Full Dimension MIMO Research Articles

Downlink massive full dimension-multiple input multiple output downlink beamforming analysis at 3.5 GHz using coordinated ON-OFF switching

<p><span lang="EN-US">The long-term evolution and advancement (LTE-A) of the 5G wireless network depends critically on energy consumption. Many existing solutions focus on limiting power constraints and consequently system coverage. So, improving the antenna array elements of the base station (BS) can solve this issue. In this paper, introduce a coordinated ON-OFF switching method in the massive full dimensional multiple input multiple output (massive-FD-MIMO) system. It enhances the radiation pattern of the antenna array element by adjusting the angular power spectra at the BS. By the way, it allows to select the minimum number of antennas for effective beamforming toward specific user equipment’s (UEs). In this context, part of antenna element should be active mode and remining should be sleep mode at the time of signal beamforming. The multipath spatial profiles are decided the beamforming frequency band with minimize energy consumption. As part of the method, we used a conjugated beamforming with power optimization scheme to determine the individual antenna potential and fading channel condition, power optimization is performed. This method quality of service, reliability, energy consumption and data rate can all be evaluated by experimenting with different-sized antenna arrays such as 16×16, 32×32, 64×64 and 128×128.</span></p>

Performance Analysis of 2D-ESPRIT Algorithm for URA in Estimation of 2D-DOA in Massive-MIMO Systems

Purpose: The performance of smart antenna is affected by antenna array configuration and the direction of arrival estimation (DOA) algorithm used .To have a suitable DOA for an uniform rectangular array (URA),The performance of two dimensional estimation of signal parameters via rotational invariance techniques (2D-SPRIT) that are applied for two different planar dispositions of antenna for URA in Massive Multiple Inputs Multiple Output (Massive MIMO) systems when subjected to the same simulation conditions is comparatively analyzed. The performance of the proposed 2D-ESPRIT algorithm with URA in vertical plane (the case of full-dimensional MIMO) has been compared with that of the existing 2D-ESPRIT algorithm that is applied with URA in horizontal plane.
 Methodology: Implementation and simulation of analyzed 2D-ESPRIT algorithms was done in MATLAB and compared considering computational complexity efficiency, DOA estimation precision, estimation failure and variation of Root mean square Error (RMSE) with Signal to Noise Ratio (SNR) and angular spread. MATLAB simulation results got from similar input parameters in a multipath environment are compared to derive a conclusion.
 Findings: Simulation results show that the proposed 2D-ESPRIT algorithm applied in vertical plane outperforms the existing 2D-ESPRIT algorithm applied in horizontal plane for all considered performance criteria that include estimation precision, running time and Root mean square error (RMSE).
 Recommendation: Other researchers interested in working on 2D-ESPRIT algorithms are recommended to improve the work reported in this paper by further reducing computational complexity observed in 2D-ESPRIT algorithm with URA in vertical plane at large antenna array size to reflect the standard of full-dimension MIMO.

A fast gridless mmWave full-dimensional MIMO channel estimation method

Most existing channel estimation methods for millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication systems focus on linear arrays rather than planar arrays since discretizing the high-dimensional angle space in planar array scenario brings in high computations. In this paper, we consider the channel estimation problem for mmWave full-dimensional MIMO system where the base station (BS) and user equipment (UE) are equipped with planar arrays. We first propose an atomic ℓ0 norm based optimization problem to find the angle estimates and then transfer the problem into a solvable semidefinite programming (SDP). We next propose a computationally efficient algorithm to solve the SDP rather than employing existing standard solvers. Compared with the grid based methods which require discretizing the angle space, our method avoids angle discretization which brings in huge computations. Various simulations show that our method is able to provide satisfying channel estimation performance while is also computationally efficient.

Network Slicing on 5G Vehicular Cloud Computing Systems

Fifth generation Vehicular Cloud Computing (5G-VCC) systems support various services with strict Quality of Service (QoS) constraints. Network access technologies such as Long-Term Evolution Advanced Pro with Full Dimensional Multiple-Input Multiple-Output (LTE-A Pro FD-MIMO) and LTE Vehicle to Everything (LTE-V2X) undertake the service of an increasing number of vehicular users, since each vehicle could serve multiple passenger with multiple services. Therefore, the design of efficient resource allocation schemes for 5G-VCC infrastructures is needed. This paper describes a network slicing scheme for 5G-VCC systems that aims to improve the performance of modern vehicular services. The QoS that each user perceives for his services as well as the energy consumption that each access network causes to user equipment are considered. Subsequently, the satisfactory grade of the user services is estimated by taking into consideration both the perceived QoS and the energy consumption. If the estimated satisfactory grade is above a predefined service threshold, then the necessary Resource Blocks (RBs) from the current Point of Access (PoA) are allocated to support the user’s services. On the contrary, if the estimated satisfactory grade is lower than the aforementioned threshold, additional RBs from a Virtual Resource Pool (VRP) located at the Software Defined Network (SDN) controller are committed by the PoA in order to satisfy the required services. The proposed scheme uses a Management and Orchestration (MANO) entity implemented by a SDN controller, orchestrating the entire procedure avoiding situations of interference from RBs of neighboring PoAs. Performance evaluation shows that the suggested method improves the resource allocation and enhances the performance of the offered services in terms of packet transfer delay, jitter, throughput and packet loss ratio.

