Showing papers on "Multi-user MIMO published in 2017"
TL;DR: This paper provides an overview of the existing multibeam antenna technologies which include the passiveMultibeam antennas (MBAs) based on quasi-optical components and beamforming circuits, multibeams phased-array antennas enabled by various phase-shifting methods, and digital MBAs with different system architectures.
Abstract: With the demanding system requirements for the fifth-generation (5G) wireless communications and the severe spectrum shortage at conventional cellular frequencies, multibeam antenna systems operating in the millimeter-wave frequency bands have attracted a lot of research interest and have been actively investigated. They represent the key antenna technology for supporting a high data transmission rate, an improved signal-to-interference-plus-noise ratio, an increased spectral and energy efficiency, and versatile beam shaping, thereby holding a great promise in serving as the critical infrastructure for enabling beamforming and massive multiple-input multiple-output (MIMO) that boost the 5G. This paper provides an overview of the existing multibeam antenna technologies which include the passive multibeam antennas (MBAs) based on quasi-optical components and beamforming circuits, multibeam phased-array antennas enabled by various phase-shifting methods, and digital MBAs with different system architectures. Specifically, their principles of operation, design, and implementation, as well as a number of illustrative application examples are reviewed. Finally, the suitability of these MBAs for the future 5G massive MIMO wireless systems as well as the associated challenges is discussed.
737 citations
TL;DR: Three forms of IM are investigated: spatial modulation, channel modulation and orthogonal frequency division multiplexing (OFDM) with IM, which consider the transmit antennas of a multiple-input multiple-output system, the radio frequency mirrors mounted at a transmit antenna and the subcarriers of an OFDM system for IM techniques, respectively.
Abstract: What is index modulation (IM)? This is an interesting question that we have started to hear more and more frequently over the past few years. The aim of this paper is to answer this question in a comprehensive manner by covering not only the basic principles and emerging variants of IM, but also reviewing the most recent as well as promising advances in this field toward the application scenarios foreseen in next-generation wireless networks. More specifically, we investigate three forms of IM: spatial modulation, channel modulation and orthogonal frequency division multiplexing (OFDM) with IM, which consider the transmit antennas of a multiple-input multiple-output system, the radio frequency mirrors (parasitic elements) mounted at a transmit antenna and the subcarriers of an OFDM system for IM techniques, respectively. We present the up-to-date advances in these three promising frontiers and discuss possible future research directions for IM-based schemes toward low-complexity, spectrum- and energy-efficient next-generation wireless networks.
676 citations
TL;DR: Cell-free Massive MIMO is shown to provide five- to ten-fold improvement in 95%-likely per-user throughput over small-cell operation and a near-optimal power control algorithm is developed that is considerably simpler than exact max–min power control.
Abstract: Cell-free Massive multiple-input multiple-output (MIMO) comprises a large number of distributed low-cost low-power single antenna access points (APs) connected to a network controller. The number of AP antennas is significantly larger than the number of users. The system is not partitioned into cells and each user is served by all APs simultaneously. The simplest linear precoding schemes are conjugate beamforming and zero-forcing. Max–min power control provides equal throughput to all users and is considered in this paper. Surprisingly, under max–min power control, most APs are found to transmit at less than full power. The zero-forcing precoder significantly outperforms conjugate beamforming. For zero-forcing, a near-optimal power control algorithm is developed that is considerably simpler than exact max–min power control. An alternative to cell-free systems is small-cell operation in which each user is served by only one AP for which power optimization algorithms are also developed. Cell-free Massive MIMO is shown to provide five- to ten-fold improvement in 95%-likely per-user throughput over small-cell operation.
561 citations
TL;DR: A user-centric virtual cell approach to CF massive MIMO, wherein each user is served only by a limited number of access points, which requires less backhaul overhead than the CF approach, and outperforms the latter in terms of achievable rate-per-user.
Abstract: Recently, the so-called cell-free (CF) massive MIMO architecture has been introduced, wherein a very large number of distributed access points simultaneously and jointly serve a much smaller number of mobile stations. This letter introduces a user-centric (UC) virtual cell approach to CF massive MIMO, wherein each user is served only by a limited number of access points. The UC approach requires less backhaul overhead than the CF approach, and outperforms the latter in terms of achievable rate-per-user for the vast majority of the users in the network.
353 citations
TL;DR: An analysis of the spectral efficiency of single-carrier and orthogonal-frequency-division-multiplexing (OFDM) transmission in massive MIMO systems that use one-bit ADCs is presented and it is concluded that wideband massive M IMO systems work well with one- bit ADCs.
