MIMO Downlink Systems Research Articles

Low Spatial Peak-to-Average Power Ratio Transmission for Improved Energy Efficiency in Massive MIMO Systems.

A significant portion of the operating power of a base station is consumed by power amplifiers (PAs). Much of this power is dissipated in the form of heat, as the overall efficiency of currently deployed PAs is typically very low. This is because the structure of conventional precoding techniques typically results in a relatively high variation in output power at different antennas in the array, and many PAs are operated well below saturation to avoid distortion of the transmitted signals. In this work, we use a realistic model for power consumption in PAs and study the impact of power variation across antennas in the array on the energy efficiency of a massive MIMO downlink system. We introduce a family of linear precoding matrices that allow us to control the spatial peak-to-average power ratio by projecting a fraction of the transmitted power onto the null space of the channel. These precoding matrices preserve the structure of conventional precoders; e.g., they suppress multiuser interference when used together with zeroforcing precoding and bring advantages over these precoders by operating PAs in a more power-efficient region and reducing the total radiated distortion. Our numerical results show that by controlling the power variations between antennas in the array and incorporating the nonlinearity properties of PA into the precoder optimization, significant gains in energy efficiency can be achieved over conventional precoding techniques.

Quantized precoding and companding schemes for PAPR reduction in UFMC‐based massive MIMO downlink systems

AbstractUniversal‐filtered multi‐carrier (UFMC) is a promising waveform technology, which inherits the robustness of FBMC and simplicity of OFDM. In this article, the UFMC waveform is combined with the massive multi‐user multiple‐input and multiple‐output (MU‐MIMO) technology to meet the desired needs of future wireless networks. In order to eliminate MU interference (MUI), the precoding is essential in massive MU‐MIMO downlink. However, the transmitted signals produced by the precoders have high peak‐to‐average power ratio (PAPR), thus resulting in reduction of power efficiency of the system. Hence, this article proposes the quantized MU precoding and companding schemes to increase the power efficiency of UFMC‐based massive MU‐MIMO downlink systems. A nonlinear quantized precoder called squared‐infinity norm Douglas‐Rachford splitting (SQUID), which generates signals with constant envelope, is proposed. The proposed SQUID precoder reduces the power consumption and MUI of UFMC‐based massive MU‐MIMO systems. Moreover, a piecewise linear companding (PLC) scheme, which further reduces the PAPR by employing two threshold values and one companding parameter, is also proposed. The simulation results confirm that the proposed UFMC‐based massive MU‐MIMO with quantized nonlinear SQUID precoding provides better performance than quantized linear precoders. Besides, the proposed system with the PLC scheme offers better PAPR reduction of 4.5 dB when compared with linear nonsymmetrical transform and ‐law schemes.

Deep learning based user scheduling for massive MIMO downlink system

Deep learning based user scheduling for massive MIMO downlink system

On the MMSE‐based multiuser millimeter wave MIMO hybrid precoding design

SummaryA hybrid MMSE‐based precoder and combiner design with low complexity is studied in this paper for both the downlink and uplink multiuser millimeter wave MIMO systems. At first, according to the underlying channel knowledge, the phases of the RF precoder and combiner are manipulated by using the MMSE criterion. On the basis of the MMSE‐based analog precoder design, the MMSE‐based digital baseband precoder can be readily derived. Thus, this method combines the advantage of using the MMSE precoding and phase extraction technique to obtain a reasonable solution. The proposed hybrid precoding design will be examined in both the uplink and downlink multiuser MIMO systems. Numerical results are presented to show that the proposed MMSE‐based hybrid precoding design is capable of attaining superior performance in terms of both the spectral efficiency and energy efficiency over the existing designs. Moreover, we will show that the MMSE‐based design can be readily extended to the multiuser millimeter wave MISO systems when only statistical channel state information is available.

On the Optimal CSI Feedback Rate of Downlink MIMO Systems Using Multiple Receive Antennas in Cellular Networks

A downlink cellular network is considered, in which multiple-antenna base stations (BSs) are distributed following a homogeneous Poisson point process. Each BS serves a single user equipped with multiple-receive antennas. The partial channel state information is achieved at the transmitter using a limited feedback. The singular-value-decomposition-based precoding is performed for the downlink spatial multiplexing. In this letter, the optimal number of feedback bits that maximizes the net spectral efficiency is investigated. The net spectral efficiency is defined to measure the net profit achieved by using limited-feedback-based spatial multiplexing. By extending previous studies, the effect of using multiple-receive antennas on the optimal number is investigated. Specifically, the scaling rate of the optimal number is newly obtained for more than one receive antenna.

