Showing papers on "Multi-user MIMO published in 2022"

MIMO-LoRa for High-Data-Rate IoT: Concept and Precoding Design

Abstract: Long range (LoRa) is a widely adopted modulation scheme for Internet of Things (IoT), but its data rate is low. To tackle this problem, in this letter, we introduce a novel concept of MIMO-LoRa: an integration of multiple-input multiple-output (MIMO) and LoRa for achieving high data rates. We also design a precoding for the proposed MIMO-LoRa system to further enhance the link reliability. The validity and effectiveness of the proposed MIMO-LoRa system are demonstrated through numerical simulations.

Energy-Efficient Resource Allocation of Wireless Energy Transfer for the Internet of Everything in Digital Twins

Abstract: The work aims to improve the stability of wireless energy transfer (WET) in the Internet of Things (IoT), prolong the service life of wireless devices, and promote green communication. Based on a digital twins (DTs) IoT environment, we depict how to optimize the energy efficiency of large-scale multiple-input multiple-output (MIMO) systems under WET technology. The large-scale distributed antenna array is applied to the wireless sensor network. MIMO can produce extremely narrow beams so that the system reduces interference to other users. Our MIMO system's energy efficiency optimization uses fractional planning and the block coordinate descent algorithm. The simulation results show that the algorithm has the best throughput performance when the maximum transmission power reaches 19 dBm. The total energy consumption of the proposed resource allocation algorithm is only about 9 percent higher than that of the power minimization algorithm. In the case of different maximum transfer powers, the number of iterations in which the proposed algorithm is required to converge is within four. Changes in the number of users cannot affect the convergence performance of the proposed algorithm. After the antenna selection mechanism is introduced, the average power of the energy received by the user is improved notably compared to the case of simply using the largescale distributed antenna array. The research results can reference large-scale MIMO systems' energy efficiency optimization problems under WET conditions in the DTs IoT environment.

Uplink NOMA-MIMO Systems with Rayleigh Power Distribution

Abstract: The article is devoted to multiple-input multiple-output antenna systems, also called MIMO systems, which are widely used in wireless communication systems. In this article we consider a case when the MIMO system works in overloaded mode. In this mode MIMO systems can be considered as a system with non-orthogonal multiple access NOMA. The main goal of this article is to analyze this interesting case using statistical computer simulation. Based on the analysis of the capacity of a discrete-continuous multiuser MIMO uplink channel, the possibility of such systems functioning in overload mode is proved.

MIMO Antennas: Design Approaches, Techniques and Applications

Abstract: The excessive use of digital platforms with rapidly increasing users in the wireless domain enforces communication systems to provide information with high data rates, high reliability and strong transmission connection quality. Wireless systems with single antenna elements are not able to accomplish the desired needs. Therefore, multiple-input multiple-output (MIMO) antennas are getting more attention in modern high-speed communication systems and play an essential part in the current generation of wireless technology. However, along with their ability to significantly increase channel capacity, it is a challenge to achieve an optimal isolation in a compact size for fifth-generation (5G) terminals. Portable devices, automobiles, handheld gadgets, smart phones, wireless sensors, radio frequency identification and other applications use MIMO antenna systems. In this review paper, the fundamentals of MIMO antennas, the performance parameters of MIMO antennas, and different design approaches and methodologies are discussed to realize the three most commonly used MIMO antennas, i.e., ultra-wideband (UWB), dual-band and circularly polarized antennas. The recent MIMO antenna design approaches with UWB, dual band and circularly polarized characteristics are compared in terms of their isolation techniques, gain, efficiency, envelope correlation coefficient (ECC) and channel capacity loss (CCL). This paper is very helpful to design suitable MIMO antennas applicable in UWB systems, satellite communication systems, GSM, Bluetooth, WiMAX, WLAN and many more. The issues with MIMO antenna systems in the indoor environment along with possible solutions to improve their performance are discussed. The paper also focuses on the applications of MIMO characteristics for future sixth-generation (6G) technology.