Abstract: Analog-to-digital converters (ADCs) stand for a significant part of the total power consumption in a massive multiple-input multiple-output (MIMO) base station. One-bit ADCs are one way to reduce power consumption. This paper presents an analysis of the spectral efficiency of single-carrier and orthogonal-frequency-division-multiplexing (OFDM) transmission in massive MIMO systems that use one-bit ADCs. A closed-form achievable rate, i.e., a lower bound on capacity, is derived for a wideband system with a large number of channel taps that employ low-complexity linear channel estimation and symbol detection. Quantization results in two types of error in the symbol detection. The circularly symmetric error becomes Gaussian in massive MIMO and vanishes as the number of antennas grows. The amplitude distortion, which severely degrades the performance of OFDM, is caused by variations between symbol durations in received interference energy. As the number of channel taps grows, the amplitude distortion vanishes and OFDM has the same performance as single-carrier transmission. A main conclusion of this paper is that wideband massive MIMO systems work well with one-bit ADCs.
334 citations
TL;DR: In this paper, the authors investigated the performance of linear precoders, such as maximal-ratio transmission and zero-forcing, subject to coarse quantization and derived a closed-form approximation on the rate achievable under such quantization.
Abstract: Massive multiuser (MU) multiple-input multiple-output (MIMO) is foreseen to be one of the key technologies in fifth-generation wireless communication systems. In this paper, we investigate the problem of downlink precoding for a narrowband massive MU-MIMO system with low-resolution digital-to-analog converters (DACs) at the base station (BS). We analyze the performance of linear precoders, such as maximal-ratio transmission and zero-forcing, subject to coarse quantization. Using Bussgang’s theorem, we derive a closed-form approximation on the rate achievable under such coarse quantization. Our results reveal that the performance attainable with infinite-resolution DACs can be approached using DACs having only 3–4 bits of resolution, depending on the number of BS antennas and the number of user equipments (UEs). For the case of 1-bit DACs, we also propose novel nonlinear precoding algorithms that significantly outperform linear precoders at the cost of an increased computational complexity. Specifically, we show that nonlinear precoding incurs only a 3 dB penalty compared with the infinite-resolution case for an uncoded bit-error rate of 10−3, in a system with 128 BS antennas that uses 1-bit DACs and serves 16 single-antenna UEs. In contrast, the penalty for linear precoders is about 8 dB.
307 citations
TL;DR: In this paper, the authors investigated the application of NOMA with successive interference cancellation (SIC) in downlink multiuser multiple-input multiple-output (MIMO) cellular systems, where the total number of receive antennas at user equipment (UE) ends in a cell is more than the number of transmit antennas at the BS.
Abstract: We investigate the application of non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) in downlink multiuser multiple-input multiple-output (MIMO) cellular systems, where the total number of receive antennas at user equipment (UE) ends in a cell is more than the number of transmit antennas at the base station (BS). We first dynamically group the UE receive antennas into a number of clusters equal to or more than the number of BS transmit antennas. A single beamforming vector is then shared by all the receive antennas in a cluster. We propose a linear beamforming technique in which all the receive antennas can significantly cancel the inter-cluster interference. On the other hand, the receive antennas in each cluster are scheduled on the power domain NOMA basis with SIC at the receiver ends. For inter-cluster and intra-cluster power allocation, we provide dynamic power allocation solutions with an objective to maximizing the overall cell capacity. An extensive performance evaluation is carried out for the proposed MIMO-NOMA system and the results are compared with those for conventional orthogonal multiple access (OMA)-based MIMO systems and other existing MIMO-NOMA solutions. The numerical results quantify the capacity gain of the proposed MIMO-NOMA model over MIMO-OMA and other existing MIMO-NOMA solutions.
295 citations
TL;DR: In the past six years or so, the number of scientific articles and conference papers providing possible multiple-input, multiple-output (MIMO) antenna system solutions has noticeably increased but a wide range of publications still suffer from some major misconceptions and unclear understanding of the fundamental aspects while designing, characterizing, and evaluating such multiantenna systems.
