Multiple-input Multiple-output Transmission Research Articles

SYMMeTRy: Exploiting MIMO Self-Similarity for Under-Determined Modulation Recognition

Modulation recognition (modrec) seeks to identify the modulation of a transmitter from coresponding spectrum scans. It is an essential functional component of future spectrum sensing with critical applications in dynamic spectrum access and spectrum enforcement. While predominantly studied in single-input single-output (SISO) systems, practical modrec for multiple-input multiple-output (MIMO) communications requires more research attention. Existing MIMO modrec impose stringent requirements of fully- or over-determined sensing front-end, i.e. the number of sensor antennas should exceed that at the transmitter. This poses a prohibitive sensor cost even for simple 2x2 MIMO systems and will severely hamper progress in flexible spectrum access. We design a MIMO modrec framework that enables efficient and cost-effective modulation classification for under-determined settings involving fewer sensor antennas than those used for transmission. Our key idea is to exploit the inherent multi-scale self-similarity of MIMO modulation IQ constellations, which persists in under-determined settings. Our framework, called SYMMeTRy (Self-similaritY for MIMO ModulaTion Recognition), designs domain-aware classification features with high discriminative potential by summarizing regularities of symbol co-location in the MIMO constellation. To this end, we summarize the fractal geometry of observed samples to extract discriminative features for supervised MIMO modrec. We evaluate SYMMeTRy in a realistic simulation and in a small-scale MIMO testbed. We demonstrate that it maintains high and consistent performance across various noise regimes, channel fading conditions and with increasing MIMO transmitter complexity. Our efforts highlight SYMMeTRy's high potential to enable efficient and practical MIMO modrec in spectrum sensing infrastructures with mixed-complexity sensors.

Cell Partitioning Antenna System Performance in Multi-User Scenarios for mmWave Communications

Fixed-beam, high-gain antenna systems can be used for a finer partitioning of the currently used cell-sectoring. This partitioning has the benefit of reducing the number of users seen per antenna beam, which reduces interference. Furthermore, the high antenna gain allows for a high effective isotropic radiated power while keeping the transmit power low. In this paper, we study the performance of such a fixed-beam, high gain antenna system design for millimeter-wave mobile communications. The antenna system is designed to keep the inter-sector interference in a multi-site scenario low. The performance is analyzed for single- and multi-user environments. In single-input single-output mode, the 50th percentile of the signal-to-interference-plus-noise ratio lies between 12.5 dB to 39.7 dB if 3 to 0 interferers are present, respectively. For multiple-input multiple-output transmission using zero-forcing, the signal-to-interference-plus-noise ratio increases and the 50th percentile ranges from 36.1 dB to 43.3 dB if 3 to 0 interferes are present, respectively. By using maximum ratio transmission, the best performance is achieved with no interferers present, while a plunge in performance is observed with interferers. Furthermore, the study revealed that the narrow beam antenna system can also provide a clear signal separation for small spatial separations. In the given example, the signal-to-interference-plus-noise ratio is larger than 32.1 dB with 11 active antenna elements, where 2.8 meters separate the users. Hence, the paper shows that the cell-partitioning antenna systems provide coverage in the desired area while keeping the inter-sector interference low, and the considered transmission techniques can be used for situation optimized mobile communication links.

