Massive Massive Multiple-input Multiple-output Base-station Research Articles

Navigating The Complexity Overcoming Mobility Obstacles in Massive MIMO Systems with MIMO Antennas.

This research investigates the synergy between Massive Multiple Input, Multiple Output (MIMO) systems and mobility challenges, with a focus on the pivotal role played by Multiple Antenna Systems (MIMO antennas). Employing a sophisticated experimental setup featuring a 3.5 GHz Massive MIMO base station equipped with 64 MIMO antennas, mobile terminals on motorized platforms, and advanced RF measurement tools, the study explores adaptive beamforming, spatial multiplexing, and diversity techniques. Results from 100 experiments, each lasting 10 minutes, reveal that adaptive beamforming dynamically improves user tracking in response to mobility-induced channel variations. Spatial multiplexing and diversity techniques enhance throughput and reliability, especially in high user mobility scenarios. The quantitative findings align with existing literature, providing practical insights for the deployment of MIMO antennas. The study addresses limitations and proposes avenues for future research, enhancing our understanding of MIMO antenna applications and contributing to the evolution of wireless communication technologies in dynamic environments.

Single-port measurement scheme: An alternative approach to system calibration for 5G massive MIMO base station conformance testing

To calibrate the test system of fifth-generation (5G) massive multiple-input multiple-output (MIMO) base station (BS), this paper proposes a promising single-port measurement scheme, which is more cost-effective and convenient than conventional scheme. The conventional scheme first requires the disconnection of the measurement equipment from the BS test system, and then uses a costly vector network analyzer (VNA) for the system calibration measurement, which is cumbersome, slow, and inconvenient. Instead, the proposed scheme can conduct the system calibration with low cost directly based on the existing measurement equipment in the original test system, i.e. no need for the extra expensive VNA. The accuracy performance of the proposed scheme is evaluated by the frequency response error measured between the proposed and the conventional schemes, e.g. with an amplitude error range of [−0.45, 0.14] dB and a phase error range of [−0.2∘, 2.5∘]. Therefore, the superiority is that the proposed single-port scheme in this paper accomplished the equivalent measurement as the conventional scheme, and further reduced the cost and inconvenience for the test industry. Finally, the reduced cost and complexity by the proposed measurement scheme is beneficial to both the industry and academic scientific world in terms of faster and more efficient testing as well as increased reproducibility of research findings.

Blocking probability of massive MIMO: What is the capacity of a massive MIMO IoT system?

In this paper, we provide a methodology to evaluate the capacity of a Massive multiple-input multiple-output (MIMO) supported Internet of Things (IoT) system in which a large number of low cost low power IoT devices transmit and receive sporadic data. Numerous IoT devices are supported by a single cell Massive MIMO base station (BS) with maximum-ratio (MR) processing. Orthogonal reference signals (RSs) or pilots are assigned randomly to all the IoT devices for channel estimation purpose. The number of simultaneously active IoT devices follows Poisson distribution. Due to the tremendous number of IoT devices, orthogonal RSs are heavily reused, which severely degrades the receiver signal quality. One of the most important performance criteria for this kind of system is the blocking probability which shows the percentage of the outage IoT devices, and how we maintain the low blocking probability while supporting all the IoT devices simultaneously is particularly important. Due to RS reuse, we can divide IoT devices into two groups based on their interference levels. We provide detailed theoretical analyses, and show that the blocking primarily happens to the group with higher interference level. Increasing the number of service antennas and/or reducing the number of IoT devices can help to improve the performance of the blocking probability, however there is a regime in which the parameter adjustment helps little to improve the performance. Based on these factors, we provide a useful algorithm to improve the performance of blocking probability. A number of simulation results are also provided to validate the theoretical analysis.

UAV-Aided Aerial Reconfigurable Intelligent Surface Communications With Massive MIMO System

To capture the advantages of unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS) technologies, we propose the use of multiple passive aerial RISs in a massive multiple-input multiple-output (MIMO) network. Each aerial RIS is comprised of a RIS panel attached to a UAV, the intention being to support in extending network coverage from the massive MIMO base station. Compared with stationary RISs, our proposed aerial RISs (termed as UAV-RISs) have the ability to reach more users thanks to the line-of-sight links. Our aim is to maximise the total network throughput by finding the optimal power control coefficients at the base station and the phase shifts of the multiple RISs used in the system. This is jointly solved subject to the power consumption constraints, UAV-RIS deployment, and quality-of-service required at the users. We apply zero-forcing precoding for the beamforming design at the base station, and develop an iterative algorithm based on first-order approximation, block coordinate descent, and alternating optimisation technique. Numerical results demonstrate that our proposed method exhibits low computational-complexity and outperforms benchmark schemes in terms of the total network throughput achieved and improvement for the users with worst-case throughput.

