurable intelligent surfaces (RISs). Examined from the practical perspective, the potential and challenges of MIMO in JCAS are summarized, and promising solutions are provided. Motivated by the great potential of the Internet of Things (IoT), we also specify JCAS in IoT scenarios and discuss the uniqueness of applying JCAS to IoT. In the end, open issues are outlined to envisage a ubiquitous, intelligent, and secure JCAS network in the near future.

A Comprehensive Review and Comparative analysis of 5G and 6G based MIMO Channel Estimation Techniques

Abstract: A wireless network's overall performance is greatly impacted by the accuracy of its channel estimate. Deep learning has also shown to be a significant advancement in improving communication reliability and lowering processing complexity for 5G and beyond networks. Massive multiple-input multiple-output (MIMO) and mmWave communications are disruptive technologies that have been implemented into fifth-generation (5G) and subsequent wireless communication standards, such as 6G, in order to handle the increasing wireless data traffic and maintain connections. MIMO systems use space multiplex by using a variety of antennas to increase efficiency at a specifically used bandwidth. MIMO allows for numerous sources and sinks to share a single communication channel. The characteristics of these networks are their spectral variety and their ability to multiplex spatially. This study still provided an overview of MIMO, examined MIMO channel estimation methods based on the 5G and 6G wireless communication standards, and analysed MIMO channel estimation methods for the coexistence of these two wireless network generations.

Large MIMO Channel Estimation Study Based on Independent Component Analysis

Abstract: MIMO systems, which consist of multiple transmitting and receiving antennas, are used as a method for effective use of frequency bandwidth. In general, signal separation in MIMO requires a known channel matrix. However, using Independent Components Analysis, signal separation is possible even when the channel matrix is unknown. On the other hand, if the channel matrix is known, MIMO technology may be efficiently utilized by precoding in the reverse direction line of TDD. In this study, we examined whether ICA can be used for signal separation and channel information estimation. We report that signal detection and channel estimation in large-scale MIMO can be performed without any problems.

A Scalable Precoding Processor for Large-Scale MU-MIMO Systems

Abstract: The number of devices served by baseband stations is constantly increasing due to the rising data traffic in modern communication systems. In order to support large-scale multi-user multiple-input multiple-output (MU-MIMO) systems and achieve their capacity, it is necessary to consider power allocation and user selection along with precoding. This paper introduces a scalable MU-MIMO precoding processor that solves the joint optimization problem for precoding, power allocation, and user selection. We define custom vector instructions and dedicate vector arithmetic operators based on the RV32IM instruction set architecture to efficiently support various MU-MIMO baseband processing scenarios. The proposed vector operators include parallel dual-precision multipliers to enable energy-efficient processing by adjusting the computing resolution of each step without degrading the algorithm-level quality. The proposed processor is fabricated using 28nm CMOS technology and is capable of solving the state-of-the-art joint optimization problem in only 0.51ms for the $64\times 64$ large-scale MU-MIMO configuration. Our processor achieves up to 17.4 times higher processing efficiency compared to previous precoder design, even when supporting the largest number of users and the most complicated algorithm.

Mitigating Interference and Improving the SINR in a Discrete Time Frame of a Downlink MU-MIMO Transmission in 5G and Beyond Wireless Networks

Abstract: Multiple-input, multiple-output (MIMO) wireless system technologies have attracted a lot of attention because they dramatically increase the capacity of band-limited wireless channels to meet the demands of high data-rate wireless communications. To keep up with the wireless cellular network's users' exponential expansion and their desire for high data rates, this quality is essential. However, the use of higher frequencies results in smaller cells, which exacerbates already-present issues like interference. This is particularly evident in mobile User Equipment (UE) that traverses the network. At the downlink of the Multi-User MIMO (MU-MIMO), researchers have made an effort to address this issue to improve Quality of Service (QoS) metrics such as outage probability, Signal-to-Interference-plus-Noise ratio (SINR), etc. However, it has been shown that the majority of the algorithms adopted by researchers to study the downlink MU-MIMO system are computationally complex. Although, this is partly due to the dynamic nature of the aspects that must be taken into account in order to reflect real-world events. The effects of which can be seen as interference, outage, energy consumption, security, link and capacity reliability, etc. In addressing these concerns, most work inadvertently trade-off the computational complexity to investigate these effects or put aside factors such as the mobility state of the UE to lower complexity and investigate the downlink MU-MIMO. This paper proposes an Efficient Algorithm for Downlink (EMD-MU-MIMO) for Fifth-Generation and Beyond (B5G) networks using a closed-form outage probability of a discrete-time frame of MU-MIMO Transmission. In comparison to the conventional IEEE 802.11ax algorithm, the proposed algorithm mitigates interference in the downlink MU-MIMO by 7.5% and improves the SINR by 26.1%.