Throughput Enhancement in Downlink MU-MIMO Using Multiple Dimensions

This paper focuses on the throughput performance enhancement in the single cell multi-user MIMO (MU-MIMO) downlink system model. For better quality of service, this paper proposes the scheme that increases system throughput and improves the spectral efficiency. Specifically, the signal transmission and detection schemes are proposed by using multiple dimensions. At the transmitter side, two dimensions (power and space) are adopted at the same time. To achieve multiple access (MA), the space domain is exploited by using a block diagonalization (BD) precoding technique, and the power domain is exploited to transmit more data symbols. At the receiver, the signal detection structure corresponding to a transmitter is also proposed. In the simulation results, comparisons of throughput performance are presented in various aspects. As a result, the proposed scheme outperforms the conventional schemes using only one dimension in terms of throughput. This paper shows strong performance in MU-MIMO senarios by adopting multiple dimensions.

Energy and spectral efficiency of secure massive MIMO downlink systems

Spectral efficiency, energy efficiency, and security are cornerstones for the upcoming 5G systems. In this study, the issue of how the energy and spectral efficiency of multiuser massive multiple-input multiple-output (Ma-MIMO) systems are affected in the presence of a secrecy constraint is addressed. The performance of the two most prominent linear precoding techniques, the matched filter (MF) and zero-forcing (ZF) precoders, for secure downlink multiuser Ma-MIMO in the presence of multi-antenna passive eavesdropper is investigated. The authors consider three performance metrics, namely, the achievable ergodic secrecy rate, the secrecy spectral efficiency (SSE), and the secrecy energy efficiency (SEE), assuming perfect and imperfect channel state information. The tradeoff between SSE and SEE is also studied. Moreover, the authors derive tight lower bounds on the achievable ergodic secrecy rate for MF and ZF precoding techniques. The derived lower bounds provide insights on the tradeoff between the SSE and SEE. It is shown that ZF precoder outperforms MF precoder at high transmit power, whereas at very low transmit power, MF outperforms ZF. Moreover, it is shown that using large number of transmit antennas can improve the SSE and the SEE with orders of magnitude compared to a single-input single-output system.

Spectral Efficiency Maximization of a Single Cell Massive MU-MIMO Down-Link TDD System by Appropriate Resource Allocation

This paper deals with the problem of maximizing the spectral efficiency in a massive multi-user MIMO downlink system, where a base station is equipped with a very large number of antennas and serves single-antenna users simultaneously in the same frequency band, and the beamforming training scheme is employed in the time-division duplex mode. An optimal resource allocation that jointly selects the training duration on uplink transmission, the training signal power on downlink transmission, the training signal power on uplink transmission, and the data signal power on downlink transmission is proposed in such a way that the spectral efficiency is maximized given the total energy budget. Since the spectral efficiency is the main concern of this work, and its calculation using the lower bound on the achievable rate is computationally very intensive, in this paper, we also derive approximate expressions for the lower bound of achievable downlink rate for the maximum ratio transmission (MRT) and zero-forcing (ZF) precoders. The computational simplicity and accuracy of the approximate expressions for the lower bound of achievable downlink rate are validated through simulations. By employing these approximate expressions, experiments are conducted to obtain the spectral efficiency of the massive MIMO downlink time-division duplexing system with the optimal resource allocation and that of the beamforming training scheme. It is shown that the spectral efficiency of the former system using the optimal resource allocation is superior to that yielded by the latter scheme in the cases of both MRT and ZF precoders.

Worst-case weighted sum-rate maximization in multicell massive MIMO downlink system for 5G communications

In this paper, we present a robust beamforming design to examine the weighted sum-rate maximization (WSRM) problem in a multicell massive MIMO downlink system for 5G communications. This work assume imperfect channel state information (CSI) by adding uncertainties to channel matrices with worst-case models i.e. singular value uncertainty model (SVUM) and ellipsoidal uncertainty model (EUM). In SVUM, WSRM problem is formulated subject to the transmit power constraints. While, the problem is devised in EUM by alternatively considering its dual power minimization problem subject to the worst-case signal-to-interference-plus-noise ratio (SINR) constraints for all mobile stations. The designed problem for both SVUM and EUM are known as non-deterministic polynomial (NP) problem which is difficult to solve. We propose an iterative algorithm established on majorization minimization (MM) technique that solves and achieves convergence to stationary point of these two problems. In EUM, the convergence point is obtained after converting the infinite number of SINR constraints into linear matrix inequalities (LMI) by employing S-Procedure. Extensive numerical results are provided to show that the proposed iterative algorithm significantly increases performance in terms of sum-rate and also attains faster convergence as compared with the conventional polynomial time algorithm.