An Adaptable and Scalable Generator of Distributed Massive MIMO Baseband Processing Systems

This paper presents an algorithm-adaptable, scalable, and platform-portable generator for massive multiple-input multiple-output (MIMO) baseband processing systems. This generator is written in Chisel hardware construction language, and produces instances that implement distributed massive MIMO base station (BS) processing, including channel estimation and beamforming. The generator can be reused for different MIMO systems and hardware datapath designs by changing the parameters. The generator is paired with a Python-based system simulator, which incorporated together can emulate a system testing various baseband signal processing algorithms. The field programmable gate array (FPGA) emulation is performed with generated instances using various parameter values. To demonstrate the algorithmic adaptability, a Golay-sequence-based channel estimation method, a beamspace calibration method, and a channel denoising algorithm are evaluated across a range of channel models. The performance of the generator, necessity of the algorithmic adaptability, and ease of hardware generation are evaluated and discussed. The emulated register-transfer level (RTL) implementation with different system parameters shows that with beamspace methods, the demodulation error vector magnitude is improved by up to 29.8%.

Rate and Energy Efficiency Improvements of Massive MIMO-Based Stochastic Cellular Networks With NOMA

Non-orthogonal multiple access (NOMA) coupled with massive multiple-input multiple-output (MIMO) base stations hold immense potential in increasing the spectral and energy efficiencies while enabling massive access of future cellular networks. To this end, we investigate the rate performance of a system employing multi-user NOMA and massive MIMO base stations distributed under a Poisson process. We adopt a time-division-duplexing mode, and employ matched filter based precoding in the downlink of the cellular network. We investigate two power allocation scenarios for the individual users while keeping the overall power usage of a NOMA cluster constant: 1) pre-defined power allocation and 2) power allocation based on user-base station distance. Considering imperfect successive interference cancellation, pilot contamination, and error propagation for the two power allocation scenarios, we characterize the average rate of a NOMA user and the signal detection probability under asymptotic conditions for the number of antennas. Furthermore, we derive the moment generating function of the out-of-cell interference caused by pilot contamination. We show that NOMA improves the rate performance and by extension the energy efficiency under most system conditions. Moreover, the rate can be increased further through denser network deployments, while the user fairness is greatly impacted by the power allocation scheme.

Spatial Correlation in Indoor Massive MIMO: Measurements and Ray Tracing

This letter investigates spatial correlation properties of radio-frequency massive multiple-input-multiple-output (MIMO) channels. The correlation between channel vectors at the receive side is studied for the interreceiver distances up to several wavelengths. This is an important property of 5G wireless networks and its accurate prediction is desirable in many applications. Measured and simulated channels are compared using an alternative formulation of the channel correlation function, the argument of which is the distance between any two receivers in proximity of a selected region. The measurements were conducted using a massive MIMO base station (BS) testbed and virtual arrays of receivers, positioned with a robotic system. The simulations were performed using the ray-tracing (RT) technique in a simplified model of an indoor environment, augmented with stochastic geometry elements. In addition, a line-of-sight (LOS) channel model was derived from the RT results, and the role of the scattered power on the correlation was evaluated. The results show that the RT model predicts the correlation with an error not exceeding 10%. The variation of the correlation function profile with increasing receiver to BS separation distance is also captured by the RT model. The simulated LOS model predictions, which account solely for direct propagation paths, were found to significantly underestimate the correlation at the subwavelength distance, and overestimate it at larger distances.

Probe Selection for 5G Massive MIMO Base Station Over-the-Air Testing

A sectored multiprobe anechoic chamber is seen as a promising method to carry out the radiated testing of massive multiple-input–multiple-output (MIMO) base station (BS), and realistic channel environment reconstruction is crucial for the performance assessment of wireless devices, especially for the testing of beamforming procedures, such as beam acquisition, tracking, and so on. This letter proposes a novel probe selection algorithm and corresponding device rotation scheme to enable more accurate channel emulation with specific probe antennas. On the other hand, within the acceptable threshold of error, the number of required probe antennas can be reduced, which will mitigate setup complexity and the number of hardware resources. In the simulation, to verify the robustness of the proposed probe configuration, several metrics are examined with different numbers of selected probes, in terms of spatial correlation and power angular spectrum emulation. The simulation results show that the proposed selection and rotation algorithms perform well in synthesizing the accurate target propagation environment on the BS side.

