Multiuser Multiple-input Multiple-output Channels Research Articles

Structured light based multiuser indoor communications: Exploiting quantum encoding over classical data channel

By leveraging the characteristics of both quantum encoding and classical data channel, we present a unique and novel multiuser optical communication system that utilizes fascinating properties of the structured light for information transmission. Specifically, we propose an indoor orbital angular momentum (OAM) multiuser multiple-input multiple-output (MIMO) optical communication system, where the quantum encoding is performed and the multiuser transmission is then analyzed from the context of the classical data channel. In the proposed system, as the OAM beam propagates, its angular spread is analyzed. In addition, we show that the variance of the beam divergence increases with the increasing OAM index mode on the basis of the derived MIMO channel impulse response for OAM carrying Laguerre–Gaussian beams. Comparative studies reveal that the proposed system significantly outperforms the conventional non-orthogonal multiple access (NOMA) applied with MIMO.

Downlink MIMO-RSMA With Successive Null-Space Precoding

In this paper, we consider the precoder design for an underloaded or critically loaded downlink multi-user multiple-input multiple-output (MIMO) communication system. We propose novel precoding and decoding schemes which enhance system performance based on rate splitting at the transmitter and single-stage successive interference cancellation at the receivers. The proposed successive null-space (SNS) precoding utilizes linear combinations of the null-space basis vectors of the successively augmented MIMO channel matrices of the users as precoding vectors to adjust the inter-user-interference experienced by the receivers. We formulate a non-convex weighted sum rate optimization problem for the precoding vectors and the associated power allocation for the proposed SNS-based MIMO-rate-splitting multiple access (RSMA) scheme. We obtain a suboptimal solution for this problem via successive convex approximation. Moreover, we study the robustness of the proposed precoding scheme to imperfect channel state information (CSI) at the base station via derivative-based sensitivity analysis. Our analysis and simulation results reveal the enhanced performance and robustness of the proposed SNS-based MIMO-RSMA scheme over several baseline multi-user MIMO schemes, especially for imperfect CSI.

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.

Passive Beamforming and Information Transfer Design for Reconfigurable Intelligent Surfaces Aided Multiuser MIMO Systems

This paper investigates the passive beamforming and information transfer (PBIT) technique for multiuser multiple-input multiple-output (Mu-MIMO) systems with the aid of reconfigurable intelligent surfaces (RISs), where the RISs enhance the primary communication via passive beamforming (P-BF) and at the same time deliver additional information by the on-off reflecting modulation (in which the RIS information is carried by the on/off state of each reflecting element). For the P-BF design, we propose to maximize the achievable user sum rate of the RIS-aided Mu-MIMO channel and formulate the problem as a two-step stochastic program. A sample average approximation (SAA) based iterative algorithm is developed for the efficient P-BF design of the considered scheme. To strike a balance between complexity and performance, we further propose a simplified P-BF algorithm by approximating the stochastic program as a deterministic alternating optimization problem. For the receiver design, the signal detection at the receiver is a bilinear estimation problem since the RIS information is multiplicatively modulated onto the reflected signals of the reflecting elements. To solve this bilinear estimation problem, we develop a turbo message passing (TMP) algorithm in which the factor graph associated with the problem is divided into two modules: one for the estimation of the user signals and the other for the estimation of the on-off state of each RIS element. The two modules are executed iteratively to yield a near-optimal low-complexity solution. Furthermore, we extend the design of the Mu-MIMO PBIT scheme from single-RIS to multi-RIS, by leveraging the similarity between the single-RIS and multi-RIS system models. Extensive simulation results are provided to demonstrate the advantages of our P-BF and receiver designs.

Average Vector-Symbol Error Rate Closed-Form Expression for ML Group Detection Receivers in Large MU-MIMO Channels With Transmit Correlation

