Multiuser Multiple-input Multiple-output Research Articles

Hybrid Beamforming in 5G mmWave Networks: A Full-Stack Perspective

This paper studies the cross-layer challenges and performance of Hybrid Beamforming (HBF) and Multi-User Multiple-Input Multiple-Output (MU-MIMO) in 5G millimeter wave (mmWave) cellular networks with full-stack TCP/IP traffic and MAC scheduling. While previous research on HBF and MU-MIMO has focused on link-level analysis of full-buffer transmissions, this work reveals the interplay between HBF techniques and the higher layers of the protocol stack. To this aim, prior work on the full-stack evaluation of mmWave cellular networks has been extended by including the modeling of MU-MIMO and HBF. Our results reveal novel relations between the networking layers and the HBF MU-MIMO performance at the physical layer. Particularly, throughput can be increased in 5G networks by means of Space Division Multiple Access (SDMA). However, in order to achieve such benefits it is necessary to take into account certain trade-offs and the implementation complexity of a full-stack HBF solution.

Double Intelligent Reflecting Surface-Assisted Multi-User MIMO Mmwave Systems With Hybrid Precoding

This work investigates the effect of double intelligent reflecting surface (IRS) in improving the spectrum efficient of multi-user multiple-input multiple-output (MIMO) network operating in the millimeter wave (mmWave) band. Specifically, we aim to solve a weighted sum rate maximization problem by jointly optimizing the digital precoding at the transmitter and the analog phase shifters at the IRS, subject to the minimum achievable rate constraint. To facilitate the design of an efficient solution, we first reformulate the original problem into a tractable one by exploiting the majorization-minimization (MM) method. Then, a block coordinate descent (BCD) method is proposed to obtain a suboptimal solution, where the precoding matrices and the phase shifters are alternately optimized. Specifically, the digital precoding matrix design problem is solved by the quadratically constrained quadratic programming (QCQP), while the analog phase shift optimization is solved by the Riemannian manifold optimization (RMO). The convergence and computational complexity are analyzed. Finally, simulation results are provided to verify the performance of the proposed design, as well as the effectiveness of double-IRS in improving the spectral efficiency.

An Experimental Proof of Concept for Integrated Sensing and Communications Waveform Design

The integration of sensing and communication (ISAC) functionalities have recently gained significant research interest as a hardware-, power-, spectrum-and cost-efficient solution. This experimental work implements a dual-functional sensing and communication framework where a single radiation waveform, either omnidirectional or directional, can realize both sensing and communication functions. We design an orthogonal frequency division multiplexing (OFDM) based multi-user multiple input multiple output (MIMO) software-defined radio (SDR) testbed to validate the dual-functional model. We carry out over-the-air experiments to investigate the optimal trade-off factor to balance the performance for both functions. On the communication side, we obtain bit error rate (BER) results from the testbed to show the communication performance using the dual-functional waveform. On the sensing performance, we measure the output beampatterns of our transmission to examine their similarity to simulation based beampatterns. We also implement a sensing experiment to realize activity detection functions. Our experiment reveals that the dual-functional approach can achieve comparable BER performance with pure communication-based solutions while achieving fine sensing beampatterns and realistic sensing functionality simultaneously.

Performance Analysis and Throughput Enhancement of the STET Technique for WLAN IEEE 802.11ad

The IEEE 802.11ad innovation has enabled the impact of remote devices in unauthorized 60 GHz unlicensed frequency band at Giga bits per second information transfer rate in speed concentrated 5G applications. We have presented an innovative work that deals with the upgradation of the ability of IEEE 802.11ad wireless LAN to make it suitable for wireless applications. An exact examination on the IEEE 802.11ad analysis has been carried out in this work to achieve the greatest throughput. This has pulled attraction in broad consideration for accomplishing the pinnacle transmission rate of 8 Gbit/s. IEEE 802.11ad is a convention utilized for extremely high information rates (around 8 Gbit/s) and for short range remote correspondence of around 1 to 10 meters. The Multi-layer with Multi-User Multiple Input Multiple-Output (MLMU-MIMO) innovation has enabled transmission of multiple information packets all the while from the WLAN IEEE 802.11 ad Access Point (AP) to various receivers by means of different wireless applications. To help the MLMU-MIMO innovation at Medium Access Control (MAC), a new method called Simultaneous Transmission for Enhanced Throughput (STET) has been presented for enhancement of the transmission rate of the wireless standard. A mathematical model has been used for the evaluation of the performance of an IEEE 802.11ad AP empowering the STET allocation technique. This STET model can help determination of the throughput improvement of a STET technique, for example, audio information, images, good quality and foundation impact. The main goal of this work is to analyze the improvement of the STET allocation technique in regard to the usage of rare frequency band, when obtaining spectrum access between the various access points. The theoretical and simulation outcomes are also confirmed by Riverbed modeler 17.5 simulation tool.