Abstract: In the past six years or so, the number of scientific articles and conference papers providing possible multiple-input, multiple-output (MIMO) antenna system solutions has noticeably increased. Flagship conferences on antennas and propagation have recently had multiple sessions addressing MIMO antenna systems and their applications. The importance of such antenna systems lies in the magnitude of their application in current wireless devices and gadgets, and this thrust will continue because fourth-generation (4G) and the upcoming fifth-generation (5G) wireless standards rely heavily on MIMO technology. But throughout the years, and up until now, a wide range of publications still suffer from some major misconceptions and unclear understanding of the fundamental aspects while designing, characterizing, and evaluating such multiantenna systems.
263 citations
TL;DR: In this article, a two-antenna building block for forming the multiple-input multiple-output (MIMO) array in the mobile device such as the smartphone is presented, which is formed by two gap-coupled loop antennas having asymmetric mirrored (AM) structures with respect to the system ground plane of the smartphone.
Abstract: A compact two-antenna building block for forming the multiple-input multiple-output (MIMO) array in the mobile device such as the smartphone is presented. The building block has a planar structure of small size $7 \times 10$ mm2 (about $0.08\lambda \times 0.12\lambda$ ) for operating at 3.5-GHz band (3.4–3.6 GHz), which is the recently identified frequency spectrum in World Radiocommunication Conference 2015 for future broadband mobile services. The building block is formed by two gap-coupled loop antennas having asymmetrically mirrored (AM) structures with respect to the system ground plane of the smartphone. The two AM antennas show good isolation thereof and their envelope correlation coefficient is much less than 0.1 in the operating band, showing very good independence of the two antennas in their far-field radiation characteristics. By using four such building blocks, an eight-antenna MIMO array at 3.5-GHz band in the smartphone is easily implemented. The channel capacity of the eight-antenna MIMO array in an $8 \times 8$ MIMO system is calculated to be about 36 b/s/Hz with 20-dB signal-to-noise ratio. The measured channel capacity obtained using an $8 \times 8$ MIMO measurement setup is also presented, which generally agrees with the calculated results. The obtained eight-antenna MIMO array is promising for future or fifth-generation smartphone applications.
244 citations
21 May 2017
TL;DR: In this article, the authors present details and applications of a novel channel simulation software named NYUSIM, which can be used to generate realistic temporal and spatial channel responses to support realistic physical and link-layer simulations and design for fifth-generation (5G) cellular communications.
Abstract: This paper presents details and applications of a novel channel simulation software named NYUSIM, which can be used to generate realistic temporal and spatial channel responses to support realistic physical-and link-layer simulations and design for fifth-generation (5G) cellular communications. NYUSIM is built upon the statistical spatial channel model for broadband millimeter-wave (mmWave) wireless communication systems developed by researchers at New York University (NYU). The simulator is applicable for a wide range of carrier frequencies (500 MHz to 100 GHz), radio frequency (RF) bandwidths (0 to 800 MHz), antenna beamwidths (7° to 360° for azimuth and 7° to 45° for elevation), and operating scenarios (urban microcell, urban macrocell, and rural macrocell), and also incorporates multiple-input multiple-output (MIMO) antenna arrays at the transmitter and receiver. This paper also provides examples to demonstrate how to use NYUSIM for analyzing MIMO channel conditions and spectral efficiencies, which show that NYUSIM is an alternative and more realistic channel model compared to the 3rd Generation Partnership Project (3GPP) and other channel models for mmWave bands.
226 citations
TL;DR: Key features for FD-MIMO systems are presented, a summary of the major issues for the standardization and practical system design, and performance evaluations for typical FD- MIMO scenarios are presented.
Abstract: Multiple-input multiple-output (MIMO) systems with a large number of base station antennas, often called massive MIMO, have received much attention in academia and industry as a means to improve the spectral efficiency, energy efficiency, and processing complexity of next generation cellular systems. The mobile communication industry has initiated a feasibility study of massive MIMO systems to meet the increasing demand of future wireless systems. Field trials of the proof-of-concept systems have demonstrated the potential gain of the Full-Dimension MIMO (FD-MIMO), an official name for the MIMO enhancement in the 3rd generation partnership project (3GPP). 3GPP initiated standardization activity for the seamless integration of this technology into current 4G LTE systems. In this article, we provide an overview of FD-MIMO systems, with emphasis on the discussion and debate conducted on the standardization process of Release 13. We present key features for FD-MIMO systems, a summary of the major issues for the standardization and practical system design, and performance evaluations for typical FD-MIMO scenarios.
Posted Content•
TL;DR: It is shown that hybrid beamforming with a small number of radio frequency (RF) chains can asymptotically approach the performance of fully digital beamforming for a sufficiently large number of transceiver antennas due to the sparse nature of the mmWave channels.