In this paper, we derive a closed-form expression for the evaluation of the average vectorsymbol error rate (VER) of group detection followed by maximum-likelihood (GD-ML) receivers in large multi-user multiple-input multiple-output (MU-MIMO) systems with transmit side correlated Rayleigh channels. We assume M antennas at the base station (BS), N closely-located, single-antenna user equipment (UEs) with load factor λ = N/M , and N ≫ 1; consequently, we evaluate the performance of GD-ML receivers as the load factor grows to unity. The derived expression requires a negligible correlation at the receive side of the communication channel. Hence, from a practical point-of-view, when considering scenarios with a large number of UEs, the derived analytical expression is generally more applicable for systems with a distributed massive number of BS antennas. Numerical results are provided to validate our derived expression. We observe that the GD-ML with Nu group size achieves a diversity order proportional to M - N + Nu. Moreover, we show that for small group sizes, the analytical and simulation results remain close, and at moderate to high signal-to-noise ratio (SNR), the derived expression very closely matches the simulations, whereas this match becomes perfect as the users' side correlation increases. We also demonstrate that GD-ML outperforms the zero-forcing (ZF) and minimum mean-squared error (MMSE) receivers, in terms of VER; where for high λ, GD-ML exploits the maximum spatial multiplexing gain. Moreover, in terms of floating-point operations (FLOPs), we show that GD-ML receivers have almost the same complexity as ZF and MMSE where the ML detection stage adds a negligible complexity compared to the channel matrix inversion operation.

Hybrid zero‐forcing for correlated and semi‐orthogonal multi‐user MU‐MIMO channels

Fifth generation cellular networks must support dense user environments where close proximity users and highly correlated channels are prevalent. This study presents a novel decorrelating zero-forcing (DZF) scheme. It improves downlink zero-forcing (ZF) performance over multi-user multiple-input multiple-output channels when highly correlated users are present. DZF groups correlated users into pairs where the stronger user is labelled ‘near’ and the weaker user, ‘far’. For the far and unpaired users, the proposed design is similar to conventional ZF (CZF) in that the base station performs traditional ZF and the users employ the leading left singular vectors of the channel for processing. In contrast, the near users employ the second strongest left singular vector which decorrelates their effective channel with the paired far user. This reduces the noise inflation inherent in ZF for correlated channels. From simulations and analysis the authors demonstrate that DZF has both rate and fairness advantages over CZF when highly correlated users are present. Furthermore, they design a hybrid ZF (HZF) scheme, which harnesses the advantages of both CZF and DZF, hence providing robustness against the joint scheduling of semi-orthogonal and highly correlated users with very little additional complexity. Simulations clearly demonstrate that HZF has higher rates than CZF and DZF.

A user pairing method to improve the channel capacity for multiuser MIMO channels in downlink mode based on NOMA

This paper investigates applications of multiple-input multiple-output (MIMO) in non-orthogonal multiple access (NOMA) for downlink multiuser systems, where the total number of transmitter antennas is equal to or less than receiver antennas in each user. We also consider a user pairing scheme involving 3 users per cluster with non-overlapping frequency band for users with similar channel gains. The integration of beamforming and user pairing along with successive interference cancellation (SIC) can reduce occurred interference and maximize the sum rate in MIMO-NOMA systems. The novelty of this work is to provide a solution for achieving better performance and massive connectivity in NOMA with 3 users in each cluster by increasing the number of transmitter and receiver antennas. The analytical expressions of the MIMO-NOMA transmission scheme are derived in the ergodic sum capacity term. Also, the impact of the number of users in a cluster on the ergodic capacity of the desired NOMA scheme is evaluated. Finally, computer simulation results are performed to show the superiority of MIMO-NOMA over MIMO-OMA and MIMO-(NOMA-OMA).

A Novel Nonlinear and Non-iterative Precoding Technique for Single and Multi User MIMO Systems

A modification of the well known linear and iterative based precoder intended for both single and multi-user multiple-input multiple-output (MIMO) has been proposed. The proposed precoder uses the nonlinear and non-iterative processing strategies to obtain more efficient and less complexity designs. The non-linearity in the precoder is introduced by using the nonlinear constellation precoding technique based on maximum distance separable codes. Also, the computation complexity in iterative based precoder design is avoided by using a singular value decomposition method. The maximum likelihood detection for the linear MIMO channel is considered. The simulation results are provided in-terms of bit error rate versus signal-to-noise ratio to show that the proposed combined non-linear and non-iterative precoding schemes outperform the conventional linear and iterative based MIMO precoder designs.