5G MIMO Antenna Designs for Base Station and User Equipment: Some recent developments and trends

Abstract: 5G multiple-input, multiple-output (MIMO) antenna systems will be an important pillar in realizing the new standard. The key advantages that MIMO provides are high data rate, low latency, and high reliable communication. The main objective of this article is to present a comprehensive review, recent trends and development of sub-6 GHz and millimeter wave (mm-wave) MIMO antenna designs for next-generation wireless communications. This work features MIMO antenna designs for both base station (BS) as well as handheld devices for 5G communications. A state-of-the-art literature review is presented to report the recent developments in sub-6 GHz 5G MIMO, integrated 4G, and mm-wave 5G MIMO, mm-wave 5G MIMO antennas, and mm-wave massive-MIMO (m-MIMO) BS antenna designs for the first time in a comprehensive manner. Moreover, the challenges associated with 5G communication are also discussed.

A Deep Learning-Based Intelligent Receiver for Improving the Reliability of the MIMO Wireless Communication System

Abstract: Multiple-input–multiple-output (MIMO) technology is one of the most widely used communication technologies. However, with the increasing number of antennas, the complexity of the MIMO wireless communication receiver becomes higher and higher. On the other hand, the complex communication channels also raise up a great challenge to the reliability of the communication receiver system. With the rapid development and wide application of deep learning, it has been applied in the field of communication to solve some problems that are difficult to solve by the traditional methods, and thereby, improves the reliability of communication systems. Inspired by this idea, this article reviewed the signal processing process of the MIMO receiver system from the perspective of system reliability. Based on deep learning, the signal processing modules of the receiver system are jointly optimized, which changes the information recovery process of the traditional receiver and proposes the intelligent receiver for MIMO communication. In order to verify the system reliability of the intelligent receiver, this article analyzes it from the aspects of antenna numbers and channel conditions. The influence of different implementation methods of the intelligent receiver on the system reliability is also analyzed. Simulation results show that the proposed intelligent receiver for the MIMO wireless communication can recover information with a lower bit error rate and higher reliability compared with the traditional receiver under different conditions and antenna configurations.

5G and Beyond Networks for 3D MIMO Using Artificial Intelligence in 5G Network

Abstract: Today’s wireless systems would be incomplete without MIMO systems, which have become increasingly common in recent years due to their ability to increase both spectrum efficiency and energy efficiency at a significant rate. Prior MIMO, the most often utilised system was a single-input, single-output system, which had limited capability and could not reliably support a huge number of users. Throughout this study, an artificial intelligence machine training MIMO channel is developed to handle the huge customer demand.. However, the ever-increasing needs are not met by this new technology. AI techniques becoming more prominent in determining the angle of elevation and angle of arrival for 3D MIMO in 5G system. These days, more and more people are using wireless devices, and these devices generate an enormous volume of information that must be processed quickly and reliably. AI based machine learning solve the issue and provide more throughput and energy efficient 5G system.

Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment

Abstract: Massive MIMO and mmWave communication are the technologies for achieving 5G design goals. Fortunately, these two technologies share a symbiotic integration. As a result, amalgamating mmWave communications with massive MIMO forms,mmWave-massive MIMO,” which significantly improves spectral and energy efficiency. It also achieves high multiplexing gains and increases mobile network capacity. However, massive MIMO, mmWave communications, and mmWave-massive MIMO systems have been studied independently. Consequently, this article explores the ideas, performances, comparisons, and discussions of these three 5G technologies jointly, considering their precoding and beamforming methods. On the other hand, the complexity of these technologies increases when a large number of antennas and radio frequencies (RFs) are used. Thus, several investigations are going on to search for the appropriate precoding and beamforming strategies with low cost, power, and complexity. Therefore, massive MIMO linear precoding techniques such as zero-forcing, maximum ratio transmission, regularized zero-forcing, truncated polynomial expansion and phased zero forcing are addressed in this work. In addition, the most common non-linear precoding schemes: dirty-paper coding, Tomlinson-Harashima, and vector perturbation, are presented. Furthermore, a detailed discussion of the beamforming techniques called analog, digital, and hybrid analog-digital beamforming schemes is included. We also examine the potential of hybrid analog-digital beamforming with its fully-connected and sub-connected architecture approaches in making mmWave massive MIMO a reality. We evaluate their performance with the parameters: bit error rate, signal to noise ratio, complexity, spectral efficiency, and energy efficiency. According to the analytical and simulation results, the partially-connected hybrid analog/digital beamforming architecture offers better all-over performance for mmWave-Massive MIMO communications by compromising: power consumption, cost, complexity, and performance. Finally, the potential future directions in mmWave-massive MIMO precoding and beamforming challenges are addressed.