Comparison Energy Efficiency and Spectral Efficiency in Beamspace MIMO and Beamspace MIMO-NOMA System Model

Abstract: There are ongoing research interests in the past decade to develop wireless communication systems and advance information rate limits. Therefore, to achieve future requirements and increase network capacity, the first method is to use millimeter wave (mmWave), which is essential for the upcoming 5G wireless communication technology. However, some challenges are encountered when using both mmWave and Massive MIMO in the spectrum and power efficiency to achieve optimal performance. Beamspace (BS) MIMO is a discovery in Massive MIMO, which is essential for making an exchange between energy efficiency (EE) and spectral efficiency (SE) in BS-MIMO. Therefore, BS-MIMO can increase network capacity and reduce energy consumption by significantly reducing the required number of radio frequency (RF) chains. The problem with the traditional method is that the beam can only support one user, not more at the same time and frequency resources. In this paper, we propose to use multiple users (MU) with non-orthogonal multiple access (NOMA) in the beamspace Massive MIMO. The method is integrating the NOMA with BS-MIMO to create a new configuration called BS-MIMO-NOMA. In this paper, we present simulation performance among three methods as fully digital MIMO, BS-MIMO, and BS-MIMO-NOMA. Simulation results show that the fully digital MIMO system shows the worst EE performance compared to other methods. In addition, the BS-MIMO-NOMA method can achieve better spectrum efficiency performance compared to the beamspace-specific MIMO method. This paper aims to make the trade-off between the EE and SE in terms of best performances. In the future, we propose the use of power optimization iterative method with minimal complexity to realize the best EE performance.

Performance Analysis of Zero-Forcing Precoding in Multi-Cell One-Bit Massive MIMO Downlink

Abstract: This work investigates the downlink performance of a multi-cell massive multiple-input multiple-output (MIMO) system that employs one-bit analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) in the receiving and transmitting radio frequency (RF) chains at each base station (BS) in order to reduce the power consumption. We utilize Bussgang decomposition to derive the minimum mean squared error (MMSE) channel estimates at each BS based on the quantized received uplink training signals, and the asymptotic closed-form expressions of the achievable downlink rates under one-bit quantized zero-forcing (ZF) precoding implemented using the estimated channels. The derived expressions explicitly show the impact of quantization noise, thermal noise, pilot contamination, and interference, and are utilized to study the number of additional antennas needed at each BS of the one-bit MIMO system to perform as well as the conventional MIMO system. Numerical results verify our analysis, and reveal that despite needing more antennas to achieve the same sum average rate, the one-bit massive MIMO system is more energy-efficient than the conventional system, especially at high sampling frequencies.

Physical Layer Security in MIMO Relay-Based Cognitive Radio Network

Abstract: AbstractCognitive radio networks are one of the predominant technologies to solve the spectrum scarcity problem. In this paper we tackle the problem of secure and safe data transmission between secondary user transmitter and secondary user receiver through relays in the presence of eavesdroppers in cognitive radio-based MIMO system. MIMO stands for Multiple-Input Multiple-Output. MIMO is a wireless technology that increases the data capacity with the help of multiple transmitting and receiving antennas. In this work, the best amplify and forward relay to maximize the secrecy capacity in a MIMO system is selected. The simulation and analytical results show the improved performance through secrecy capacity and secrecy outage probability.KeywordsCognitive radioSecrecy rateSecrecy outage probabilityMIMO

Downlink Cell-Free Fixed Wireless Access: Architectures, Physical Realities, and Research Opportunities

Abstract: Recently, a new paradigm of wireless access, termed as cell-free massive multiple-input multiple-output (MIMO), has drawn significant research interest. Its primary distinction from conventional massive MIMO aided cellular networks is the ability to eliminate the detrimental inter-cell interference (ICI), or to convert ICI, into extra power for the intended signal via a multi-cell cooperation approach originated from network MIMO. However, the information-theoretical limit of cell-free access is achieved at the expense of large network configuration overhead and high MIMO processing complexity. Because of the dynamic nature of wireless channels, the global channel state information (CSI) invoked for network MIMO quickly becomes outdated, leading to performance degradation. This article focuses on the cell-free implementation of fixed wireless access (FWA), a complementary solution to fiber-to-the-premise (FTTP) where the latter is prohibitively expensive. In particular, we discuss the centralization architectures and channel characteristics of cell-free FWA, as well as their joint implications on imperfect CSI performance. Moreover, measurement-based offline simulations show that the long coherence time (‘quasi-static’) assumption of real-world FWA channels is only valid against a completely motionless background, and, thus, it should not be used in FWA system design or performance analysis. Finally, we present new research opportunities for cell-free FWA in terms of physical infrastructure, data processing, and machine learning.