Abstract: Hybrid analog and digital beamforming is a promising candidate for large-scale mmWave MIMO systems because of its ability to significantly reduce the hardware complexity of the conventional fully-digital beamforming schemes while being capable of approaching the performance of fully-digital schemes. Most of the prior work on hybrid beamforming considers narrowband channels. However, broadband systems such as mmWave systems are frequency-selective. In broadband systems, it is desirable to design common analog beamformer for the entire band while employing different digital beamformers in different frequency sub-bands. This paper considers hybrid beamforming design for systems with OFDM modulation. First, for a SU-MIMO system where the hybrid beamforming architecture is employed at both transmitter and receiver, we show that hybrid beamforming with a small number of RF chains can asymptotically approach the performance of fully-digital beamforming for a sufficiently large number of transceiver antennas due to the sparse nature of the mmWave channels. For systems with a practical number of antennas, we then propose a unified heuristic design for two different hybrid beamforming structures, the fully-connected and the partially-connected structures, to maximize the overall spectral efficiency of a mmWave MIMO system. Numerical results are provided to show that the proposed algorithm outperforms the existing hybrid beamforming methods and for the fully-connected architecture the proposed algorithm can achieve spectral efficiency very close to that of the optimal fully-digital beamforming but with much fewer RF chains. Second, for the MU-MISO case, we propose a heuristic hybrid percoding design to maximize the weighted sum rate in the downlink and show numerically that the proposed algorithm with practical number of RF chains can already approach the performance of fully-digital beamforming.
TL;DR: This paper investigates the channel behaviors of massive MIMO at a mmWave frequency band around 26 GHz and makes the extensive ray-tracing simulations with 1024 antenna elements in the same indoor scenario, and gets insights into the variation tendency of mean delay and the RMS delay with different array elements.
Abstract: The millimeter wave (mmWave) communications and massive multiple-input multiple-output (MIMO) are both widely considered to be the candidate technologies for the fifth generation mobile communication system. It is thus a good idea to combine these two technologies to achieve a better performance for large capacity and high data-rate transmission. However, one of the fundamental challenges is the characterization of mmWave massive MIMO channel. Most of the previous investigations in mmWave channel only focus on single-input single-output links or MIMO links, whereas the research of massive MIMO channels mainly focus on a frequency band below 6 GHz. This paper investigates the channel behaviors of massive MIMO at a mmWave frequency band around 26 GHz. An indoor mmWave massive MIMO channel measurement campaign with 64 and 128 array elements is conducted, based on which, path loss, shadow fading, root-mean-square (RMS) delay spread, and coherence bandwidth are extracted. Then, by using our developed ray-tracing simulator calibrated by the measurement data, we make the extensive ray-tracing simulations with 1024 antenna elements in the same indoor scenario, and get insights into the variation tendency of mean delay and the RMS delay with different array elements. It is observed that the measurement and the ray-tracing-based simulation results have reached a good agreement.
TL;DR: New massive MIMO propagation properties, such as spherical wavefront, cluster birth-death, and non-stationarity over the antenna array, are validated for the four mmWave bands by investigating the variations of channel parameters.
Abstract: Most millimeter wave (mmWave) channel measurements are conducted with different configurations, which may have large impacts on propagation channel characteristics. In addition, the comparison of different mmWave bands is scarce. Moreover, mmWave massive multiple-input multiple-output (MIMO) channel measurements are absent, and new propagation properties caused by large antenna arrays have rarely been studied yet. In this paper, we carry out mmWave massive MIMO channel measurements at 11-, 16-, 28-, and 38-GHz bands in indoor environments. The space-alternating generalized expectation-maximization algorithm is applied to process the measurement data. Important statistical properties, such as average power delay profile, power azimuth profile, power elevation profile, root mean square delay spread, azimuth angular spread, elevation angular spread, and their cumulative distribution functions and correlation properties, are obtained and compared for different bands. New massive MIMO propagation properties, such as spherical wavefront, cluster birth-death, and non-stationarity over the antenna array, are validated for the four mmWave bands by investigating the variations of channel parameters. Two channel models are used to verify the measurements. The results indicate that massive MIMO effects should be fully characterized for mmWave massive MIMO systems.
TL;DR: In this article, the authors considered the downlink of a cell-free massive MIMO network, where numerous distributed access points (APs) serve a smaller number of users under time division duplex operation.