Parallel Complex Quadrature Spatial Modulation

In this paper, we propose a new multiple-input multiple-output (MIMO) transmission scheme, called parallel complex quadrature spatial modulation (PCQSM). The proposed technique is based on the complex quadrature spatial modulation (CQSM) to further increase the spectral efficiency of the communication system. CQSM transmits two different complex symbols at each channel use. In contrast with CQSM, the new transmission scheme splits the transmit antennas into groups, and modulates the two signal symbols using the conventional CQSM before transmission. Based on the selected modulation order and the number of possible groups that can be realized, the incoming bits modulate the two signal symbols and the indices of the transmit antennas in each group. We demonstrated that while the complexity and performance of the proposed scheme is the same as that of CQSM, the number of required transmit antennas is significantly reduced. The proposed PCQSM achieves such a benefit without requiring any additional radio frequency (RF) chains. The results obtained from Monte Carlo simulation showed that at a Bit Error Rate (BER) of 10−4, the performance of the PCQSM with two antenna groups closely matches that of CQSM, and outperformed quadrature spatial modulation (QSM) and parallel quadrature spatial modulation (PQSM) by over 0.7 dB. As the number of antenna groups increased to 4, the BER performance of PCQSM with reduced number of transmit antenna and modulation order matches that of QSM. The BER of the proposed scheme using maximum likelihood (ML) receiver is also analyzed theoretically and compared with the BER obtained via simulations.

Low Complexity Adaptation for Reconfigurable Intelligent Surface-Based MIMO Systems

Reconfigurable intelligent surface (RIS)-based transmission technology offers a promising solution to enhance wireless communication performance cost-effectively through properly adjusting the parameters of a large number of passive reflecting elements. This letter proposes a cosine similarity theorem-based low-complexity algorithm for adapting the phase shifts of an RIS that assists a multiple-input multiple-output (MIMO) transmission system. A semi-analytical probabilistic approach is developed to derive the theoretical average bit error probability (ABEP) of the system. Furthermore, the validity of the theoretical analysis is supported through extensive computer simulations.

Throughput Scaling of Covert Communication Over Wireless Adhoc Networks

We consider the problem of covert communication over wireless adhoc networks in which (roughly) $n$ legitimate nodes (LNs) and $n^{\kappa }$ for $\kappa > 0$ non-communicating warden nodes (WNs) are randomly distributed in a square of unit area. Each legitimate source wants to communicate with its intended destination node while ensuring that every WN is unable to detect the presence of the communication. In this scenario, we study the throughput scaling law. Due to the covert communication constraint, the transmit powers are necessarily limited. Under this condition, we introduce a preservation region around each WN. This region serves to prevent transmission from the LNs and to increase the transmit power of the LNs outside the preservation regions. For the achievability results, multi-hop (MH), hierarchical cooperation (HC), and hybrid HC-MH schemes are utilized with some appropriate modifications. In the proposed MH and hybrid schemes, because the preservation regions may impede communication along direct data paths, the data paths are suitably modified by taking a detour around each preservation region. To avoid the concentration of detours resulting extra relaying burdens, we distribute the detours evenly over a wide region. In the proposed HC scheme, we control the symbol power and the scheduling of distributed multiple-input multiple-output transmission. We also present upper bounds on the throughput scaling under the assumption that every active LN consumes the same average transmit power over the time period in which the WNs observe the channel outputs. For $0 , these upper bounds match with the achievable throughput scalings.

Energy Efficiency Optimization in Massive MIMO Secure Multicast Transmission.

Herein, we focus on energy efficiency optimization for massive multiple-input multiple-output (MIMO) downlink secure multicast transmission exploiting statistical channel state information (CSI). Privacy engineering in the field of communication is a hot issue under study. The common signal transmitted by the base station is multicast transmitted to multiple legitimate user terminals in our system, but an eavesdropper might eavesdrop this signal. To achieve the energy efficiency utility–privacy trade-off of multicast transmission, we set up the problem of maximizing the energy efficiency which is defined as the ratio of the secure transmit rate to the power consumption. To simplify the formulated nonconvex problem, we use a lower bound of the secure multicast rate as the molecule of the design objective. We then obtain the eigenvector of the optimal transmit covariance matrix into a closed-form, simplifying the matrix-valued multicast transmission strategy problem into a power allocation problem in the beam domain. By utilizing the Minorize-Maximize method, an iterative algorithm is proposed to decompose the secure energy efficiency optimization problem into a sequence of iterative fractional programming subproblems. By using Dinkelbach’s transform, each subproblem becomes an iterative problem with the concave objective function, and it can be solved by classical convex optimization. We guarantee the convergence of the two-level iterative algorithm that we propose. Besides, we reduce the computational complexity of the algorithm by substituting the design objective with its deterministic equivalent. The numerical results show that the approach we propose performs well compared with the conventional methods.