LIDAR-Assisted Channel Modelling for LiFi in Realistic Indoor Scenarios

We present a new, accurate, low complexity channel modelling methodology for LiFi in realistic indoor scenarios. A LIDAR scanner is used to capture the 3D environment in which the LiFi system is to be deployed. Next, the generated 3D point cloud data is pre-processed to determine the reflectance parameters of the walls and objects in the room. This is easier and more realistic than the manual definition of the environment, which is the current state of the art. As an additional innovation, the complexity of the channel modeling is reduced by i) modeling the line-of-sight and initial reflections precisely in the frequency-domain and ii) using a well-established analytical model based on the integrating sphere for all higher-order diffuse reflections. All steps together yield a substantially simplified channel modelling approach and model the links between multiple optical frontends and multiple mobile devices realistically. As a validation of our new approach, we compare measurements and simulations in two indoor scenarios: an empty room and a conference room with furniture. Simulations and measurements show excellent agreement with a mean square error below 3 percent. Moreover, we evaluate the performance of a distributed multiuser multiple-input multiple-output (MIMO) link and found excellent agreement between the model and measurements. Finally, we discuss the fundamental trade-off between complexity and model error, which depends on the scenario.

Hybrid Precoding and Combining Strategy for MMSE-Based Rate Balancing in mmWave Multiuser MIMO Systems

In this paper, a new hybrid precoding and combining method is proposed for the downlink of multiuser multiple-input multiple-output (MU-MIMO) millimeter wave (mmWave) channels. The proposed method designs the precoders and combiners for radio frequency (RF) and baseband processing, respectively, based on the minimum mean square error (MMSE) criterion and the rate fairness among users. To design the RF precoder and combiners implemented by phase shifters, a new matrix factorization algorithm is devised by combining the gradient method with the projection to the nearest unitary matrix. Under the total transmit power constraint, the proposed factorization method increases the achievable rate by making the columns of the RF precoder near-orthogonal and growing the Frobenius norm of the baseband precoder. In addition, a new MMSE-based rate balancing algorithm is proposed to design the baseband precoder and combiners in terms of maximizing the minimum user rate. The proposed rate balancing scheme iteratively updates the baseband precoder, the transmit power constraint for the baseband precoder, the baseband combiners, and the weighting vector for rate balancing. Through theoretical analysis, it is shown that the proposed design method has a polynomial complexity order. Numerical simulations present that the proposed matrix factorization method outperforms existing schemes requiring low computational complexity and the proposed rate balancing scheme converges to a stationary point satisfying the total transmit power constraint. Moreover, simulation results in MU-MIMO channels are provided to show that the proposed design scheme performs better than existing hybrid processing schemes while achieving the minimum user rate close to the upper bound of MMSE processing.

Statistical CSI-Based Transmission Design for Reconfigurable Intelligent Surface-Aided Massive MIMO Systems With Hardware Impairments

We consider a reconfigurable intelligent surface (RIS)-aided massive multi-user multiple-input multiple-output (MIMO) communication system with transceiver hardware impairments (HWIs) and RIS phase noise. Different from the existing contributions, the phase shifts of the RIS are designed based on the long-term angle information. Firstly, an approximate analytical expression of the uplink achievable rate is derived. Then, we use genetic algorithm (GA) to maximize the sum rate and the minimum date rate. Finally, we show that it is crucial to take HWIs into account when designing the phase shift of RIS.