Prediction of Time-Varying Multi-User MIMO Channels Based on DOA Estimation Using Compressed Sensing

In multi-user multiple-input multiple-output (MIMO) systems, a base station requires downlink channel state information for each user to suppress interferences. In time-varying environments, however, channels at the actual transmission time differ from the estimated ones because we have delay. This causes interference and deteriorates the packet error rate performance. To overcome this problem, we previously proposed a channel prediction method based on direction of arrival (DOA) estimation of multipath components obtained with a compressed sensing technique. This method can predict channels with high accuracy when we can assume that user equipment alone moves and the surrounding scatterers are stationary. In real environments, however, this assumption does not hold, and this method cannot be applied. In this paper, we propose a prediction method using two-step compressed sensing without the above assumption. In the first step, we estimate the DOAs of multipath signals. In the second step, we estimate the Doppler frequencies and their complex amplitudes using the estimated DOA information. From these values, we predict the MIMO channels at the actual transmission time. We discuss the performance of this method in this paper.

Nested Precoding in MU-MIMO Channels: The Superposition Transmission of Space-Time Coding and Spatial-Division Multiplexing

Nonorthogonal multiple access (NOMA) can improve the spectrum efficiency through reusing the power-level space by different users. Although NOMA in single-input single-output channels has been thoroughly explored, it is still underexploited in multiple-input multiple-output (MIMO) channels. Precoding design in multiuser MIMO channels with nonorthogonal transmission is a multidimensional nesting problem, it is hard to compare two matrix channels if only their power levels are considered. In this paper, we first propose a method to compare the covariance matrices of two channel matrices, and then derive a channel condition under which the linear precoding scheme can achieve the sum capacity. Considering arbitrary realizations of multiuser channels, we provide a nested precoding algorithm that can work well in highly correlated multiuser channels. Based on this idea, a specialized superposition transmission scheme between signaling and data information is proposed, where plenty of resources beneath the signaling signal are utilized to transmit data information for dedicated users, and a large amount of extra rates are achieved. In addition, space-time coding is used for signaling information and spatial-division multiplexing is used for multiuser data information. Under the constraint that signaling information should be correctly decoded at any position in the cell, we seek to maximize the sum rate of the underneath multiuser data streams. To this end, the optimal and a low-complexity simplified precoding algorithms are developed. Finally, simulation results verify the throughput improvement and the correct decoding probability of the signaling information.

Multi-User Millimeter Wave MIMO With Full-Dimensional Lens Antenna Array

Millimeter wave (mmWave) communication by utilizing lens antenna arrays is a promising technique for realizing cost-effective 5G wireless systems with large MIMO (multiple-input multiple-output) but only limited radio frequency (RF) chains. This paper studies an uplink multi-user mmWave single-sided lens MIMO system, where only the base station (BS) is equipped with a full-dimensional (FD) lens antenna array with both elevation and azimuth angle resolution capabilities, and each mobile station (MS) employs the conventional uniform planar array (UPA) without the lens. By exploiting the angle-dependent energy focusing property of the lens antenna array at the BS as well as the multi-path sparsity of mmWave channels, we propose a low-complexity path division multiple access (PDMA) scheme, which enables virtually interference-free multi-user communications when the angle of arrivals (AoAs) of all MS multi-path signals are sufficiently separable at the BS. To this end, a new technique called path delay compensation is proposed at the BS to effectively transform the multi-user frequency-selective MIMO channels to parallel frequency-flat small-size MIMO channels for different MSs, for each of which the low-complexity single-carrier(SC) transmission is applied. For general scenarios with insufficient AoA separations, analog beamforming at the MSs and digital combining at the BS are jointly designed to maximize the achievable sum-rate of the MSs based on their effective MIMO channels resulting from path delay compensation. In addition, we propose a new and efficient channel estimation scheme tailored for PDMA, which requires negligible training overhead in practical mmWave systems and yet leads to comparable performance as that based on perfect channel state information (CSI).

Multiuser Space–Time Line Code With Optimal and Suboptimal Power Allocation Methods

In this paper, a multiuser space-time line code (STLC) system is proposed. In the proposed multiuser STLC system, a zero-forcing (ZF)-based precoder decomposes multiuser multiple-input multiple-output (MIMO) channels into multiple single-user MIMO channels, and the STLC is performed with the effective single user MIMO channel independently for each user. Here, to maximize the sum rate, an optimal power allocation method is designed based on a water-filling strategy. Also, a simple suboptimal method called fairness-aware per-user (FAPU) power allocation is devised. It is analytically and numerically verified that each user of the proposed ZF-based STLC system asymptotically achieves the maximum of single-user achievable rate as the number of transmit antennas increases. The numerical results of rigorous simulation justify that the proposed ZF-based STLC with FAPU power allocation provides near optimal performance and outperforms the existing ZF-based maximum Eigen beamforming scheme and conventional multiuser STLC schemes. Furthermore, two simple search algorithms to find the optimal number of users that maximizes sum rate are devised. Numerical results verify that the proposed algorithms can effectively find the optimal number of users by reducing the search interval.