Power Efficiency Model for MIMO Transmitters Including Memory Polynomial Digital Predistortion

Multiple-input multiple-output (MIMO) beamforming array gain can make multi-antenna transmitters (TXs) more power efficient. However, these MIMO TXs require more complex digital predistortion (DPD). In this brief, analytical expressions are derived for the power consumption of both MIMO power amplifier (PA) arrays and their respective DPD, taking into account the effects of precoding on PA output power and peak-to-average power ratio (PAPR). It is shown that for complex DPD algorithms such as cross-over DPD (CO-DPD) in combination with wide bandwidths, the overall DPD power consumption can exceed the overall PA power consumption already for scenarios with more than two antennas.

Differential optical spatial modulation with pulse position modulation over atmospheric turbulence

Optical spatial modulation (OSM), a recent optical multiple-input multiple-output transmission scheme in wireless optical communication, has aroused great research interests. OSM scheme requires accurate channel state information (CSI) during transmitter and receiver sides, but it is difficult to accurately estimate CSI in OSM scheme. Therefore, a scheme named differential optical spatial modulation scheme with pulse position modulation (DOSM-PPM) based on the space-time mapping block of orthogonal design is proposed in order to completely avoid CSI estimation. The bit error rate (BER) performance of DOSM-PPM is analyzed under log-normal turbulent channel model and simulated using Monte Carlo method. The results show that the transmission rate of DOSM-PPM is improved effectively. Meantime, the proposed DOSM-PPM scheme outperforms DOSM scheme with spatial pulse amplitude modulation by 1 dB at 1 × 10 − 3 BER with the same spectrum efficiency.

Precoded Generalized Spatial Modulation for Downlink MIMO Transmissions in Beyond 5G Networks

The design of multiple input multiple output (MIMO) schemes capable of achieving both high spectral and energy efficiency constitutes a challenge for next-generation wireless networks. MIMO schemes based on generalized spatial modulations (GSM) have been widely considered as a powerful technique to achieve that purpose. In this paper, a multi-user (MU) GSM MIMO system is proposed, which relies on the transmission of precoded symbols from a base station to multiple receivers. The precoder’s design is focused on the removal of the interference between users and allows the application of single-user GSM detection at the receivers, which is accomplished using a low-complexity iterative algorithm. Link level and system level simulations of a cloud radio access network (C-RAN) comprising several radio remote units (RRUs) were run in order to evaluate the performance of the proposed solution. Simulation results show that the proposed GSM MU-MIMO approach can exploit efficiently a large number of antennas deployed at the transmitter. Moreover, it can also provide large gains when compared to conventional MU-MIMO schemes with identical spectral efficiencies. In fact, regarding the simulated C-RAN scenario with perfect channel estimation, system level results showed potential gains of up to 155% and 139% in throughput and coverage, respectively, compared to traditional cellular networks. The introduction of imperfect channel estimation reduces the throughput gain to 125%.

Full-Azimuth Beam Steering MIMO Antenna Arranged in a Daisy Chain Array Structure.

This paper presents a multiple-input, multiple-output (MIMO) antenna system with the ability to perform full-azimuth beam steering, and with the aim of realizing greater than 20 Gbps vehicular communications. The MIMO antenna described in this paper comprises 64 elements arranged in a daisy chain array structure, where 32 subarrays are formed by pairing elements in each subarray; the antenna yields 32 independent subchannels for MIMO transmission, and covers all communication targets regardless of their position relative to the array. Analytical results reveal that the proposed antenna system can provide a channel capacity of more than 200 bits/s/Hz at a signal-to-noise power ratio (SNR) of 30 dB over the whole azimuth, which is equivalent to 20 Gbps for a bandwidth of 100 MHz. This remarkably high channel capacity is shown to be due to two significant factors; the improved directivity created by the optimum in-phase excitation and the low correlation between the subarrays due to the orthogonal alignment of the array with respect to the incident waves. Over-the-air (OTA) experiments confirm the increase in channel capacity; the proposed antenna can maintain a constant transmission rate over all azimuth angles.