Performance Evaluation of Uplink Multiuser MIMO-OFDM System With Single RF Chain Receiver

In response to the recent increase in wireless-traffic demand in various wireless communication networks, the number of spatial multiplexings, represented by multiple input multiple output (MIMO) systems, has been increasing. Assuming a realistic hardware configuration achieving an increase in the number of spatial multiplexings depends on increasing the amount of hardware, such as analog/digital (A/D) and D/A converters, and radio frequency (RF) chains. Simplifying the hardware configuration while maintaining large channel capacity was the challenging issue to further improve the channel capacity in Beyond-5G and 6G. This paper proposes a novel system configuration based on an uplink multiuser MIMO - orthogonal frequency division multiplexing (OFDM) system with a single RF chain receiver. By oversampling OFDM signals with a single RF chain receiver, our approach provides an additional spatial multiplexing by switching the antenna directivity pattern in synchronization with the received sampling frequency. Oversampled OFDM signals are typically used for noise reduction, in the proposed configuration, they are used for adding spatial multiplexings. We clarify the potential of the proposed configuration for improving the channel capacity by applying it to the uplink multiuser MIMO-OFDM system. To demonstrate its feasibility, we developed a testbed and analyzed its effectiveness in experiment in an actual indoor office environment.

A Reliable Singular Value Decomposition and Geometric Mean Decomposition Based Precoding Scheme for MU-MIMO-VLC System

In this paper, in order to improve the reliability of Multi-User Multiple-Input Multiple-Output Visible Light Communication (MU-MIMO-VLC) system, we propose a precoding scheme that based on Singular Value Decomposition (SVD) and Geometric Mean Decomposition (GMD) assisted Orthogonal Transformation (OT). In this design, we use SVD to conduct the decomposition of the user’s complementary channel matrix. Then, the equivalent channel matrix is obtained by multiplying the user’s channel matrix and the decomposed component. After that, the GMD is carried out to decompose the equivalent channel matrix. Finally, the precoding matrix of the proposed scheme is obtained. We then derive the theoretical Symbol Error Rate (SER) of the proposed scheme. The simulation results are provided to validate the effectiveness of the proposed scheme, and to demonstrate that the reliability of the proposed design is superior to benchmark schemes.

A Pricing-Based Approach for Energy-Efficiency Maximization in RIS-Aided Multi-User MIMO SWIPT-Enabled Wireless Networks

In this work, we investigate the performance of a reconfigurable intelligent surface (RIS)-aided multi-user simultaneous wireless information and power transfer (SWIPT) network, where a multiple-input multiple-output (MIMO) base station (BS) serves multiple MIMO information receivers (IRs) while ensuring a minimum harvested power at multiple MIMO energy receivers (ERs). In order to improve the energy efficiency (EE) of the network, we consider a pricing-based performance metric called network utility. We then establish an optimization framework to jointly optimize the transmit precoding matrix (TPM) and phase shift matrix (PSM) to maximize the network utility function with constraints on the available transmit power at BS, minimum harvested power required at each ER, and unit modulus phase shift condition at RIS. Due to the non-convex nature of this problem, we divide it into two sub-problems where a sub-optimal solution of TPM and PSM are obtained separately using successive convex approximation and bisection search-based algorithms. Further, we propose an EE maximization (EEM) algorithm based on the block coordinate descent method to achieve the optimal solution of the master problem by iteratively obtaining the sub-optimal TPM, PSM, and network price using their respective algorithms. Moreover, we also prove that the solution obtained for each problem using their respective algorithm converges to the Karush-Kuhn-Tucker (KKT) optimum point of that problem. We also show the efficacy of the proposed algorithm using simulation results. In particular, we highlight the importance of using RIS in a multi-user MIMO SWIPT network and demonstrate the effect of various parameters on the network’s EE performance.