Abstract: We consider the downlink of a cell-free massive multiple-input multiple-output (MIMO) network, where numerous distributed access points (APs) serve a smaller number of users under time division duplex operation. An important issue in deploying cell-free networks is high power consumption, which is proportional to the number of APs. This issue has raised the question as to their suitability for green communications in terms of the total energy efficiency (bits/Joule). To tackle this, we develop a novel low-complexity power control technique with zero-forcing precoding design to maximize the energy efficiency of cell-free massive MIMO considering the Backhaul power consumption and the imperfect channel state information.
TL;DR: A new, highly reconfigurable system architecture for 5G cellular user equipment, namely distributed phased arrays based MIMO (DPA-MIMO) is proposed and the link budget calculation and data throughput numerical results are presented for the evaluation of the proposed architecture.
Abstract: Research and development on the next generation wireless systems, namely 5G, has experienced explosive growth in recent years. In the physical layer, the massive multiple-input-multiple-output (MIMO) technique and the use of high GHz frequency bands are two promising trends for adoption. Millimeter-wave (mmWave) bands, such as 28, 38, 64, and 71 GHz, which were previously considered not suitable for commercial cellular networks, will play an important role in 5G. Currently, most 5G research deals with the algorithms and implementations of modulation and coding schemes, new spatial signal processing technologies, new spectrum opportunities, channel modeling, 5G proof of concept systems, and other system-level enabling technologies. In this paper, we first investigate the contemporary wireless user equipment (UE) hardware design, and unveil the critical 5G UE hardware design constraints on circuits and systems. On top of the said investigation and design tradeoff analysis, a new, highly reconfigurable system architecture for 5G cellular user equipment, namely distributed phased arrays based MIMO (DPA-MIMO) is proposed. Finally, the link budget calculation and data throughput numerical results are presented for the evaluation of the proposed architecture.
TL;DR: This paper proposes an angle domain hybrid precoding and channel tracking method by exploring the spatial features of the mm-wave massive MIMO channel and results are provided to corroborate the studies.
Abstract: The millimeter-wave (mm-wave) massive multiple-input multiple-output (MIMO) system has gained much attention for its considerable improvement in system throughput. However, the cost of complex hardware, e.g., radio frequency (RF) chains, hinders it from practical deployment. In this paper, we propose an angle domain hybrid precoding and channel tracking method by exploring the spatial features of the mm-wave massive MIMO channel. The number of the effective spatial beams, or equivalently the RF chains, is enormously decreased via the operation of spatial rotation . The users are then scheduled by the angle division multiple access scheme, which groups users according to their direction of arrivals (DOAs). Meanwhile, a channel tracking method is designed for the subsequent data transmission through a small number of pilot symbols. Specifically, the channel information is divided into the DOA information and the gain information, where the DOA information is tracked by a modified unscented Kalman filter and the gain information is estimated from beam training. Numerical results are provided to corroborate our studies.
TL;DR: In this paper, the authors provide a comprehensive overview of the various methodologies used to approach the aforementioned joint optimization task in the downlink of multiuser MIMO communication systems.
Abstract: Remarkable research activities and major advances have been occurred over the past decade in multiuser multiple-input multiple-output (MU-MIMO) systems. Several transmission technologies and precoding techniques have been developed in order to exploit the spatial dimension so that simultaneous transmission of independent data streams reuse the same radio resources. The achievable performance of such techniques heavily depends on the channel characteristics of the selected users, the amount of channel knowledge, and how efficiently interference is mitigated. In systems where the total number of receivers is larger than the number of total transmit antennas, user selection becomes a key approach to benefit from multiuser diversity and achieve full multiplexing gain. The overall performance of MU-MIMO systems is a complex joint multi-objective optimization problem since many variables and parameters have to be optimized, including the number of users, the number of antennas, spatial signaling, rate and power allocation, and transmission technique. The objective of this literature survey is to provide a comprehensive overview of the various methodologies used to approach the aforementioned joint optimization task in the downlink of MU-MIMO communication systems.
TL;DR: The most promising lines of research from the recent literature in common directions for the 5G project are highlighted, which include spatial multiplexing using massive multi-user multiple-input multiple-output (MIMO) techniques with millimetre-waves (mm-waves) in small cell geometries.