Beamforming Technique for Improving Physical Layer Security in an MIMO-OFDM Wireless Channel

Abstract: The open nature of the wireless medium leads to the growing technical literature on solutions and techniques for increasing the privacy and security of a wireless communication channel. This work focuses on implementing the beamforming technique incorporated with a combination of MIMO-OFDM techniques for increasing physical layer security in the downlink of a wireless communication channel. The rectangular antenna array has been employed at the Tx side of an MIMO-OFDM channel with two orthogonal polarizations. This results in an improvement in the downlink performance due to a reduction in a duration of the channel sounding procedure compared to its uplink counterpart. We have used the WINNER II module from MathWorks’ MATLAB to simulate a realistic wiretap channel including Alice (to represent a sender), Bobs (to represent users), and Eve (to represent the information leakage). We have numerically estimated the success rate of Eve and physical layer security with performing a beamforming technique, compared to the available techniques without any beamforming technique, in an MIMO-OFDM wireless channel. Although physical layer security is affected by power, we have demonstrated that the beamforming technique with the technique of assigning subcarriers for Bobs can significantly improve the physical layer security and thereby overcome information leakage in the wiretap channel.

Single Cluster Multiple-Input Multiple-Output (MIMO) Non-Orthogonal Multiple Access (NOMA) Transmission

Abstract: To improve spectral efficiency in multi-cell systems, we propose a multiple-input multiple-output (MIMO) non-orthogonal multiple access technique that simultaneously transmits multiple data streams to a cluster consisting of one cell-center user and one cell-edge user. Based on the MIMO channel state of the cell-center user, the proposed technique for single-cell systems finds the receive beamforming matrix for the user and performs power allocation to its data streams. Considering the MIMO channel state of the cell-edge user and interference from the cell-center user, the technique designs the receive beamforming matrix for the cell-edge user and allocates the power for the user to its data streams. By extending this technique to multi-cell systems, the proposed technique finds the receive beamforming matrix for the cell-center user and performs power allocation to its data streams according to its MIMO channel state and interference from neighboring cells. The receive beamforming matrix design and power allocation for the cell-edge user is performed based on its MIMO channel state, interference from the cell-center user, and interference from neighboring cells. Simulation results demonstrate that the proposed technique achieves better performance than the existing techniques in terms of data rates and outage probabilities for the users.

Towards Extra Large-Scale MIMO: New Channel Properties and Low-Cost Designs

Abstract: Extra large-scale multiple-input multiple-output (MIMO) has been recognized as one of the potential development directions of massive MIMO. By employing even more antennas than massive MIMO in the fifth-generation era, extra large-scale MIMO can further exploit the spatial domain resources and enable ultra high data rates, low latency communications as well as emerging applications, such as sensing and localization, in sixth-generation mobile communication systems. However, with the increase of the size of the antenna array, and the decrease of the distance between a user and the array, new channel properties, that did not manifest in conventional massive MIMO, start to kick in. Most importantly, existing research strategies pertaining to massive MIMO cannot be directly applied or simply extended to fit the extra large-scale MIMO case. Moreover, increasing the number of antennas will inevitably boost the total cost, which refers to not only the high hardware cost, but also the burden of vast processing and computations as well as the substantial training overhead. In this paper, we make a survey on the state-of-the-art on the new channel properties of and low-cost designs for extra large-scale MIMO systems. Particularly, we pursue a mathematical analysis to explain why the new features appear and illustrate how they affect the system model. Furthermore, we summarize and compare the low-cost designs from various perspectives and give our suggestions from a practical deployment point of view.

A Practical Channel Estimation Strategy for XL-MIMO Communication Systems

Abstract: Extremely large-scale massive MIMO (XL-MIMO) has been emerged as an innovative technique for future 6G communication. Channel state information (CSI) acquisition is a crucial but challenging task in XL-MIMO wireless systems due to the larger number of base station (BS) antennas. In this letter, we investigate a practical strategy to realize efficient channel estimation for XL-MIMO communication systems with the consideration of hybrid-field channel model. Different from the existing work requiring the specific proportion of the number of far-field and near-field channel paths as a prior knowledge, which is not feasible in practical communications, our method aims to provide a criterion to determine the value of proportion first and then acquire the corresponding estimated channel components. Simulation results show the effectiveness and superiority of our proposed channel estimation method as compared to the benchmarks.