Energy Efficiency Maximization for IRS-Assisted Uplink Systems: Joint Resource Allocation and Beamforming Design

This letter investigates the design of resource allocation to maximize the energy efficiency (EE) in a multiuser multiple-input multiple-output (MIMO) intelligent reflecting surface (IRS)-assisted uplink network. The design is formulated as a mixed-integer non-convex optimization problem which jointly optimizes the antenna selection (AS) and power allocation at user sides and the beamforming matrices adopted at the BS and IRS. To facilitate the design of a suboptimal solution, we first decompose the original problem into two sub-problems via the alternative optimization (AO) method. In particular, for the first sub-problem, we propose an iterative algorithm based on the majorization minimization (MM) approach to make the numerator of the fractional problem into a concave form and then we employed the Dinkelbach algorithm. For the second sub-problem, we adopt the inner approximation (IA) method to optimize the beamforming matrices at the BS and IRS. Simulation results demonstrate the superiority of the proposed method over benchmark schemes for the case of a single antenna case and also provide considerable performance gains due to the use of an antenna selection strategy.

Joint Spatial Division and Coaxial Multiplexing for Downlink Multi-User OAM Wireless Backhaul

Orbital angular momentum (OAM) at radio frequency (RF) provides a novel approach of multiplexing a set of orthogonal modes on the same frequency channel to achieve high spectral efficiencies (SEs). However, the existing research on OAM wireless communications is mainly focused on point-to-point transmission in the line-of-sight (LoS) scenario. In this paper, we propose an overall scheme of the downlink multi-user OAM (MU-OAM) wireless backhaul based on uniform circular arrays (UCAs) for broadcasting networks, which can achieve the joint spatial division and coaxial multiplexing (JSDCM). A salient feature of the proposed downlink MU-OAM wireless backhaul systems is that the channel matrices are completely characterized by the position of each small base station (SBS), independent of the numbers of subcarriers and antennas, which avoids estimating large channel matrices required by the traditional downlink multi-user multiple-input multiple-output (MU-MIMO) wireless backhaul systems. Thereafter, we propose an OAM-based multi-user distance and angle of arrival (AoA) estimation method, which is able to simultaneously estimate the positions of multiple SBSs with a flexible number of training symbols. With the estimated distances and AoAs, a MU-OAM preprocessing scheme is applied to eliminate the co-mode and inter-mode interferences in the downlink MU-OAM channel. At last, the proposed methods are extended to the downlink MU-OAM-MIMO wireless backhaul system equipped with uniform concentric circular arrays (UCCAs), for which much higher spectral efficiency (SE) and energy efficiency (EE) than traditional MU-MIMO systems can be achieved. Both mathematical analysis and simulation results validate that the proposed scheme can effectively eliminate both interferences of the practical downlink MU-OAM channel and approaches the performance of the ideal MU-OAM channel.

On the Sum-Rate of RIS-Assisted MIMO Multiple-Access Channels Over Spatially Correlated Rician Fading

Reconfigurable intelligent surface (RIS) stands out as a promising technology by enhancing the electromagnetic wave propagation environment with its passive reflecting elements. In this paper, we focus on the ergodic sum-rate analysis and maximization of the RIS-assisted uplink multiuser multiple-input multiple-output (MIMO) multiple-access channel (MAC) under Rician fading by exploiting full statistical channel state information (CSI). The spatial correlations at the base station, the users, and the RIS are also considered. By using the replica method originated in statistical physics, the closed-form asymptotic ergodic sum-rate of the system is first derived in the large-system regime on the account of the unique channel structure of the RIS-assisted MIMO-MAC system. Then, based on the derived asymptotic ergodic sum-rate, we propose an alternating optimization (AO) algorithm to jointly design the transmit covariance matrix of users and the phase-shifting matrix of RIS with full statistical CSI. Simulation results are also demonstrated to verify the accuracy of the derived asymptotic ergodic sum-rate and the superiority of the proposed AO algorithm. The results reveal that the derived closed-form asymptotic ergodic sum-rate matches very well with the Monte Carlo results even for a small number of antennas, and the proposed AO algorithm can achieve up to 10 bps/Hz gain at high signal-to-noise (SNR) regime, which is therefore valuable for future RIS-assisted MIMO-MAC system designs.