Networked Optical Massive MIMO Communications

The low cost and versatility of optical devices make it possible to pack a large number of optical transceivers into arrays and exploit massive multiple-input multiple-output (MIMO) transmission in optical wireless communications. Nevertheless, optical massive MIMO presents several distinct challenges such as, the line-of-sight propagation and intensity modulation, incompatible with existing radio frequency massive MIMO techniques. This paper presents a networked optical massive MIMO system that consists of multiple base stations (BSs), each equipped with a transmit lens and an optical transmitter array, cooperatively serving a number of user terminals (UTs), each equipped with a receive lens and a photodetector array. We establish the optical massive MIMO channel model, analyze its asymptotic behavior, and evaluate the potential of networked optical massive MIMO on system throughput improvement. To achieve high throughput, we propose optical beam division multiple access (BDMA) transmission schemes under the total and per transmitter power constraints with the asymptotic optimality. Our results show that the system sum rate increases proportionally to the number of BSs and UTs using the optical BDMA transmission. Further numerical results show that the proposed optical massive MIMO system along with the optical BDMA transmission is able to achieve high throughput with low complexity.

MIMO Detection for Reconfigurable Intelligent Surface-Assisted Millimeter Wave Systems

Millimeter wave (mmWave) band, or high frequencies such as THz, has large undeveloped band of spectrum. However, wireless channels over the mmWave band usually have one or two paths only due to the severe attenuation. The channel property restricts its development in the multiple-input multiple-output (MIMO) system, which can improve throughput by increasing the spectral efficiency. Recent development in reconfigurable intelligent surface (RIS) provides new opportunities to mmWave communications. In this study, we propose a mmWave system, which used low-precision analog-to-digital converters (ADCs), with the aid of several RIS arrays. Moreover, each RIS array has many reflectors with discrete phase shift. By employing the linear spatial processing, these arrays form a synthetic channel with increased spatial diversity and power gain, which can support MIMO transmission. We develop a MIMO detector according to the characteristics of the synthetic channel. RIS arrays can provide spatial diversity to support MIMO transmission, however, different number, antenna configuration, and deployment of RIS arrays affect the bit error rate (BER) performance. We present state evolution (SE) equations to evaluate the BER of the proposed MIMO detector in the different cases. The BER performance of indoor system is studied extensively through leveraging by the SE equations. We reveal numerous insights about the RIS effects and discuss the appropriate system settings. In addition, our results demonstrate that the low-cost hardware, such as the 3-bit ADCs of the receiver side and the 2-bit uniform discrete phase shift of the RIS arrays, only moderately degenerate the system performance.

Network Massive MIMO Transmission Over Millimeter-Wave and Terahertz Bands: Mobility Enhancement and Blockage Mitigation

Mobility and blockage are two critical challenges in wireless transmission over millimeter-wave (mmWave) and Terahertz (THz) bands. In this paper, we investigate network massive multiple-input multiple-output (MIMO) transmission for mmWave/THz downlink in the presence of mobility and blockage. Considering the mmWave/THz propagation characteristics, we first propose to apply per-beam synchronization for network massive MIMO to mitigate the channel Doppler and delay dispersion effects. Accordingly, we establish a transmission model. We then investigate network massive MIMO downlink transmission strategies with only the statistical channel state information (CSI) available at the base stations (BSs), formulating the strategy design problem as an optimization problem to maximize the network sum-rate. We show that the beam domain is favorable to perform transmission, and demonstrate that BSs can work individually when sending signals to user terminals. Based on these insights, the network massive MIMO precoding design is reduced to a network sum-rate maximization problem with respect to beam domain power allocation. By exploiting the sequential optimization method and random matrix theory, an iterative algorithm with guaranteed convergence performance is further proposed for beam domain power allocation. Numerical results reveal that the proposed network massive MIMO transmission approach with the statistical CSI can effectively alleviate the blockage effects and provide mobility enhancement over mmWave and THz bands.