Benchmarking and Interpreting End-to-End Learning of MIMO and Multi-User Communication

Abstract: End-to-end autoencoder (AE) learning has the potential of exceeding the performance of human-engineered transceivers and encoding schemes, without a priori knowledge of communication-theoretic principles. In this work, we aim to understand to what extent and for which scenarios this claim holds true when comparing with fair benchmarks. Our particular focus is on memoryless multiple-input multiple-output (MIMO) and multi-user (MU) systems. Four case studies are considered: two point-to-point (closed-loop and open-loop MIMO) and two MU scenarios (MIMO broadcast and interference channels). For the point-to-point scenarios, we explain some of the performance gains observed in prior work through the selection of improved baseline schemes that include geometric shaping as well as bit and power allocation. For the MIMO broadcast channel, we demonstrate the feasibility of a novel AE method with centralized learning and decentralized execution. Interestingly, the learned scheme performs close to nonlinear vector-perturbation precoding and significantly outperforms conventional zero-forcing. Lastly, we highlight potential pitfalls when interpreting learned communication schemes. In particular, we show that the AE for the considered interference channel learns to avoid interference, albeit in a rotated reference frame. After de-rotating the learned signal constellation of each user, the resulting scheme corresponds to conventional time sharing with geometric shaping.

Centralized and Distributed Millimeter Wave Massive MIMO-Based Data Fusion With Perfect and Bayesian Learning (BL)-Based Imperfect CSI

Abstract: This paper presents low-complexity decision rules as well as the pertinent analysis for data fusion in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) wireless sensor networks (WSNs). The proposed framework considers both unknown and known parameter scenarios, and the spatial correlation arising due to close proximity of the sensors for both the centralized MIMO (C-MIMO) and distributed MIMO (D-MIMO) antenna configurations. The resulting detection performance is characterized by determining the closed-form expressions of probabilities of detection and false alarm for both antenna configurations. The optimal sensor gains are also determined for both the D-MIMO and C-MIMO architectures to further improve the detection performance. Additionally, asymptotic analysis is presented for both antenna configurations to determine the power scaling laws for the mmWave massive MIMO WSN, which lead to an improved sensor battery life without sacrificing the system performance. Furthermore, decision rules are also derived along with the pertinent analysis for a practical scenario with uncertainty in the channel state information (CSI) at the fusion center, wherein CSI of the mmWave massive MIMO channel is estimated using the novel sparse Bayesian learning (SBL) framework. Simulation results are presented to illustrate the performance of the proposed schemes and to validate the analytical results.

Fronthaul Optical Links Using Sub-Nyquist Sampling Rate ADC for B5G/6G Sub-THz Ma-MIMO Beamforming

Abstract: This paper details fronthaul optical links using sub-Nyquist sampling rate analog-to-digital converters (ADCs) for Beyond fifth generation (B5G) and 6G sub-THz massive multiple-input multiple-output (Ma-MIMO) beamforming. Unlike Common Public Radio Interface (CPRI) using high speed ADCs in current fronthaul link, the proposed scheme involves ADCs operating at sub-Nyquist sampling rate for each antenna element. Based on pre-allocated relative time delays, pre-processed orthogonal frequency-division multiplexing (OFDM) signals sent from a baseband unit (BBU) can be deaggregated to different Ma-MIMO OFDM signals by sub-Nyquist sampling rate ADCs. In experiments, we assume that each remote radio unit (RRU) is equipped with 32/64 antenna elements and 32/64 ADCs operating at 1/32 and 1/64 of the Nyquist sampling rate. Furthermore, the received Ma-MIMO OFDM signal is then up-converted to 100-GHz for wireless transmission and defined as Ma-MIMO RF OFDM signal. We simulate the 32/64 antenna elements transmission scenario by individually transmit and demodulate each Ma-MIMO RF OFDM signal with 32/64 times of point-to-point antenna transmission. The error vector magnitude (EVM) and signal-to-noise ratio (SNR) of each received Ma-MIMO RF OFDM signal are less than 8% and 26 dB, respectively. And the total received 64 Ma-MIMO RF OFDM signals will require line rate as high as 393.6374 Gb/s according to CPRI option-7. Notably, the proposed scheme reduces the requirement of sampling rate and enables all the Ma-MIMO OFDM signals at baseband without the insertion of guard band. Thus, the proposed scheme can reduce the complexity of signal deaggregation and power consumption in the demodulation process, leading to an improvement in cost efficiency.