Gyre Precoding and T-Transformation-Based GFDM System for UAV-Aided mMTC Network

In this paper, an unmanned aerial vehicle (UAV)-aided multi-antenna configured downlink mmWave cooperative generalized frequency division multiplexing (GFDM) system is proposed. To provide physical layer security (PLS), a 3D controlled Lorenz mapping system is introduced. Furthermore, the combination of T-transformation spreading codes, walsh Hadamard transform, and discrete Fourier transform (DFT) techniques are integrated with a novel linear multi-user multiple-input multiple-output (MU-MIMO) gyre precoding (GP) for multi-user interference reduction. Furthermore, concatenated channel-coding with multi-user beamforming weighting-aided maximum-likelihood and zero forcing (ZF) signal detection schemes for an improved bit error rate (BER) are also used. The system is then simulated with a single base station (BS), eight massive machine-type communications (mMTC) users, and two UAV relay stations (RSs). Numerical results reveal the robustness of the proposed system in terms of PLS and an achievable ergodic rate with signal-to-interference-plus-noise ratio (SINR) under the implementation of T-transformation scheme. By incorporating the 3D mobility model, brownian perturbations of the UAVs are also analyzed. An out-of-band (OOB) reduction of 320 dB with an improved BER of 1×10−4 in 16-QAM for a signal-to-noise ratio, Eb/N0, of 20 dB is achieved.

Performance Evaluation of MU-MIMO Transmissions with Joint Interference Constraint in HetNet

In this paper, we investigate the per-tier outage probability of multiuser multiple-input multiple-output (MU-MIMO) transmissions in heterogeneous networks (HetNets) with joint interference constraint. In the tier of cellular cell, user equipment (UE) is required to report measured channel information and the base station (BS) adopts ZF-based precoding MU-MIMO transmission to achieve multiuser diversity gain. With the constraint of cross-tier interference and unpredicted inter-beam interference, we derive the closed-form expression of outage probability of downlink MU-MIMO transmissions. Considering the capacity of nodes in the tier of ad hoc networks, a max-SINR scheduler and codebook-based MU-MIMO transmission are employed. The scheduler selects the best receiving nodes for each beam in predefined codebook according to measured signal to interference plus noise ratio (SINR), and the transmitting node performs data transmissions using orthogonal beams. In the presence of inter-node interference, inter-beam interference, and cross-tier interference, we obtain the closed-form expression of outage probability of MU-MIMO transmissions when downlink or uplink transmissions occur in cellular cell. Additionally, in case that the outage probability in ad hoc networks should satisfy quality of service (QoS) requirement, a restricted area in cellular cell in which the outage probability in ad hoc networks is not greater than a required threshold is explored. Numerical results show that the unpredictable inter-beam interference in cellular cell degrades the outage probability slightly. The restricted area increases with the outage probability threshold.

Beamforming Using Exact Evaluation of Leakage and Ergodic Capacity of MU-MIMO System.

Closed-form evaluation of key performance indicators (KPIs) of telecommunication networks help perform mathematical analysis under several network configurations. This paper deals with a recent mathematical approach of indefinite quadratic forms to propose simple albeit exact closed-form expressions of the expectation of two significant logarithmic functions. These functions formulate KPIs which include the ergodic capacity and leakage rate of multi-user multiple-input multiple-output (MU-MIMO) systems in Rayleigh fading channels. Our closed-form expressions are generic in nature and they characterize several network configurations under statistical channel state information availability. As a demonstrative example of the proposed characterization, the derived expressions are used in the statistical transmit beamformer design in a broadcast MU-MIMO system to portray promising diversity gains using standalone or joint maximization techniques of the ergodic capacity and leakage rate. The results presented are validated by Monte Carlo simulations.

Rate-Splitting Multiple Access to Mitigate the Curse of Mobility in (Massive) MIMO Networks

Rate-Splitting Multiple Access (RSMA) is a robust multiple access scheme for downlink multi-antenna wireless networks. RSMA relies on multi-antenna Rate-Splitting (RS) at the transmitter and Successive Interference Cancellation (SIC) at the receivers. In this work, we study the performance of RSMA under the important setup of imperfect Channel State Information at the Transmitter (CSIT) originating from user mobility and latency/delay (between CSI acquisition and data transmission) in the network. We derive a lower bound on the ergodic sum-rate of RSMA for an arbitrary number of transmit antennas, number of users, user speed and transmit power. Then, we study the power allocation between common and private streams and obtain a closed-form solution for optimal power allocation that maximizes the obtained lower bound. The proposed power allocation greatly reduces precoder design complexity for RSMA. By Link-Level Simulations (LLS), we demonstrate that RSMA with the proposed power allocation is robust to the degrading effects of user mobility and has significantly higher performance compared to conventional multi-user (massive) Multiple-Input Multiple-Output (MIMO) strategies. The work has important practical significance as results demonstrate that, in contrast to conventional multi-user (massive) MIMO whose performance collapse under mobility, RSMA can maintain reliable multi-user connectivity in mobile deployments.