Abstract: The exponential increase in mobile data traffic is considered to be a critical driver towards the new era, or 5G, of mobile wireless networks. 5G will require a paradigm shift that includes very high carrier frequency spectra with massive bandwidths, extreme base station densities, and unprecedented numbers of antennas to support the enormous increase in the volume of traffic. This paper discusses several design choices, features, and technical challenges that illustrate potential research topics and challenges for the future generation of mobile networks. This article does not provide a final solution but highlights the most promising lines of research from the recent literature in common directions for the 5G project. The potential physical layer technologies that are considered for future wireless communications include spatial multiplexing using massive multi-user multiple-input multiple-output (MIMO) techniques with millimetre-waves (mm-waves) in small cell geometries. These technologies are discussed in detail along with the areas for future research.
TL;DR: In this paper, a framework for designing a massive multiple-input multiple-output (MIMO) testbed by investigating hardware (HW) and system-level requirements, such as processing complexity, duplexing mode, and frame structure, is proposed.
Abstract: This paper sets up a framework for designing a massive multiple-input multiple-output (MIMO) testbed by investigating hardware (HW) and system-level requirements, such as processing complexity, duplexing mode, and frame structure. Taking these into account, a generic system and processing partitioning is proposed, which allows flexible scaling and processing distribution onto a multitude of physically separated devices. Based on the given HW constraints such as maximum number of links and maximum throughput for peer-to-peer interconnections combined with processing capabilities, the framework allows to evaluate modular HW components. To verify our design approach, we present the Lund University Massive MIMO testbed, which constitutes the first reconfigurable real-time HW platform for prototyping massive MIMO. Utilizing up to 100 base station antennas and more than 50 field programmable gate array, up to 12 user equipment are served on the same time/frequency resource using an LTE-like orthogonal frequency division multiplexing time-division duplex-based transmission scheme. Proof-of-concept tests with this system show that massive MIMO can simultaneously serve a multitude of users in a static indoor and static outdoor environment utilizing the same time/frequency resource.
TL;DR: A scalable and flexible massive MIMO precoding scheme by exploiting the null-space of user signals is proposed, capable to effectively alleviate the interference to victim users and support high QoS as well as spectral efficiency.
Abstract: Scalability and flexibility are widely considered as two major design goals for 5G networks. Aiming at these goals, this article first identifies a promising architecture based on the heterogeneous cloud radio access network (H-CRAN), reviews the challenges in MIMO precoding for H-CRAN, and then proposes a scalable and flexible massive MIMO precoding scheme by exploiting the null-space of user signals. Specifically, the system can accomplish effective radio resource management and flexible spatial coordination by distinguishing the intended and victim users' CSI, and avoid the interference by precoding within the null-space for the CSI of victim users. Simulation results indicate that the proposed scheme is capable to effectively alleviate the interference to victim users and support high QoS as well as spectral efficiency.
TL;DR: A low-complexity hybrid precoding and combining design for the millimeter-wave MU-MIMO transmission, applicable to both fully connected and sub-connected structures, shows that the proposed techniques offer an enhanced performance- complexity tradeoff compared with both existing hybrid schemes and fully digital schemes.
Abstract: In this letter, we propose a low-complexity hybrid precoding and combining design for the millimeter-wave MU-MIMO transmission, applicable to both fully connected and sub-connected structures Analog precoding and combining schemes are first designed, where a joint approach, a decoupled approach, and a sub-optimal approach are proposed to harvest the array gain Virtual path selection is performed to maximize the channel gain of the analog effective channel Then, based on the effective channel, a low-dimensional zero-forcing precoding is applied in the baseband to manage the interference The simulation results show that the proposed techniques offer an enhanced performance-complexity tradeoff compared with both existing hybrid schemes and fully digital schemes
TL;DR: A novel hybrid channel estimation is proposed by separately estimating the angle information and the gain matrix, which could significantly save the training overhead and substantially improve the channel estimation accuracy compared with the conventional beamspace approach.
Abstract: This paper presents a new view of multi-user (MU) hybrid massive multiple-input and multiple-output (MIMO) systems from array signal processing perspective. We first show that the instantaneous channel vectors corresponding to different users are asymptotically orthogonal if the angles of arrival of users are different. We then decompose the channel matrix into an angle domain basis matrix and a gain matrix. The former can be formulated by steering vectors and the latter has the same size as the number of RF chains, which perfectly matches the structure of hybrid precoding. A novel hybrid channel estimation is proposed by separately estimating the angle information and the gain matrix, which could significantly save the training overhead and substantially improve the channel estimation accuracy compared with the conventional beamspace approach. Moreover, with the aid of the angle domain matrix, the MU massive MIMO system can be viewed as a type of non-orthogonal angle division multiple access to simultaneously serve multiple users at the same frequency band. Finally, the performance of the proposed scheme is validated by computer simulation results.