Experimental investigation of beam-steering applied to 2 × 2 MIMO system with single receiving RF chain and time-modulated antenna array

AbstractMultiple antennas and multiple radio frequency (RF) chains in both the transmitter and receiver are required in conventional radio systems employing the multiple-input multiple-output (MIMO) method. This paper presents an experimental investigation of a beam-steering time-modulated MIMO receiver with a single RF chain. Implementation of the receiver is based on a time-modulated antenna array (TMAA) and a software-defined radio. The sidebands generated inherently by the TMAA are utilized as virtual spatial channels with the beam-steering functionality. Performance of the system is investigated experimentally. The bit error rate and condition number of the channel matrix are examined for different radiation patterns in order to determine favorable configurations in a given multipath environment. Obtained results show a considerable impact of the beam-steering on the performance of MIMO transmission.

Generalized Code Index Modulation and Spatial Modulation for High Rate and Energy-Efficient MIMO Systems on Rayleigh Block-Fading Channel

In this article, a high data rate and energy-efficient multiple-input multiple-output transmission scheme is considered by combining two popular and rational modulation techniques: spatial modulation (SM) and code index modulation-spread spectrum (CIM-SS). Since in the considered system, called generalized CIM-SM (GCIM-SM), incoming information bits determine modulated symbols, activated transmit antenna indices as well as their corresponding spreading code indices, data bits are conveyed not only by modulated symbols but also by the indices of the active antenna and spreading codes. Hence, a GCIM-SM scheme accommodates faster data rates while spending less transmission power and possessing better error performance compared to the conventional direct sequence spread spectrum (DS-SS), SM, quadrature SM (QSM), and CIM-SS systems. The mathematical expressions of the GCIM-SM system for bit error rate, throughput, energy efficiency, and the system complexity are derived to analyze the overall system performance. Besides, it has been shown via computer simulations that the GCIM-SM system has lower transmission energy, faster data transmission rate, and better error performance than DS-SS, SM, QSM, and CIM-SS systems. Performance analysis of the considered system was performed on Rayleigh block-fading channels for quadrature amplitude modulation technique.

Estimation of Wideband Dynamic mmWave and THz Channels for 5G Systems and Beyond

Millimeter wave (mmWave) wideband channels in a multiple-input multiple-output (MIMO) transmission are described by a sparse set of impulse responses in the angle-delay, or space-time (ST), domain. These characteristics will be even more prominent in the THz band used in future systems. We consider two approaches for channel estimation: compressed-sensing (CS), exploiting the sparsity in the angular/delay domain, and low-rank (LR), exploiting the algebraic structure of channel matrix. Both approaches share several commonalities, and this paper provides for the first time i) a comparison of the two approaches, and ii) new versions of CS and LR methods that significantly improve performance in terms of mean squared error (MSE), computational complexity, and latency. We derive the asymptotic MSE bound for any estimator of the ST-MIMO multipath channels with invariant angles/delays and time-varying fading, with unknown angle/delay diversity order: the bound also accounts for the degradation introduced by sub-optimal separable channel models. We will show that in the considered scenarios both CS and LR approaches attain the bound. Our performance assessment over ideal and 3 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rd</sup> generation partnership project (3GPP) channel models, suitable for the fifth-generation (5G) and beyond of cellular networks, shows the trade-off obtained by the methods over various metrics: i) CS methods are converging faster than the LR methods, both attaining the asymptotic MSE bound; ii) the CS methods depend on the array manifold, while LR methods are independent of the array calibration; iii) CS solutions are more complex than LR solutions.