Intelligent Reflecting Surfaces: Sum-Rate Optimization Based on Statistical Position Information

In this paper, we consider a multi-user multiple-input multiple-output (MIMO) system aided by multiple intelligent reflecting surfaces (IRSs) that are deployed to increase the coverage and, possibly, the rank of the channel. We propose an optimization algorithm to configure the IRSs, which is aimed at maximizing the network sum-rate by exploiting only the statistical characterization of the locations of the mobile users. As a consequence, the proposed approach does not require the estimation of either instantaneous channel state information (CSI) or second-order channel statistics for IRS optimization, thus significantly relaxing (or even avoiding) the need of frequently reconfiguring the IRSs, which constitutes one of the most critical issues in IRS-assisted systems. Numerical results confirm the validity of the proposed approach. It is shown, in particular, that IRS-assisted wireless systems that are optimized based on statistical position information still provide large performance gains as compared to the baseline scenarios in which no IRSs are deployed.

Joint Active and Passive Beamforming Design for IRS-Assisted Multi-User MIMO Systems: A VAMP-Based Approach

This paper tackles the problem of joint active and passive beamforming optimization for an intelligent reflective surface (IRS)-assisted multi-user downlink multiple-input multiple-output (MIMO) communication system under both ideal and practical IRS phase shifts. We aim to maximize the spectral efficiency of the users by minimizing the sum mean square error (MSE) of the users’ received symbols. For this, a joint non-convex optimization problem is formulated under the sum minimum mean square error (MMSE) criterion. Alternating minimization is used to break the original joint optimization problem into the separate optimization of the active precoding matrix for the base station (BS) and the matrix of phase shifts for the IRS. While the MMSE active precoder is obtained in closed-form, the IRS phase shifts are optimized iteratively using a modified version (developed in this paper) of the vector approximate message passing (VAMP) algorithm. Moreover, the underlying joint optimization problem is solved under two different models for the IRS phase shifts, namely by assuming <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$i$ </tex-math></inline-formula> ) a unimodular (i.e., ideal) constraint on the reflection coefficients and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$ii$ </tex-math></inline-formula> ) a more practical reflection elements termination by a variable reactive load (which inherently introduces the phase-dependent amplitude attenuation in the IRS phase shifts). Simulation results are presented to illustrate the performance of the proposed method under both perfect and imperfect channel state information (CSI) and to show the effect of the practical constraint on the system throughput. The results validate the superiority of the proposed method over the state-of-the-art techniques both in terms of throughput and computational complexity.

Low Complexity Hybrid Precoding Designs for Multiuser mmWave/THz Ultra Massive MIMO Systems.

Millimeter-wave and terahertz technologies have been attracting attention from the wireless research community since they can offer large underutilized bandwidths which can enable the support of ultra-high-speed connections in future wireless communication systems. While the high signal attenuation occurring at these frequencies requires the adoption of very large (or the so-called ultra-massive) antenna arrays, in order to accomplish low complexity and low power consumption, hybrid analog/digital designs must be adopted. In this paper we present a hybrid design algorithm suitable for both mmWave and THz multiuser multiple-input multiple-output (MIMO) systems, which comprises separate computation steps for the digital precoder, analog precoder and multiuser interference mitigation. The design can also incorporate different analog architectures such as phase shifters, switches and inverters, antenna selection and so on. Furthermore, it is also applicable for different structures, namely fully-connected structures, arrays of subarrays (AoSA) and dynamic arrays of subarrays (DAoSA), making it suitable for the support of ultra-massive MIMO (UM-MIMO) in severely hardware constrained THz systems. We will show that, by using the proposed approach, it is possible to achieve good trade-offs between spectral efficiency and simplified implementation, even as the number of users and data streams increases.