Performance Measures of Spatially Multiplexed MIMO-OFDM System using Different Modulation Techniques

Abstract: Multiple input multiple output (MIMO) systems employ more than one antenna at each of the two ends of the communication link and may transport at least two data streams over a single channel without requiring additional transmission capacity or power. In order to construct a stable communication stream, the receiving side should often have more antennas than the broadcasting side. Because of their better presentation abilities, MIMO frameworks have quickly gained popularity over the last decade. However, multi-stream interference and inter-symbol interference are encountered in spatially multiplexed MIMO systems as a result of the remote channel’s time-dispersive characteristics. To provide dependable and reliable communication, the influence of interference must be appropriately limited at the recipient. In order to counteract interference in spatially multiplexed wireless channels, orthogonal frequency division multiplexing (OFDM) is usually used. The study found that combining MIMO and OFDM delivers higher productivity, unwavering quality, gain, and information rate, and that it is an appealing air-interface suggestion for next-generation WLAN and WMANs. As a result, a spatially multiplexed MIMO-OFDM system was developed in this study, and performance measures such as bit error rate and bit energy to noise ratio were investigated using various modulation methods. At the receiver, the proposed method uses a zero forcing equalizer to spatially de-multiplex the data.

Scalable and Reconfigurable Distributed MU-MIMO System

Abstract: In this paper, we propose a concept of a scalable and reconfigurable distributed multiuser MIMO (MU-MIMO) system and an interference coordination for ultra-dense radio access network (RAN). With careful consideration of the feasible radio signal processing capability for MU-MIMO, the communication service area is divided into a number of disjointed small areas (cells), each being formed based on the distributed antenna location information, and then, users in each cell are grouped into multiple user-clusters based on the user location information. In order to improve the spectrum efficiency, small-scale cluster-wise distributed MU-MIMO signal transmission is performed in parallel by reusing the same frequency in all user-clusters in all cells. However, in return, the strong interference is produced and this limits the improvement of system capacity. Hence, the introduction of interference coordination is essential. We evaluate the user capacity by computer simulation to show the effectiveness of the proposed scalable and reconfigurable distributed MU-MIMO system and interference coordination.

User-Centric Cell-Free and Co-Located Cellular Large Scale MU-MIMO Systems: A Comparative Performance Study With Spatial Channel Correlation in Dense Urban Scenario