Design of Low-Complexity Hybrid Precoder and Inkjet-Printed Antenna Array for Massive MIMO Downlink Systems

The dramatically growing mobile communication industry necessitates the demand for the speedy and error-free connectivity at considerably low cost for the billions of users. This is made possible only through the technological advancements that replace the current 4G wireless systems by 5G. Massive MIMO is the key technology used in 5G that offers spectral efficiency of up to 3 times and throughput of up to 10 times the current 4G. The additional antennas used in massive MIMO systems help in many ways but lack in complexity. Hence, in this paper, we propose two design methodologies to reduce the complexity of massive MIMO systems. The first one is the design of low-complexity hybrid precoder based on Zero-Forcing (ZF) precoding algorithm and Neumann series approximation. The second one is the design of flexible, environment friendly, simple 128-element antenna array at the frequency of 2.4 GHz using inkjet printing technology. The substrate used for printing is the “glossy paper” with dielectric constant of 2.31, and the ink used is silver nanoparticle ink with conductivity of 35,700,000 s/m. The element used for the formation of array is the z-shaped coplanar waveguide (CPW) monopole antenna. The performance of the proposed designs is evaluated in terms of probability of error for the hybrid precoding algorithm and radiation characteristics like gain, directivity, and return loss for the printed antenna design.

An Interference Cancellation Technique for Distributed MIMO Systems

This study proposes an uncooperative-multi-cell-multiple-input–multiple-output system to increase the throughput of an ill-conditioned wireless MIMO downlink system. The proposed algorithm suppresses the inter-cell interference at each mobile station using a set of adaptive receive beamformers, but handles the intra-cell interference at each base station using a Tomlinson Harashima precoder. Using the singular vectors of channel matrices, the receive beamformers can be designed based on a linear-constrained-minimum-variance criterion. On the other hand, to obtain high enough degree of freedoms for cancelling the intra-cell interference at each base station, the precoder is applied to the re-assembled downlink virtual channel formed by the simplified channel state information. Using the proposed interference suppression techniques, a multi-cell downlink system with multiple uncooperative base stations can be decomposed into a set of parallel subchannels. The resulting system has better performance in channel capacity than conventional MIMO systems. Computer simulations support the validity of the proposed approach.

Novel Precoder Design with Generalized Side-Information Cancellation for Multiuser MIMO Downlink Systems

Novel Precoder Design with Generalized Side-Information Cancellation for Multiuser MIMO Downlink Systems

Performance Analysis of Multi-User Massive MIMO Downlink Under Channel Non-Reciprocity and Imperfect CSI

This paper analyzes the performance of linearly precoded time division duplex based multi-user massive MIMO downlink system under joint impacts of channel non-reciprocity (NRC) and imperfect channel state information (CSI). We consider a generic and realistic NRC model that accounts for transceiver frequency-response as well as mutual coupling mismatches at both user equipment (UE) and base station (BS) sides. The analysis covers two most prominent forms of linear precoding schemes, namely, zero-forcing (ZF) and maximum-ratio transmission (MRT), and assumes that only the statistical properties of the beamformed channel are used at the UE side to decode the received signal. Under the approximation of i.i.d. Gaussian channels, closed-form analytical expressions are derived for the effective signal to interference and noise ratios (SINRs) and the corresponding capacity lower bounds. The expressions show that, in moderate to high SNR, the additional interference caused by imperfect NRC calibration can degrade the performance of both precoders significantly. Moreover, ZF is shown to be more sensitive to NRC than MRT. Numerical evaluations with practical NRC levels indicate that this performance loss in the spectral efficiency can be as high as 42% for ZF, whereas it is typically less than 13% for MRT. It is also shown that due to the NRC, the asymptotic large-antenna performance of both precoders saturate to an identical finite level. The derived analytical expressions provide useful tools and valuable technical insight, e.g., into calculating the NRC calibration requirements in BSs and UEs for any given specific performance targets in terms of effective SINR or the system capacity bound.

Statistical 3-D Beamforming for Large-Scale MIMO Downlink Systems Over Rician Fading Channels

In this paper, we investigate a downlink transmission algorithm for single-cell multiuser systems with two-dimensional (2-D) large-scale antenna array at the base station (BS) over Rician fading channels. We first derive some properties of the channel’s line-of-sight (LOS) component in the large-scale antenna array scenario. Next, based on these properties and under the assumption of only statistical channel state information (CSI), i.e., the LOS component and Rician $K$ -factor, at the BS, we derive the optimal beamforming vector for each user in maximizing an approximation of the ergodic sum rate. The main guidelines for user scheduling are also presented. Then, a three-dimensional (3-D) beamforming downlink transmission algorithm exploiting only the statistical CSI of each user is proposed. For this algorithm, we derive an exact analytical closed-form expression for the achievable ergodic rate and present tractable approximations. Based on our analysis, we gain some valuable insights. The proposed algorithm is shown to perform well in achieving considerable sum rate while requiring much less CSI at the BS. It requires three scalar values at the BS for each user, and can achieve an ergodic sum rate closer to the ergodic sum rate achieved by the matched-filter precoding with perfect CSI at the BS.