Performance Evaluation of MIMO System with Different Receiver Structures

Abstract: Spatial diversity has attained great impact on future wireless communications; especially in multiple input and multiple output (MIMO) systems. MIMO technology permits for more effectual use of the radio spectrum and empowers sophisticated data rates, improved coverage, and enhanced reliability. MIMO is now a practical technology for medical and other healthcare facilities that are time-constrained. However, the recital of MIMO systems depends upon the effective channel modelling and the improvisation has been achieved by incorporating reliable receiver structures like matched filter, decorrelator, and minimum mean square error filtering (MMSE). Hence, the designer has to analyze the MIMO system in various fading environments in order to achieve high performance in terms of capacity, BER and throughput. Therefore, this work mainly focused on analyzing the recital of MIMO system in terms of capacity over Raileigh fading channel. Further, the capacity has been evaluated for various receiver structures having matched filter, decorrelator and MMSE filters. The capacity of MIMO system with different receiver structures has been evaluated for 2×2, 4×4, 8×8 MIMO configurations over Raleigh fading environment.

Capacity Analysis and Rate Maximization Design in RIS-Aided Uplink Multi-User MIMO

Abstract: <p>Reconfigurable intelligent surface (RIS) has recently drawn intensive attention due to its potential of simultaneously realizing high spectral and energy efficiency in a sustainable way. This paper focuses on the design of efficient transmission methods to maximize the uplink sum throughput in a RIS-aided multi-user multi-input multi-output (MU-MIMO) system. To provide an insightful basis, the channel capacity of RIS-aided MU-MIMO is theoretically analyzed. Then, the conventional transmission schemes based on orthogonal multiple access are presented as the baseline. From the information-theoretic perspective, we propose two novel schemes, i.e., \textit{joint transmission} based on the semidefinite relaxation of quadratic optimization problems and \textit{opportunistic transmission} relying on the best user selection. The superiority of the proposed schemes over the conventional ones in terms of achievable rates is justified through simulation results.</p>

Comparative Analysis of MIMO Multiuser Signal Detection

Abstract: The advancements in wireless communication have been incredibly helpful to our modern way of life. The many put in and much product technology, which involves using several broadcasts and receive antennas, will improve this. The high SNR system makes use of MIMO to boost capacity. Supporting more speed within the many put in and much product system is possible through use of spatial multiplexing, which also provides spatial diversity gain. There are typically several users of a communication system all using the same radio bandwidth. Here, each user can send their own data stream from many to one at once, or the base station can send out its own data stream for all users to decode from one to many, all thanks to the system's many antennas. In the case of a single-user MIMO system, this is typically attributed to the system's increased flexibility as a result of using many antennas.

Analyses of Virtual MIMO Multi-User System Performance with Linear Precoding Schemes Using Indoor Measurements at 5 GHz

Abstract: In this paper, based on 5 GHz indoor multi-user measurements, linear precoding schemes such as zero-forcing (ZF), minimum mean square error (MMSE) and successive interference cancelation (SIC) are applied in the base station in order to investigate the performance of virtual multi-input multi-output (MIMO) over single-user MIMO system. However, to form a virtual MIMO multi-user system, the resources of two users are brought together. In order to achieve a low spatial correlation, two spaced antennas in the MS have been chosen and four spaced antennas elements in BS have been selected. Therefore, the resources of two users (U1 and U2) are brought together to form a 4 × 4 virtual MIMO multi-user system with the BS. The properties of the user_1 (U1) and user_2 (U2) will be analyzed and compared to those properties of virtual MIMO multi-user system formed by U1 and U2. In most cases, the maximum achievable rate is seen with virtual MIMO multi-user compared to single-user MIMO. So virtual MIMO multi-user is desirable for boosting system capacity than single-user MIMO.

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

Abstract: 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.