Abstract: Large Scale Multi-user MIMO (LS-MU-MIMO) is a promising technology for the fifth-generation (5G) and beyond wireless systems. It offers several magnitudes of improvement in data rates and spectral efficiency (SE) due to its ability to suppress the interference and to have the properties of channel hardening and favourable propagation. In its conventional cellular paradigm, a large number of co-located antennas are deployed at the Base Station (BS) to serve a smaller number of user terminals (UTs). In order to deal with the inter-cell interferences more efficiently to achieve higher SE, a Cell-Free paradigm was proposed. Previous studies, which compare the two network deployments, relied on idealized assumptions, such as perfect channel state information, uncorrelated channels, and single-cell processing analysis-based, to name a few. This paper intends to bring further understanding of these two paradigms by examining the potential benefits of each paradigm in more realistic scenarios. Specifically, the influence of channel correlation on the achieved performance and network density in dense urban scenarios is investigated. Here, the performance of a Cell-Free network versus a traditional Co-located Cellular network structure has been compared in a more realistic setting. The comparison is carried out in different settings, taking into consideration the dense urban scenario, which supports low-to-moderate mobility and channel dispersion. First, we study the system performance gain in terms of Per-Terminal SE for different ratios of Antenna-UT and pilot scalers. Next, the Area-SE, defined as the sum SE of all UTs per unit area, is considered for different values of network density. Then, the channel estimation accuracy for both network deployments is compared, and its impact on the system performance as the Antenna-UT ratio increases is presented. Further, the impact of the spatially correlated channels is investigated in both network configurations. Finally, fronthaul requirements and distributed implementation in Cell-Free system deployment are discussed. Numerical simulations have been performed to investigate the performance gap between the two network deployments. Considering a cell-free system with scalable linear detectors and a large number of APs, the results show that the impact of noise and small-scale fading vanishes; moreover, a reduction in the non-coherent interference is observed in the same way as in the Co-Cellular LS-MU-MIMO systems. The findings indicate that employing linear detectors results in non-increasing Per-Terminal SE as the network density increases. It is also found that Area-SE grows exponentially with the network density in both system deployments. Moreover, the increase in the Antenna-UT ratio improves the Per-Terminal SE and channel estimation accuracy. However, increasing the pilot scalers affects the systems’ behavior in both deployments differently. Furthermore, local detection schemes are investigated, demonstrating the advantages of distributed implementation in the Cell-Free system in terms of reducing fronthaul signaling.

Multi-User Massive MIMO Visible Light Communications With Limited Pilot Transmission

Abstract: Visible light communication (VLC) building on the existing illumination infrastructure utilizes light emitting diode (LED) luminaries as wireless transmitters. To achieve data rates on the order of gigabits per second in VLC systems, multiple-input multiple-output (MIMO) transmission has been identified as a key technology. In this paper, we consider a centralized network architecture where the ceiling LED luminaries act as transmitter elements of a distributed massive MIMO VLC system. To obtain the full benefits of massive MIMO, channel state information must be available at the transmitter side. Downlink (DL) channel estimation in a massive MIMO system requires huge pilot overhead in DL as well as feedback overhead in uplink. This makes the implementation of massive MIMO system infeasible if not properly designed. In our study, we address the design of massive MIMO VLC systems with a limited number of DL pilot signals. We explore different DL pilot patterns (PPs) in frequency, time, and spatial domains where interpolation is performed to obtain the global channel matrix taking advantage of the indoor environment geometry and layout of luminaries. We then present data rate results for different DL PPs under the consideration of varying number of active user equipments through Monte-Carlo simulations.

A review on Precoding Techniques For mm-Wave Massive MIMO Wireless Systems

Abstract: The growing demands for high data rate wireless connectivity shed lights on the fact that appropriate spectrum regions need to be investigated so that the expected future needs will be satisfied. With this in mind, the research community has shown considerable interest in millimeter-wave (mm-wave) communication. Generally, hybrid transceivers combining the analog phase shifter and the RF chains with digital signal processing (DSP) systems are used for MIMO communication in the fifth generation (5G) wireless networks. This paper presents a survey for different precoding or beamforming techniques that have been proposed in the literature. These beamforming techniques are mainly classified based on their hardware structure into analog and digital beamforming. To reduce the hardware complexity and power consumption, the hybrid precoding techniques that combine analog and digital beamforming can be implemented for mm-wave massive MIMO wireless systems. The performance of the most common hybrid precoding algorithms has been investigated in this paper.

3×3 MIMO 60-GHz OFDM-RoF System With Long-Distance Wireless Transmission Enabled by MIMO Volterra Filtering

Abstract: A 3×3 60-GHz multiple-input multiple-output (MIMO) radio-over-fiber system with an MIMO Volterra filter was demonstrated. The main objective of the proposed scheme is to compensate for the nonlinear distortion caused by radio frequency (RF) power amplifiers (PAs) before the signals reaches the transmitter antennas—particularly when the PAs operate with a high input power to achieve a high output RF power for long-distance wireless transmission. When the required wireless transmission distance is only 7 m, the 3×3 MIMO system with careful control of the PA input power can achieve a data rate of 126 Gbps. However, the data rate decreases rapidly over a longer wireless distance because of the larger loss. By eliminating nonlinear distortion and interchannel interference simultaneously, MIMO Volterra filtering can significantly increase the achievable data rate of a long-distance system. When the required data rate is 90 Gbps (or 100 Gbps), the maximum wireless transmission distance is 118 m (or 70 m) with the aid of MIMO Volterra filtering, but it is only 74 m (or 40 m) without MIMO Volterra filtering.