Pilot Decontamination for Massive MIMO Network With UAVs

This letter studies the pilot contamination (PC) problem for massive multiple-input multiple-output (MIMO) networks with coexisting terrestrial users and unmanned aerial vehicles (UAVs). Due to the strong line-of-sight (LoS) air-to-ground channels between UAVs and base stations (BSs), UAVs usually cause a more severe PC issue as compared to the traditional terrestrial users. To mitigate the PC caused by UAVs, we propose a low-complexity distributed scheme by exploiting the full-dimensional beamforming of massive MIMO BSs and the angle-dependent LoS channels between them and high-altitude UAVs. Numerical results show the effectiveness of the proposed pilot decontamination scheme and the significant signal-to-interference-plus-noise ratio (SINR) gains in both the uplink and downlink after pilot decontamination.

On Over-the-Air Testing for Devices With Directional Antennas

This paper investigates the impact of devices under test (DUTs) with directional antennas on the recreated channel in the over-the-air (OTA) testing for massive multiple-input multiple-output (MIMO) devices using prefaded signal synthesis (PFS) technique. Assuming the uplink in real radio environments, the directional receiver (Rx) antenna patterns would affect the gains in different incoming directions, thereby affecting the spatial characteristics of the target channel. A typical multi-probe anechoic chamber (MPAC) setup for massive MIMO base stations (BSs) is studied, where a limited number of probe antennas are distributed over the probe wall to emulate the target channel by proper probe weighting. The directional antenna patterns would have nonnegligible effects on the emulated spatial characteristics which may become inaccurate for DUTs with directional antennas and thus need to be re-examined. Therefore, the reconstructed channel with the PFS technique will be investigated under the MPAC setup in this paper, with particular focus on the DUTs with directional antennas. The deviations between the covariance matrix of the Rx antennas under the target channel and the covariance matrix under the reconstructed channel are used as the metric to evaluate the performance of the reconstructed channel, and the optimal probe weights are also re-determined. Furthermore, given beamforming capability of massive MIMO BSs, the impact of the BS antenna patterns on angular spectrum is investigated as well. In addition, since the reconstructed channel needs to not only reflect the spatial characteristics of Rx antennas but also reflect the spatial characteristics of transmitter antennas and propagation environment, the end-to-end channel capacities are evaluated. Simulation results under various scenarios show that the accuracies of the reconstructed channel in terms of spatial correlation, angular spectrum and channel capacity can be improved by using the re-optimized probe weights when directional antenna patterns of the DUTs are taken into account.

Secure Communication in Relay-Assisted Massive MIMO Downlink With Active Pilot Attacks

In this paper, the achievable secrecy rate of a relay-assisted massive multiple-input multiple-output (MIMO) downlink is investigated in the presence of a multi-antenna active/passive eavesdropper. The excess degrees-of-freedom offered by a massive MIMO base-station (BS) are exploited for sending artificial noise (AN) via random and null-space precoders. An active eavesdropper contaminates the uplink channel estimates by sending pilot sequences identical to those of the legitimate users/relay. This active pilot contamination makes the massive MIMO BS implicitly beamform the confidential signals toward the active eavesdropper during two-hop downlink transmissions. The achievable secrecy rates are derived by taking the detrimental effects of actively contaminated channel state information with estimation errors and spatially correlated fading at the multiple-antenna terminals into account. The secrecy rate loss incurred by active pilot attacks over passive eavesdropping is investigated, and the secrecy rate gap between random and null-space-based AN is compared. A novel transmit power control policy is designed to efficiently allocate transmit power at the BS/relay for payload data and AN sequences for maximizing the achievable secrecy rate. Our results reveal that active pilot contamination attacks significantly degrade the achievable secrecy rate in dual-hop transmissions, and the corresponding detrimental effects cannot be asymptotically mitigated in the infinite BS antenna regime.