Experimental Field Trials on MU-MIMO Transmissions for High SHF Wide-Band Massive MIMO in 5G

The field trial results for massive multi-user multiple-input multiple-output (MU-MIMO) transmission at 28 GHz with 500 MHz bandwidth are reported in this paper. In this experiment, hybrid beamforming with block diagonal precoding is employed, in which channel state information is acquired by uplink sounding assuming channel reciprocity in a time division duplex system. 8-user MU-MIMO scenarios with various user distributions are considered, and the downlink transmission performance and propagation channel characteristics are evaluated. The trial results show that digital precoding improves the system performance and that over 20 Gbps total throughput can be achieved for a variety of user distributions. The performance of the precoding is evaluated in terms of eliminating inter-user interference.

Quadrature spatial modulation based multiuser MIMO transmission system

This study presents a multiuser (MU) multiple-input multiple-output (MIMO) downlink transmission scheme based on the quadrature spatial modulation (QSM) concept, which uses the indices of the non-zero entries in its transmission vector to modulate and transmit an independent sequence of bits for each user in the system. The MU interference is removed by using a matrix precoding technique based on channel state information (CSI) known as block diagonalisation (BD). The performance of the proposed scheme is compared with the conventional MU–MIMO–BD system for uncorrelated Rayleigh fading channels and correlated fading channels with imperfect CSI in the reception. Additionally, a low-complexity near maximum likelihood (ML) detection algorithm for the MU–MIMO–QSM signal's detection is proposed. For the considered cases, the proposed MU–MIMO–QSM scheme exhibits gains up to 1 dB in bit error rate performance and a reduction in detection complexity up to 93% as compared to the conventional MU–MIMO–BD scheme for the optimal ML detection. The proposed algorithm performs very near to the optimal ML detector whilst achieving a complexity reduction of up to 58%.

Novel Unmanned Aerial Vehicle-Based Line-of-Sight MIMO Configuration Independent of Transmitted Distance Using Millimeter Wave

Recently, the millimeter-wave band has been used in outdoor wireless communications to improve the frequency utilization efficiency. In this study, we propose a method to realize line-of-sight multiple-input multiple-output (LOS-MIMO) transmission independent of the transmitted distance using a two-dimensional (2-D) fixed antenna element arrangement, assuming millimeter-wave-band communication by small autonomous unmanned aerial vehicles. In conventional LOS-MIMO transmission with uniformly spaced antenna elements, the theoretical upper bound of the channel capacity is obtained, which decreases at a certain transmitted distance. Therefore, we focus on the fact that the propagation channel characteristics in pure LOS are geometrically determined by the transmitted distance, and consider the optimization of the arrangement of antenna elements. The element arrangement is fixed without using antenna selection from the viewpoint of system simplification. In addition, from the viewpoint of array size, we study the optimization corresponding to a 2-D element arrangement. The proposed method approximates the optimal arrangement from a vast number of 2-D element arrangements using a genetic algorithm. We evaluate the channel capacity characteristics of the proposed method by computer simulation and show that the characteristic degradation due to change in the transmitted distance in conventional LOS-MIMO transmission is improved. In addition, we evaluate a $4\times4$ MIMO transmission in an outdoor environment. The $4\times4$ MIMO propagation channel is also measured by an actual measurement equipment in the 66-GHz band and it is shown that the measured and calculated results agree with each other.

Joint Modulation and Beamforming for MIMO Systems With 1-b DACs

To realize multiple-input multiple-output (MIMO) with low cost and low power consumption, the use of low-resolution digital-to-analog converters (DAC) is drawing significant interest. While previous studies on low-resolution DAC MIMO have focused on optimizing precoding for massive MIMO, this approach faces the limitation that the coarse resolution at the transmitter makes it difficult to construct a transmit signal close enough to the desired one when a small scale MIMO transmitter is considered as in IoT networks. To address this problem, we propose a new transmission framework that jointly performs modulation and beamforming. With the proposed scheme, a message symbol is directly mapped into a feasible transmit vector. We also develop a channel-adaptive mapping function within the proposed framework that minimizes error probability. Simulation results show that the proposed scheme can significantly improve the error performance.