Graph Neural Network Aided Expectation Propagation Detector for MU-MIMO Systems

Abstract: Multiuser massive multiple-input multiple-output (MU-MIMO) systems can be used to meet high throughput requirements of 5G and beyond networks. In an uplink MU-MIMO system, a base station is serving a large number of users, leading to a strong multi-user interference (MUI). Designing a high performance detector in the presence of a strong MUI is a challenging problem. This work proposes a novel detector based on the concepts of expectation propagation (EP) and graph neural network, referred to as the GEPNet detector, addressing the limitation of the independent Gaussian approximation in EP. The simulation results show that the proposed GEPNet detector significantly outperforms the state-of-the-art MU-MIMO detectors in strong MUI scenarios with equal number of transmit and receive antennas.

Clustered Double-Scattering Channel Modeling for XL-MIMO With Uniform Arrays

Abstract: Extra-large multiple-input multiple-output (XL-MIMO) systems reveal themselves as a potential candidate for the sixth generation (6G) of wireless communication systems due to their features. As XL-MIMO has a large antenna array, and, typically, the urban environment is plenty of obstacles and reflectors, the spatial non-stationarities are introduced in the signal received at the base station (BS), which means that only a portion of the antenna array is visible to users; hence, accurately modeling XL-MIMO channels is paramount. Previous works on XL-MIMO channel modeling have adopted the non-stationarities only in a spatial sense, and do not consider spatial-time evolution scenarios. Moreover, simplified models with only one set of clusters between the BS and the user equipment (UE) are usually adopted; hence, there is a lack of understanding regarding such channels modeling in the literature. This work proposes and extensively analyzes a double-scattering XL-MIMO channel model, by admitting two types of scattering clusters, one placed at the BS side, and another one located near the UEs. In addition, two distinct antenna array configurations are included in the analysis, the uniform linear and planar arrays (ULA and UPA). We propose a new double-scattering channel model under UPA arrangements, suitable for modeling spatial non-stationarities scenarios in XL-MIMO dynamic environment subject to BS-cluster and UE-cluster correlation, and birth-death channel clusters and scatterers. Numerical results for signal-to-interference-plus-noise ratio (SINR), condition number (CN), and spectral efficiency (SE) performance metrics considering different XL-MIMO channels and system configurations are analyzed via Monte-Carlo simulations, under linear combiners MRC, ZF, and MMSE. Also, we characterize the impact of the number of visible clusters per user, the birth-death rate growth effect on the channel clusters and scatterers, and the favorable propagation effect according to the size of visibility region (VR) overlap. It can be observed that the birth and death processes have a significant impact on the system performance. Under the proposed clustered double-scattering channel modeling, the analyzed XL-MIMO linear receivers presented an SINR degradation around 3 to 4 dB for the MMSE when the number of UEs substantially increased, while the ZF and MRC receivers present a decrease of 1 to 2 dB, approximately, in SINR for the considered dynamic configuration compared with static scenarios.

Performance Evaluation of MIMO System in Different PDSCH Modulation Type for Wireless Communication Using 20MHz Channel Bandwidth

Abstract: In the innovation of wireless communications has probably gotten the best commitment to humanity. Wireless communications make it simple to send data from a disseverment without links or wires. The modern wireless communication (4G/5G) framework required lower power consumption, high speed data transfer rate, and bandwidth efficiency. The MIMO framework is recognized as a rival to satisfy such challenges. At the transmitter and receiver terminal, a MIMO framework uses multiple antennas to improve wireless communication system performance. This paper present a comparative analysis of bit error rate in different PDSCH modulation type (16-QAM, 64- QAM, and QPSK) in different fading channel models (EPA 0HZ, EPA 5Hz, EVA 5Hz, EVA 70Hz, Flat Static MIMO) for MIMO wireless communication. This work evaluates the performance of the $2\times 2$ and $4\times 4$ MIMO systems in different PDSCH modulation types for wireless communication using 20MHz channel bandwidth to find out which type of modulation scheme works better.