High Gain Circularly Polarized Pentagonal Microstrip for Massive MIMO Base Station

In this paper we propose a circularly polarized pentagonal microstrip antenna on a suspended substrate with coaxial probe feed and five loaded slits for Massive MIMO BS Antenna applications. Massive Multiple-Input Multiple-Output (MIMO) is one of the key component to be incorporated in the 5G cellular systems. The proposed antenna is successfully simulated using HFSS 13.0, fabricated on a FR-4 substrate and measured. The proposed antenna exhibits a much higher gain of 6.17dB, improved impedance bandwidth of 171.9 MHz (Return loss, S11= -10dB) , axial ratio bandwidth (< 3dB) of 135 MHz , patch area of 1775 mm2 , and also yields return loss better than -15 dB around the center frequency of 2.45 GHz (ISM Band). Measured characteristics of the antenna are in good agreement with the simulated results.

Wireless Information and Power Transfer in Relay-Assisted Downlink Massive MIMO

The feasibility of utilizing a relay-assisted downlink massive multiple-input multiple-output (MIMO) to boost the performance of simultaneous wireless information and power transfer (SWIPT) is investigated. The key idea is to simultaneously transmit power and information toward the direct/relayed-users by leveraging the excess degrees-of-freedom offered by massive antenna arrays at the base-station (BS). The performance limits are established by deriving the harvested energies, achievable rates, and energy-rate trade-offs in the presence of imperfectly estimated/partial channel state information (CSI). These performance metrics are derived for a generalized SWIPT model, which facilitates analysis for both time-switching (TS) and power-splitting (PS) protocols. Two linear precoders based on zero-forcing and maximal ratio transmission are used at the massive MIMO BS, and a practically viable non-linear energy harvesting model is adopted for the direct/relayed-users. Joint detrimental implications of imperfect CSI at the BS, limited/statistical CSI at the users, and non-linear characteristics of energy harvesters are analytically quantified. In order to jointly guarantee user-fairness in terms of both energy and rate, a max-min optimal transmit power control policy is proposed. Then, the max-min fairness optimal energy-rate trade-offs are quantified for non-linear massive MIMO SWIPT. Our results reveal that the proposed relay-assisted downlink massive MIMO can be exploited to boost the achievable energy-rate trade-off by effectively reducing the end-to-end path-loss via shorter hop distances rendered by intermediate amplify-and-forward relays.

On Probe Weighting for Massive MIMO OTA Testing Based on Angular Spectrum Similarity

Over-the-air (OTA) radiated testing for massive multiple-input–multiple-output (MIMO) base stations (BSs) poses an urgent challenge for the extended development and deployment of the fifth-generation mobile communication systems. Conventionally, MIMO OTA uses the spatial correlation-based metric for channel emulation to evaluate the fourth-generation user terminals. However, it does not provide sufficient accuracy due to the larger dimension of massive MIMO BSs. In this letter, we propose a new criterion based on angular spectrum similarity for channel emulation in OTA testing of massive MIMO BSs. As antenna array control is critical for the performances of massive MIMO BSs, the proposed metric can reconstruct power distribution more accurately in the angular domain, thus increasing channel emulation accuracy, which will affect notable performances, such as array gain, sidelobe interference, and direction-of-arrival estimation, for massive MIMO BS OTA testing.

Power control scheme for spectral coexisting multistatic radar and massive MIMO communication systems under uncertainties: A robust Stackelberg game model

In this paper, we study the problem of robust Stackelberg game-based power control (RSG-PC) for spectral coexisting multistatic radar and massive multiple-input multiple-output (MIMO) communication systems. Recognizing that the path propagation gains cannot be assumed to be constant, the column-wise model is employed to describe the uncertainty of the parameters. The primary objective of the RSG-PC scheme is to minimize the worst-case radiated power of each radar with uncertain path gains for a specified signal-to-interference-plus-noise ratio (SINR) requirement for target detection, while the massive MIMO communication base station (MIMO-CBS) is protected from the interference of radar transmissions. The hierarchical competition between the massive MIMO-CBS and multiple radars are modeled as a robust single-leader multi-follower Stackelberg game. In the considered game model, the massive MIMO-CBS plays as the leader to decide the prices first through the maximization of its own utility. The radars act as the followers, who compete with each other in a non-cooperative Nash game according to the released interference prices from the massive MIMO-CBS subsequently. Based on the theoretical findings on the existence and uniqueness of the robust Nash equilibrium (RNE) in the formulated game, we present an iterative power control approach that guarantees the convergence to the RNE. Finally, the numerical simulations are provided to verify that our RSG-PC scheme can provide efficient power resource utilization, guarantee a predefined target detection performance, and also protect the quality of service (QoS) of massive MIMO-CBS with uncertainties in path propagation gains.