Performance analysis of zero forcing based multiuser MIMO downlink system under time variant channels

Performance analysis of zero forcing based multiuser MIMO downlink system under time variant channels

A Constellation Scaling Approach to Vector Perturbation for Adaptive Modulation in MU-MIMO

It is known that vector perturbation (VP) precoding does not apply to the case where users employ different modulations, while existing solutions for this scenario are suboptimal. In this letter, a joint vector perturbation precoding algorithm is proposed for multiuser MIMO (MU-MIMO) downlink system in the adaptive modulation scenario where different users apply different modulation types. Compared with conventional block diagonalized vector perturbation (BD-VP) and user grouping VP where the search dimension of the perturbation vector is reduced, the proposed algorithm keeps the search dimension unchanged by applying a simple transformation to the VP operation. Our analysis and results show that the proposed algorithm provides an applicable VP solution to the adaptive modulation scenario, with optimal VP performance.

Low-Complexity Downlink User Selection for Massive MIMO Systems

In this paper we propose a pair of low-complexity user selection schemes with zero-forcing precoding for multiuser massive MIMO downlink systems, in which the base station is equipped with a large-scale antenna array. First, we derive approximations of the ergodic sum rates of the systems invoking the conventional random user selection (RUS) and the location-dependant user selection (LUS). Then, the optimal number of simultaneously served user equipments (UEs), $K^*$, is investigated to maximize the sum rate approximations. Upon exploiting $K^*$, we develop two user selection schemes, namely $K^*$-RUS and $K^*$-LUS, where $K^*$ UEs are selected either randomly or based on their locations. Both of the proposed schemes are independent of the instantaneous channel state information of small-scale fading, therefore enjoying the same extremely-low computational complexity as that of the conventional RUS scheme. Moreover, both of our proposed schemes achieve significant sum rate improvement over the conventional RUS. In addition, it is worth noting that like the conventional RUS, the $K^*$-RUS achieves good fairness among UEs.

MU-MIMO 하향링크 시스템에서의 MRT 기법 사용 시 에너지 효율을 최대화하는 최적 송신 안테나의 수

MU-MIMO 하향링크 시스템에서의 MRT 기법 사용 시 에너지 효율을 최대화하는 최적 송신 안테나의 수

Robust Transceiver Design for Multicell MIMO Downlink Systems

The robust linear transceiver design for the more general model of multicell MIMO downlink system with imperfect channel state information is discussed in this paper. Our aim is to minimize the total power of the network while the quality of service (QoS) in terms of mean-square error (MSE) for every user should be strictly guaranteed for every channel realization in the uncertain region. Unfortunately, this problem may be infeasible due to the MSE constraints. Therefore, we provide a complete analysis of this problem by dividing the solutions into two phases. In phase I, a novel approach is devised to check the feasibility of this problem by considering one alternative problem which is always feasible. This alternative problem is troublesome due to infinite nonconvex MSE constraints. To handle this, we propose an iterative algorithm that performs optimization alternatively by switching between the precoders and decoders. The two subproblems in the algorithm can be recast as semidefinite programming problems which can be efficiently solved. In phase II, one novel iterative algorithm is proposed to solve the original robust problem. Finally, simulation results show that our proposed algorithms converge rapidly and can provide guaranteed QoS for all users. Moreover, we also show that, the more antennas at the users, the more power savings it can provide.

Unified Analysis of Multiuser Scheduling for Downlink MIMO Systems with Imperfect CSI

In this paper, unified BER performance and outage probability analyses of downlink multiuser scheduling for multiple-input multiple-output (MUS-MIMO) transmission/combining (transceiving) systems with imperfect channel state information (CSI) caused by feedback over Rayleigh fading channels is presented. The unified analysis is applicable to MIMO transceiving systems whose received signal-to-noise ratio (SNR) is given as largest order statistic of chi-square distribution. The performance of MUS-MIMO employing selective transmission/selective combining (ST/SC), ST/maximum ratio combining (MRC) and space-time block codes (STBC) can be analyzed by this general framework. Accurate and approximate unified closed-form BER and outage probability expressions of the MUS-MIMO transceiving system with normalized SNR-based scheduling in heterogeneous networks are derived. Based on the approximate BER and outage probability expressions, diversity gains are analyzed at high SNR. The results indicate that the MUS-MIMO for using the three transceiving schemes can achieve full diversity order for perfect CSI, while the diversity gain is degraded differently for the three transceiving schemes under imperfect CSI. Computer simulation shows that the theoretical analysis is in good agreement with simulation results, and the approximate BER expressions are very close to the accurate ones but with lower computational complexity.