Design and implementation of beamformed physical downlink control channel for 4G massive MIMO systems

The Full Dimension-MIMO (FD-MIMO) technology is capable of achieving huge improvements in network throughput with simultaneous connectivity of a large number of mobile wireless devices, unmanned aerial vehicles, and the Internet of Things (IoT). In the Long Term Evolution (LTE), with a large number of antennae at the base station and the ability to perform beamforming, the capacity of the physical downlink shared channel (PDSCH) has increased a lot. However, the current 3rd Generation Partnership Project (3GPP) specifications of the LTE do not allow the base station to perform any beamforming techniques for the physical downlink control channel (PDCCH). Hence, PDCCH has neither the capacity nor the coverage of PDSCH. Therefore, PDCCH capacity still limits the performance of a network, as it dictates the number of users that a base station can schedule at a given time instant. In Release 11, 3GPP introduced enhanced PDCCH (EPDCCH) to increase the PDCCH capacity at the cost of sacrificing the PDSCH resources. The problem of enhancing the PDCCH capacity within the available control channel resources has not been addressed yet in the literature. Hence, in this paper, we propose a novel beamformed PDCCH (BF-PDCCH) design which is aligned to the 3GPP specifications and requires simple software changes at the base station. For the evaluation of the proposed BF-PDCCH, we model various link abstractions. We evaluate them through link-level simulations and then use all these abstractions in the system-level simulations. We show that the proposed BF-PDCCH achieves significant improvement in network throughput and outperforms the current state of the art algorithms, PDCCH, and EPDCCH schemes.

RETRACTED ARTICLE: Improving spectral efficiency and low latency in 5G framework utilizing FD-MIMO

Multiple input-multiple output (MIMO), massive MIMO, full-dimension MIMO (FD-MIMO) are the most recent remote advancements, which structure the purpose of takeoff for long term evolution systems. FD-MIMO is the promising technology proposed in the Third Generation Partnership Project to the transformation for the fifth-generation wireless communication schemes. FD-MIMO tramples several practical challenges imposed by massive MIMO systems such as interference, hardware limitations by the use of 2D active antenna array system which provides beam-forming in both azimuths as well as elevation domains in three-dimensional space. The traditional construction of big-scale planar arrays maximizes the spatial correlation is addressed using the dynamic device specific single down tilt beam-forming which minimizes the signal to interference ratio. That is further reduced by using FD-MIMO with incremental Redundancy and Regression monitoring techniques formulated as soft combining strategies. In this paper, the simulation results show maximizing of the minimum signal-to-interference ratio, spectral efficiency improvement and minimizing packet transmission time between eNodeB. Also, user equipment utilizing incremental redundancy shifting, hybrid automatic repeat request and regression monitoring strategies using network simulator 3.

Superimposed Pilot for Multi-Cell Multi-User Massive FD-MIMO Systems

In this paper, superimposed pilot based communication strategies are investigated for a time-division duplex (TDD)-based massive Full-Dimension MIMO (FD-MIMO) network jointly considering both uplink (UL) and downlink (DL) performance. To be specific, the DL multi-cell multi-user MIMO operation is connected to UL channel estimation through the superimposed pilot. The performance of UL channel estimation is analytically characterized and the estimated UL channel is linked to the DL MIMO operation for the massive MIMO network. In this way, the corresponding feedback for DL channel state information (CSI) can be eliminated while the UL pilot overhead can be minimized. Results suggest that superimposed pilot could significantly improve the overall network performance of a massive FD-MIMO network.

FFR Based Joint 3D Beamforming Interference Coordination for Multi-Cell FD-MIMO Downlink Transmission Systems

This paper investigate the downlink transmission, especially the interference coordination for the cell-edge users in multi-cell full-dimension multiple-input multiple-output (FD-MIMO) systems. We assume that each base station (BS) can only obtain statistical channel state information (CSI), so as to reduce the CSI required at each BS. We propose a fractional-frequency-reuse(FFR) scheme for multi-cell FD-MIMO systems, in which all the cell-center users occupy the same frequency band, while all the cell-edge users use the rest of the frequency band. Based on this FFR scheme, two joint three-dimensional (3D) beamforming interference coordination strategies, i.e., the full-cooperative strategy, and a more energy-efficient partial-cooperative strategy, are proposed to alleviate the inter-cell interference for the cell-edge users. Moreover, tractable approximations of the ergodic rate for both cell-center and cell-edge users are derived. Simulations show that the proposed interference coordination strategies can significantly improve the cell-edge performance, while maintain relatively high total throughput. The full-cooperative strategy performs best in the cell-edge performance, and the partial-cooperative strategy performs best in the aspects of total throughput and energy-efficiency.