TL;DR: It is shown that, compared with conventional massive MIMO systems, the performance loss in one-bit massive M IMO systems can be compensated for by deploying approximately 2.5 times more antennas at the BS.
Abstract: In this letter, we investigate the downlink performance of massive multiple-input multiple-output (MIMO) systems where the base station is equipped with one-bit analog-to-digital/digital-to-analog converters (ADC/DACs) We assume that the base station employs the linear minimum mean-squared-error channel estimator and treats the channel estimate as the true channel to precode the data symbols We derive an expression for the downlink achievable rate for matched-filter precoding A detailed analysis of the resulting power efficiency is pursued using our expression of the achievable rate Numerical results are presented to verify our analysis In particular, it is shown that, compared with conventional massive MIMO systems, the performance loss in one-bit massive MIMO systems can be compensated for by deploying approximately 25 times more antennas at the BS
TL;DR: This paper proposes a novel decentralized baseband processing architecture that alleviates bottlenecks by partitioning the BS antenna array into clusters, each associated with independent radio-frequency chains, analog and digital modulation circuitry, and computing hardware.
Abstract: Achieving high spectral efficiency in realistic massive multi-user (MU) multiple-input multiple-output (MIMO) wireless systems requires computationally complex algorithms for data detection in the uplink (users transmit to base-station) and beamforming in the downlink (base-station transmits to user). Most existing algorithms are designed to be executed on centralized computing hardware at the base-station (BS), which results in prohibitive complexity for systems with hundreds or thousands of antennas and generates raw baseband data rates that exceed the limits of current interconnect technology and chip I/O interfaces. This paper proposes a novel decentralized baseband processing architecture that alleviates these bottlenecks by partitioning the BS antenna array into clusters, each associated with independent radio-frequency chains, analog and digital modulation circuitry, and computing hardware. For this architecture, we develop novel decentralized data detection and beamforming algorithms that only access local channel-state information and require low communication bandwidth among the clusters. We study the associated tradeoffs between error-rate performance, computational complexity, and interconnect bandwidth, and we demonstrate the scalability of our solutions for massive MU-MIMO systems with thousands of BS antennas using reference implementations on a graphics processing unit (GPU) cluster.
TL;DR: In this paper, an energy harvesting scheme for a multi-user multiple-input-multiple-output (MIMO) secrecy channel with artificial noise (AN) transmission is investigated, where the transmit beamforming matrix, the AN covariance matrix, and the power splitting ratio are jointly optimized to minimize the transmit power under the target secrecy rate, the total transmit power, and harvested energy constraints.
Abstract: In this paper, an energy harvesting scheme for a multi-user multiple-input-multiple-output secrecy channel with artificial noise (AN) transmission is investigated. Joint optimization of the transmit beamforming matrix, the AN covariance matrix, and the power splitting ratio is conducted to minimize the transmit power under the target secrecy rate, the total transmit power, and the harvested energy constraints. The original problem is shown to be non-convex, which is tackled by a two-layer decomposition approach. The inner layer problem is solved through semi-definite relaxation, and the outer problem, on the other hand, is shown to be a single-variable optimization that can be solved by 1-D line search. To reduce computational complexity, a sequential parametric convex approximation method is proposed to find a near-optimal solution. This paper is then extended to the imperfect channel state information case with norm-bounded channel errors. Furthermore, tightness of the relaxation for the proposed schemes is validated by showing that the optimal solution of the relaxed problem is rank-one. Simulation results demonstrate that the proposed SPCA method achieves the same performance as the scheme based on 1-D but with much lower complexity.
31 Jul 2017
TL;DR: This paper focuses on the millimeter-wave multi-user multiple-input-multiple-output (mmWave MU-MIMO) systems and proposes a low-complexity hybrid precoding and combining design, which is applicable to both fully- connected structures and sub-connected structures.
Abstract: In this paper, we focus on the millimeter-wave multi-user multiple-input-multiple-output (mmWave MU-MIMO) systems and propose a low-complexity hybrid precoding and combining design, which is applicable to both fully-connected structures and sub-connected structures. Based on the channel knowledge of each user, the analog combiner for each user is independently designed based on the singular value decomposition (SVD), while the analog precoder is obtained by the conjugate transposition to maximize the effective channel gain. Then, with the resulting effective analog channel, low-dimensional baseband precoders can be efficiently applied. The proposed scheme requires no optimization techniques or any complicated iterative algorithms, while the numerical results show that it can approach the performance of fully digital schemes and even achieve a better performance in some scenarios. It is also observed that sub-connected structures can achieve a much higher power efficiency compared to fully-connected structures and are therefore promising for the future green communication systems.