MIMO-OFDM Implementation Using VLSI

Abstract: The modulation technique which divides the available spectrum into sub-carriers is called OFDM. OFDM when compared with FDMA (Frequency-Division Multiple Access), OFDM uses the spectrum effectively by channel spacing, in this channel signals are spaced closely together and makes the carriers perpendicular to each other, it prevents the interference between a close-spaced carrier channel. OFDM is specifically used for its robustness in channel fading in the wireless communication. In order to make the system flexible, reconfigurable architecture is used as a pre-requisite. The most efficient reconfigurable and reusable architecture is FPGA. OFDM technique is used, for achieving maximum data rate, with help of MIMO systems. Interference between user to user can be observed by every user in MIMO, due to transmission of data over a common channel. To reduce the inter-user-interference, zero-force precoding technique is used at the transmitter. Here, the information is coded and is transmitted over the channels (MIMO), then the information which is received at the receiver has comparatively low Bit Error Rate (BER). The main aim of this project is, to design and implement a base band (BB)OFDM transmitter and receiver on a FPGA hardware. It involves QPSK mapping module, scrambler, encoder, inter-leaver and cyclic prefix insertion modules. This design uses a 64-point FFT or IFFT as one of its main modules. In addition to OFDM, we are using a zero-force-pre-coding technique in this system which will be simulated using Xilinx 14.5 software and verified by using MATLAB 7.1.

Error Performance of MIMO-OFDM Communication System

Abstract: This research discusses the significance of using a MIMO-OFDM system as well as its limits in terms of error performance. MIMO-OFDM systems are compared to conventional OFDM and MIMO systems using a methodology developed for assessing them. The suggested system is tested using a distinct MIMO-OFDM system, each having two broadcast antennas and two receive antennas. QPSK modulation with multiple antennas at both ends of the communication system may be used with OFDM to increase spectrum efficiency and reliability. WLAN, WMAN, and 4G cellular network technologies all use a well-known mix of MIMO and OFDM. It's also seen to be a good match for developing and building emerging wireless networks with larger data speeds. The principles of OFDM and MIMO wireless technologies, as well as a MIMO-OFDM hybrid, are also covered in this research.

Comparison of Co-located and Distributed MIMO for Indoor Wireless Communication

Abstract: This paper compares the communication performance for co-located and emerging distributed MIMO in a typical indoor scenario. The simulations, which are verified against experimental measurement data, show that distributed MIMO offers a significantly more uniform capacity for the users. The results also show that the same user capacity can be achieved with half the number of antennas in the distributed MIMO case.

Hybrid Beamforming for Multi-User Massive MIMO Systems at Millimeter-Wave Networks

Abstract: The design procedure of hybrid beamforming is investigated considering multi-user MIMO communication systems taking into account the number of independent data streams for each user. Hybrid precoding and combining are utilized at the transmitter and receiver sides of millimeter-wave multi-user massive MIMO. The obtained results indicate the trade-off in performance based on the ratio of the number of antennas to the number of data streams at the transmitter as well as the receiver. The optimization of the number of parallel data streams per user allows the increase of transmitted data rate while keeping the levels of error vector magnitude (EVM) at acceptable levels.

Enhancement in the Network Capacity using MIMO and Antenna Array in 5G Technology

Abstract: The main motive of wireless communication system is to provide better facility and fairness among the users. The main objective is to serve as many users as possible with best data rates and flexibility. All this should happen under the restrictions of radiation spread limit and limited cost. So, when it comes to increase the data rate then the main thing to consider is SNR that is Signal to noise ratio. The resources are limited so the focus should be on the reuse of the resources in order to increase the number of users and hence capacity. This paper is going to cover step by step compression sof SISO, SIMO, MISO and MIMO. The graph is plotted between BER and SNR in most cases. At the end while using MIMO it can be seen that capacity has been improved. In the created scenario we’ll see how SNR and capacity can be improved by using antenna arrays over the wireless channel