Pricing user scheduling and precoding in relay‐assisted massive MIMO systems

A downlink user scheduling algorithm based on the pricing scheduling factor is proposed for the established relay-assisted massive multiple input multiple output (MIMO) model, which represents the typical remote cell with multiple relays and a massive MIMO base station. Different from the traditional scheduling algorithms, the authors' proposed scheduling algorithm simultaneously takes account of the strength of the desired signal and interference, in which the proposed scheduling factor takes interference strength as the price to select appropriate users. An analysis on the optimal precoding vector is given by assuming each relay adopts equal gain transmission (EGT). According to the analysis, a non-cooperative solution based on the phase difference of EGT is proposed to search the optimal transmission direction of EGT with low complexity. An analytical upper bound of system sum rate is also obtained. Simulation results indicate that the proposed scheduling algorithm has excellent sum rate performance and slight rate degradation compared with the brute-force search algorithm.

Hybrid Ray-Tracing/FDTD Method for Human Exposure Evaluation of a Massive MIMO Technology in an Industrial Indoor Environment

This paper presents a numerical approach for massive multiple-input multiple-output (MIMO) human exposure assessment. It combines ray-tracing for the estimation of the wireless channel and the finite-difference time-domain method to simulate the exposure of a realistic human phantom. We apply it to estimate the exposure in a model of an industrial indoor environment with a single massive MIMO base station (BS). The exposure scenarios include line-of-sight and non-line-of-sight propagation with the BS using equal gain transmission precoding at 3.5 GHz. Calculated channel parameters are discussed in comparison with the data available in the literature. The exposure in the phantom's head is evaluated in terms of the peak-spatial specific absorption rate averaged over a 10-g cube and referenced to the free-space time-averaged Poynting vector magnitude at the same location.

A Virtual Over-the-Air Method for 5G Massive MIMO Base Station Testing With Flexible Virtual Probes

Massive multiple-input-multiple-output (MIMO) is known as a large-scale antenna technology and has been enabled for the fifth generation (5G) mobile communication systems. The over-the-air (OTA) testing of massive MIMO antenna system has attracted a lot of attention in terms of evaluating the radio performance of a 5G base station (BS). As a promising OTA test methodology, the sectored multi-probe anechoic chamber (MPAC) setup is employed for the performance testing of massive MIMO BS. However, the system cost and installation are still an issue to be considered in practice (e.g., the anechoic chamber and multiple probes), though it can accurately reconstruct the flexible propagation channels by channel emulation methods. This paper proposes a virtual OTA test framework for the performance testing of massive MIMO BS on the basis of MPAC setups. As an alternative, the proposed virtual OTA test system adopting the concept of virtual probes solves the inconveniences and limitations of the actual probe installation in MPAC setups. The BS array responses to the actual probes of MPAC setups are generated in a phase matrix for the virtual probes. First, in this paper, the system description of virtual OTA testing is given. Then, the emulation method of spatial clusters is presented for the virtual OTA testing. Finally, simulations are performed with good channel emulation accuracy.

Partial CSI Acquisition for Size-Constrained Massive MIMO Systems With User Mobility

We propose a low-complexity approach for the downlink of physically constrained massive multiple-input multiple-output (MIMO) systems with user mobility. We examine a channel state information (CSI) acquisition strategy that exploits both the spatial and temporal correlations among the channels of adjacent base station antennas. The proposed strategy solely collects CSI for a subset of antennas and time frames. Then full CSI is approximated using the CSI of adjacent antennas and previous frames. This critically reduces the CSI acquisition complexity while sacrificing the CSI quality and, hence, introduces a scalable performance-complexity tradeoff. The numerical results demonstrate that, for practical mobile speeds, the proposed scheme reduces the computational complexity and enhances the energy efficiency of massive MIMO base stations against systems with complete CSI, while approximately preserving performance.

Massive MIMO for Industrial Internet of Things in Cyber-Physical Systems

To apply cyber-physical system (CPS) technique in industrial internet, a wireless technology that is able to robustly maintain hyperconnectivity between a data center and distributed user entities and/or industrial Internet of Things devices is required. We investigate the feasibility of utilizing massive multiple-input multiple-output (MIMO) as such a wireless technology. We analyze the performance of a massive MIMO base station deployed at a data center to provide massive connectivity to a large number of devices. In addition, we discuss related research challenges for deploying massive MIMO in industrial internet applications of CPS, such as device scheduling and power control, energy efficient design and radio frequency energy transfer/harvesting, signaling techniques for drones and mobile robots, and applications of underwater industrial internet.