Iterative Hybrid Precoder and Combiner Design for mmWave Multiuser MIMO Systems

This letter investigates analog/digital hybrid precoder and combiner design for millimeter wave (mmWave) multiuser multiple-input multiple-output (MU-MIMO) systems. We propose a novel iterative algorithm for the joint hybrid precoder and combiner design by exploiting the duality of the uplink and downlink MU-MIMO channels. For the initialization stage, the proposed algorithm selects the analog precoder-combiner pair based on the orthogonal matching pursuit (OMP) algorithm to enhance the channel gain, while mitigating the multiple access interference, and obtains the digital combiner via minimum mean square error criterion. Then, the proposed algorithm enhances the performance gradually at each iteration via joint design of the uplink and downlink precoders/combiners. Simulation results demonstrate the significant performance advantages of the proposed precoder and combiner design compared with existing hybrid beamforming algorithms.

Design of Low Complex Linear Precoding Scheme for MU-MIMO Systems

The block diagonalization (BD) is a linear precoding technique for multiuser interference elimination in multi-user multiple-input multiple-output (MU-MIMO) systems. Though various methods of block diagonalization have been identified, they are convoluted regarding the computations involved. In this paper we have modeled a new paradigm for the performance improvement and complexity reduction in BD based precoding algorithms. This is consummated using principal component analysis (PCA). The traditional highly complex singular value decomposition is replaced by QR decomposition in PCA (QR-PCA) for complexity reduction. The PCA along with QR decomposition and minimum mean squared error (MMSE) channel inversion technique parallelize the MU-MIMO channel into independent and proportionate single user MIMO channel. The simulation result shows that the proposed QR-PCA based precoding algorithm in comparison with the existing algorithm achieves comparatively better sum-rate, lower BER, and lower computational complexity. The PCA along with MMSE channel inversion avoids the decoder structure, which makes the receiver system simple.

Self-Interference in Full-Duplex Multi-User MIMO Channels

We consider a multi-user multiple-input multiple-output (MIMO) setup where full-duplex (FD) multi-antenna nodes apply linear beamformers to simultaneously transmit and receive multiple streams over Rician fading channels. The exact first and second positive moments of the residual self-interference (SI), involving the squared norm of a sum of non-identically distributed random variables, are derived in closed-form. The method of moments is hence invoked to provide a Gamma approximation for the residual SI distribution. The proposed theorem holds under arbitrary linear precoder/decoder design, number of antennas and streams, and SI cancellation capability.

Extending the user capacity of MU-MIMO systems with low detection complexity and receive diversity

Multiple-input multiple-output (MIMO) based technologies are considered as an integral part of the upcoming 5G communications to fulfil the ever-increasing demands of wireless applications with high spectral efficiency requirements. However, in uplink multiuser MIMO (MU-MIMO) channels, the number of allowed users is limited by the number of receive antennas associated with radio frequency (RF) chains at the base-station and the complexity burden of multiuser detection (MUD). In this paper, a novel group layer MU-MIMO scheme with low complexity MUD is proposed to increase the number of served users well beyond the available RF chains. By taking the advantage of power control and inherent path loss in cellular systems, the allowed users are divided into groups based on their received power. Efficient group power allocation and group layer MUD (GL-MUD) are utilized to provide a valuable tradeoff between complexity and achieved performance. Furthermore, when more receive antennas than RF chains is implemented, a generalized norm based antenna selection algorithm is proposed to enhance the error performance. Symbol error probability expressions are derived and the effectiveness of proposed scheme is demonstrated through numerical simulations compared with the conventional MU-MIMO and non-orthogonal multiple-access (NOMA) systems over Rayleigh fading channels. The results show a substantial increase in user capacity up to two-fold for the available number of RF chains. In addition, significant signal-to-noise ratio gain is achieved using GL-MUD compared with different MUD techniques.