Error Control on Mobile Station Sides in Collaborative Multiple-Input Multiple-Output Systems

Abstract: Collaboration between mobile stations (MSs) may lead to a new form of wireless communication. Collaboration on MS sides considerably improves signal detection performance, especially for multiple-input multiple-output (MIMO) transmission systems. In this study, a novel detector collaboration system is proposed to reduce the traffic volume on inter-MS collaboration links. Multiple MSs in the immediate vicinity are used to collaboratively decode the MIMO signals received from a base station. Furthermore, we consider a distributed detection system, in which multiple detection MSs decode the MIMO signals independently. Multiple decision results are exploited to improve the error performance. Residual interference coefficients were used to finalize the decision results. The error ratio performance and the traffic volume over collaboration wireless links were compared with those of two combining schemes through computer simulations and field experiments. The results revealed that the proposed error control scheme on mobile station sides offers a better tradeoff between the error performance and the traffic volume on the collaboration wireless links.

Extreme Massive MIMO for Upper-Mid Band 6G Communications

Abstract: It is necessary to study the frequency characteristics in the upper-mid band, one of the new frequency candidates of 6G, and the extreme massive MIMO scheme using it. Research on a fully digital massive MIMO precoding method has drawn much attention to achieve near optimal performance with low complexity by exploiting the channel characteristics. In 6G, It is desired to utilize appropriate MIMO schemes suitable for upper-mid bands to provide not only peak data rate up to 1 Tbps but also user experienced rate up to 1 Gbps anywhere anytime, However the channel characteristics in the upper-mid band at the mobile communication environment are not yet known. In this paper, an exemplary multi-user MIMO channel is tested in the upper-mid band by utilizing ray-tracing, investigate the channel characteristics, and to show possible the corresponding MU-MIMO schemes.

The road to 6G: a comprehensive survey of deep learning applications in cell-free massive MIMO communications systems

Abstract: Abstract The fifth generation (5G) of telecommunications networks is currently commercially deployed. One of their core enabling technologies is cellular Massive Multiple-Input-Multiple-Output (M-MIMO) systems. However, future wireless networks are expected to serve a very large number of devices and the current MIMO networks are not scalable, highlighting the need for novel solutions. At this moment, Cell-free Massive MIMO (CF M-MIMO) technology seems to be the most promising idea in this direction. Despite their appealing characteristics, CF M-MIMO systems face their own challenges, such as power allocation and channel estimation. Deep Learning (DL) has been successfully employed to a wide range of problems in many different research areas, including wireless communications. In this paper, a review of the state-of-the-art DL methods applied to CF M-MIMO communications systems is provided. In addition, the basic characteristics of Cell-free networks are introduced, along with the presentation of the most commonly used DL models. Finally, future research directions are highlighted.

Energy-Efficient Cooperative MIMO Formation for Underwater MI-Assisted Acoustic Wireless Sensor Networks

Abstract: The energy problem has become one of the critical factors limiting the development of underwater wireless sensor networks (UWSNs), and cooperative multiple-input–multiple-output (MIMO) technology has shown advantages in energy saving. However, the design of energy-efficient cooperative MIMO techniques does not consider the actual underwater environment, such as the distribution of nodes. Underwater magnetic induction (MI)-assisted acoustic cooperative MIMO WSNs as a promising scheme in throughput, signal-to-noise ratio (SNR), and connectivity have been demonstrated. In this paper, the potential of the networks to reduce energy consumption is further explored through the joint use of cooperative MIMO and data aggregation, and a cooperative MIMO formation scheme is presented to make the network more energy efficient. For this purpose, we first derive a mathematical model to analyze the energy consumption during data transmission, considering the correlation between data generated by nodes. Based on this model, we proposed a cooperative MIMO size optimization algorithm, which considers the expected transmission distance and transmission power constraints. Moreover, a competitive cooperative MIMO formation algorithm that jointly designs master node (MN) selection and cooperative MIMO size can improve energy efficiency and guarantee the connectivity of underwater nodes and surface base station (BS). Our simulation results confirm that the proposed scheme achieves significant energy savings and prolongs the network lifetime considerably.