TL;DR: This paper investigates the problem of user association in a heterogeneous network with massive MIMO and small cells, where the macro base station is equipped with a massive M IMO, and the picocell BSs are equipped with regular MIMOs.
Abstract: Massive multiple-input–multiple-output (MIMO) and small cell are both recognized as key technologies for the future fifth-generation wireless systems. In this paper, we investigate the problem of user association in a heterogeneous network (HetNet) with massive MIMO and small cells, where the macro base station (BS) is equipped with a massive MIMO, and the picocell BSs are equipped with regular MIMOs. We first develop centralized user association algorithms with proven optimality, considering various objectives such as rate maximization, proportional fairness, and joint user association and resource allocation. We then develop a repeated game model, which leads to distributed user association algorithms with proven convergence to the Nash equilibrium. We demonstrate the efficacy of these optimal schemes by comparing with several greedy algorithms through simulations.
TL;DR: 3-D MIMO channel which fully utilizes the elevation domain does improve capacity and also enhance the contributing eigenvalue number, and in reality, O2I is the most beneficial scenario, then followed by UMi and UMa scenarios.
Abstract: By taking advantage of the elevation domain, three-dimensional (3-D) multiple input and multiple output (MIMO) with massive antenna elements is considered as a promising and practical technique for the fifth Generation mobile communication system. So far, 3-D MIMO is mostly studied by simulation and a few field trials have been launched recently. It still remains unknown how much does the 3-D MIMO meet our expectations in versatile scenarios. In this paper, we answer this based on measurements with $56\times 32$ antenna elements at 3.5 GHz with 100-MHz bandwidth in three typical deployment scenarios, including outdoor to indoor (O2I), urban microcell (UMi), and urban macrocell (UMa). Each scenario contains two different site locations and 2–5 test routes under the same configuration. Based on the measured data, both elevation and azimuth angles are extracted and their stochastic behaviors are investigated. Then, we reconstruct two-dimensional and 3-D MIMO channels based on the measured data, and compare the capacity and eigenvalues distribution. It is observed that 3-D MIMO channel which fully utilizes the elevation domain does improve capacity and also enhance the contributing eigenvalue number. However, this gain varies from scenario to scenario in reality, O2I is the most beneficial scenario, then followed by UMi and UMa scenarios. More results of multiuser capacity varying with the scenario, antenna number and user number can provide the experimental insights for the efficient utilization of 3-D MIMO in future.
TL;DR: This paper designs VLSI architectures that enable efficient 1-bit precoding for massive MU-MIMO systems, in which hundreds of antennas serve tens of user equipments, and presents corresponding field-programmable gate array (FPGA) reference implementations to demonstrate that 1- bit precoding enables reliable and high-rate downlink data transmission in practical systems.
Abstract: Massive multi-user (MU) multiple-input multiple-output (MIMO) will be a core technology in fifth-generation (5G) wireless systems as it offers significant improvements in spectral efficiency compared to existing multi-antenna technologies. The presence of hundreds of antenna elements at the base station (BS), however, results in excessively high hardware costs and power consumption, and requires high interconnect throughput between the baseband-processing unit and the radio unit. Massive MU-MIMO that uses low-resolution analog-to-digital and digital-to-analog converters (DACs) has the potential to address all these issues. In this paper, we focus on downlink precoding for massive MU-MIMO systems with 1-bit DACs at the BS. The objective is to design precoders that simultaneously mitigate MU interference and quantization artifacts. We propose two nonlinear 1-bit precoding algorithms and corresponding very large-scale integration (VLSI) designs. Our algorithms rely on biconvex relaxation, which enables the design of efficient 1-bit precoding algorithms that achieve superior error-rate performance compared with that of linear precoding algorithms followed by quantization. To showcase the efficacy of our algorithms, we design VLSI architectures that enable efficient 1-bit precoding for massive MU-MIMO systems, in which hundreds of antennas serve tens of user equipments. We present corresponding field-programmable gate array (FPGA) reference implementations to demonstrate that 1-bit precoding enables reliable and high-rate downlink data transmission in practical systems.