An Energy Saving Strategy for LTE-A Multiantenna Systems

Long Term Evolution - Advanced (LTE-A) supports closed-loop Multiple Input Multiple Output (MIMO) techniques to improve its performance, but in order to exploit multiuser (MU) MIMO channel capabilities, the design of an efficient Medium Access Control (MAC) scheme that supports MU-MIMO is still an open issue in the literature. This paper proposes a novel energy efficient MAC scheme for LTE-A, which aims to achieve simultaneous downlink transmissions to multiple users, through the deployment of a low complexity beamforming technique at the physical layer. Our proposed scheme takes advantage from the multiuser gain of the MIMO channel and the multiplexing gain of the Multibeam Opportunistic Beamforming (MOB) technique, to improve the system throughput and the energy efficiency of wireless networks. We provide a closed form mathematical expression of the energy efficiency, where the results from the proposed scheme achieve a considerable energy saving at the Base Station (eNB).

Pilot Reuse for Massive MIMO Transmission over Spatially Correlated Rayleigh Fading Channels

We propose pilot reuse (PR) in single cell for massive multiuser multiple-input multiple-output (MIMO) transmission to reduce the pilot overhead. For spatially correlated Rayleigh fading channels, we establish a relationship between channel spatial correlations and channel power angle spectrum when the base station antenna number tends to infinity. With this channel model, we show that sum mean square error (MSE) of channel estimation can be minimized provided that channel angle of arrival intervals of the user terminals reusing the pilots are non-overlapping, which shows feasibility of PR over spatially correlated massive MIMO channels with constrained channel angular spreads. Regarding that channel estimation performance might degrade due to PR, we also develop the closed-form robust multiuser uplink receiver and downlink precoder that minimize sum MSE of signal detection, and reveal a duality between them. Subsequently, we investigate pilot scheduling, which determines the PR pattern, under two minimum MSE related criteria, and propose a low complexity pilot scheduling algorithm which relies on the channel statistics only. Simulation results show that the proposed PR scheme provides significant performance gains over the conventional orthogonal training scheme in terms of net spectral efficiency.

Energy Beamforming With One-Bit Feedback

Multi-antenna or multiple-input multiple-output (MIMO) techniques are appealing to enhance the transmission efficiency and range for radio frequency (RF) signal enabled wireless energy transfer (WET). In order to reap the energy beamforming gain in MIMO WET, acquiring the channel state information (CSI) at the energy transmitter (ET) is an essential task. This task is particularly challenging, since existing channel training and feedback methods used for communication receivers may not be implementable at the energy receiver (ER) due to its hardware limitation. To tackle this problem, we consider in this paper a multiuser MIMO WET system, and propose a new channel learning method that requires only one feedback bit from each ER to the ET per feedback interval. Specifically, each feedback bit indicates the increase or decrease of the harvested energy by each ER in the present as compared to the previous intervals, which can be measured without changing the existing structure of the ER. Based on such feedback information, the ET adjusts transmit beamforming in subsequent training intervals and at the same time obtains improved estimates of the MIMO channels to different ERs by applying an optimization technique called analytic center cutting plane method (ACCPM). For the proposed ACCPM based channel learning algorithm, we analyze its worst-case convergence, from which it is revealed that the algorithm is able to estimate multiuser MIMO channels simultaneously without reducing the analytic convergence speed. Also, we provide extensive simulations to show its performances in terms of both convergence speed and energy transfer efficiency.

Opportunistic round robin scheduling for V-BLAST systems over multiuser MIMO channels

In this paper, we study opportunistic round robin (ORR) uplink scheduling for vertical Bell Labs layered space-time architecture (V-BLAST) systems over multiuser multiple-input multiple-output (MIMO) channels. The proposed ORR scheduling method is compared to greedy scheduling. In greedy scheduling, the base station selects the best user based on a certain criterion without any consideration for fairness. On the other hand, ORR scheduling guarantees full fairness and each user will be served by excluding the previous selected users from the competition in the next round. The selected user spatially multiplexes his data over the transmit antennas. This spatial multiplexing (SM) scheme provides high data rates, while multiuser diversity obtained from scheduling improves the performance of the uplink system. The results show the performance and capacity gains obtained by scheduling. The greedy scheduler captures full multiuser diversity. In contrast, the ORR scheduler provides substantial signal-to-noise ratio (SNR) gains compared to round robin while guaranteeing full fairness to all users.