Massive-MIMO Based RSMA Under Nakagami-m Channel Over 6G mURLLC Wireless Networks

Abstract: The sixth generation (6G) mobile wireless networks are expected to provide massive ultra-reliable and low-latency communications (mURLLC) for data services, which require extremely stringent quality-of-services (QoS) with massive connectivity. Rate splitting (RS) multiple access schemes have been proposed recently for tackling the difficulty of the massive access yielded by a large number of mobile users (MUs) requesting to connect to a single base station. Massive multiple-input and multiple-output (massive-MIMO) communication is considered a promising solution to serve massive MUs in 6G wireless networks. However, how to apply RS schemes into massive-MIMO techniques to support the massive access has not been sufficiently studied. In this paper, we propose to integrate RS schemes with massive-MIMO techniques to achieve mURLLC transmissions under a Nakagamir $m$ fading wireless channel. First, we establish the system model for the integrated RS and massive-MIMO schemes. Then, we derive closed-form expressions for the signal-to-interference-plus-noise ratios (SINRs) under a Nakagami- $-m$ fading channel and obtain the channel capacity. Finally, we use numerical analyses to validate and evaluate our proposed RS and massive-MIMO integrated schemes.

Eight-Planar-Monopole MIMO Circular Array Generating Eight Uncorrelated Waves for 6G Upper Mid-Band 8 x 8 MIMO Access Points

Abstract: For next-generation or six-generation (6G) mobile communications, the 8 x 8 MIMO operation is envisioned for the user. In this case, as compared to the fifth-generation (5G) mid-band 4 x 4 MIMO operation, a much larger spectral efficiency can be expected for the user, which in turn will effectively increase the user-experienced data throughput with a fixed carrier bandwidth. For such applications, to transmit eight MIMO streams for the 6G 8 x 8 MIMO access point, a simple yet compact MIMO array formed by eight planar monopoles arranged in a circular array with radial metal walls to generate eight uncorrelated waves is presented in this study. The MIMO array operates in a wide band of 5.9-8.4 GHz, which covers the possible new 6G mobile bands in 5.925-7.125 GHz and 7.125-8.4 GHz. The targeted new 6G mobile bands are in the upper mid-band’s lower frequency region, close to the 5G mid-band, and are expected to show similar rich multipath scattering as the 5G 4 x 4 MIMO operation. To verify it, we apply the proposed MIMO array to transmit eight MIMO streams for the 8 x 8 MIMO operation in a practical on-campus scenario and obtain a spectral efficiency of about 34 bps/Hz, which is about two times that of the 5G 4 x 4 MIMO operation. The results indicate that the proposed MIMO array is promising for applications in the 6G 8 x 8 MIMO system.

Performance Analysis of Massive MIMO Systems under Wireless Fading Channels

Abstract: This paper analyses the massive Multiple Input Multiple Output (MIMO) system channel capacity. The performance of massive MIMO is assessed by looking at the Symbol Error Rate (SER) in various fading channels. The purpose of this work is to investigate how the number of antennas and user equipment affects the capacity of massive MIMO system. This paper compares massive MIMO performance to the conventional MIMO systems. The fading channels considered in the study include Rayleigh, Rician, and Nakagami with using mathematical models and simulations. This work findings will provide important insights into the benefits of massive MIMO systems is improving in wireless communication systems.

Interference Leakage Minimization in RIS-Assisted MIMO Interference Channels

Abstract: We address the problem of interference leakage (IL) minimization in the K-user multiple-input multiple-output (MIMO) interference channel (IC) assisted by a reconfigurable intelligent surface (RIS). We describe an iterative algorithm based on block coordinate descent to minimize the IL cost function. A reformulation of the problem provides a geometric interpretation and shows interesting connections with envelope precoding and phase-only zero-forcing beamforming problems. As a result of this analysis, we derive a set of necessary (but not sufficient) conditions for a phase-optimized RIS to be able to perfectly cancel the interference on the K-user MIMO IC.

Capacity Analysis and Rate Maximization Design in RIS-Aided Uplink Multi-User MIMO

Abstract: Reconfigurable intelligent surface (RIS) has recently drawn intensive attention due to its potential of simultaneously realizing high spectral and energy efficiency in a sustainable way. This paper focuses on the design of efficient transmission methods to maximize the uplink sum throughput in a RIS-aided multi-user multi-input multi-output (MU-MIMO) system. To provide an insightful basis, the channel capacity of RIS-aided MU-MIMO is theoretically analyzed. Then, the conventional transmission schemes based on orthogonal multiple access are presented as the baseline. From the information-theoretic perspective, we propose two novel schemes, i.e., joint transmission based on the semidefinite relaxation of quadratic optimization problems and opportunistic transmission relying on the best user selection. The superiority of the proposed schemes over the conventional ones in terms of achievable rates is justified through simulation results.