Achieving Phase Coherency and Gain Stability in Active Antenna Arrays for Sub-6 GHz FDD and TDD FD-MIMO: Challenges and Solutions

Full-dimension MIMO (FD-MIMO) using planar active antenna systems (AAS) is considered a critical technology for fifth-generation (5G) cellular systems to improve network capacity. An AAS is typically subject to hardware impairments that negatively impact network capacity. Hence, this article focuses on impairments that cause phase and magnitude errors between radio frequency (RF) chains and shows why they are particularly difficult to avoid in practical AAS. Although previous investigations show these impairments to degrade performance, they are not useful in deriving measurable impairment margins for practical FD-MIMO deployments. Knowing impairment limits are critical for system designers to make hardware design tradeoffs such as AAS configuration, component selection, implementation complexity, and cost. Moreover, it also helps set conformance limits for critical lab verification. Therefore, the paper first investigates the impact of the impairments and derives their practical limits for FD-MIMO by explicitly considering the cumulative effects of the channel model, inter-cell interference, link adaptation, and channel aging due to feedback delays. It is shown that a lower number of digitized RF chains can be a better choice under lower impairments. Next, the sources of impairments are investigated by using measurements carried out in the lab and the field during live operation in a commercial LTE network. Phase drift from local oscillators (LO) and internal temperature variations are identified as two significant sources. The tradeoffs and shortcomings of some of the existing solutions in massive MIMO literature are discussed. Finally, in order to address the shortcomings, a novel and practical coherent LO distribution architecture and array calibration mechanism are proposed. This solution is shown to be applicable to both TDD and FDD FD-MIMO. Measurement results are provided to prove the high degree of coherency and stability achieved on a unique array architecture called high definition active antenna system (HDAAS).

MIMO-OFDM in a Cooperative Frequency Selective Fading Channel: An Analysis

Diversity is an integral technique in the advancement of wireless communications. Multiple-input multiple-output (MIMO) technology continues to occupy a pivotal position in the fourth-generation (4G) standards and beyond. With the advent of full-dimension (FD) MIMO and massive MIMO, new paradigms are being targeted in the disruptive technology. Third-generation partnership project (3GPP) has also emphasized the advanced MIMO technology for achieving its vision of International Mobile Telephony (IMT) 2020. However, implementing multiple antennas can be cumbersome due to limiting factors such as size, cost, and hardware limitations. In such a scenario, where implementing many antennas is not feasible, the benefits of diversity can be reaped by employing cooperative communication. Single antenna mobiles can share their mobile stations giving rise to a virtual MIMO system. In this paper, the authors have analyzed the performance of cooperative mobile stations in a frequency selective channel. Orthogonal frequency division multiplexing (OFDM), known for its robustness against multipath fading, is the modulation technique employed to circumvent the hazardous effects of intersymbol interference (ISI). MIMO is the key technology for achieving capacity advantage and improving link reliability. The blend of these two cutting edge technologies in a cooperative relay system presents encouraging results and inferences. Maximal Ratio Combining (MRC) is employed at the relay and the receiver to maximize the signal-to-noise ratio (SNR). Decode and forward (DF) protocol is used at the relay node owing to its regenerative nature and adaptability. The closed-form expressions for bit error rate (BER) and outage probability (Pout) are derived and compared with the experimental results. The effect of power decay factor is analyzed and simulation is done for 2 × 2, 2 × 3, and 2 × 4 transmit and receive antennas. The number of antennas at the relay is kept as 2. The analytical results agree with the simulation results.

FD-MIMO via Pilot-Data Superposition: Tensor-Based DOA Estimation and System Performance

Increased pilot overhead is one of the major issues for 5G full-dimension MIMO (FD-MIMO) systems. In this paper, we introduce the FD-MIMO system using pilot-data superposition to reduce the uplink pilot overhead and investigate the impact of superimposed pilots on the overall network performance. The pilot-data superposition can relatively increase the resources allocated to the uplink data transmission. However, in time division duplex (TDD) systems, it also negatively impacts the downlink throughput since the relatively reduced pilot power can affect the estimation of the channel state information (CSI) which is used for the downlink precoding. To improve the CSI estimation, the intrinsic tensor feature of the FD-MIMO channel is exploited in our method. The introduced CSI estimation algorithm is designed through the expectation-maximization (EM) framework via tensor as the processing data structure. Furthermore, Cramer-Rao lower bound (CRLB) is utilized as a metric in our evaluation. The overall system achievable rate which is a weighted sum of the uplink and downlink throughput is investigated to reveal the fundamental trade-off between the uplink and downlink transmission in the TDD-based FD-MIMO system. In our simulation, the results demonstrate the superior performance of the introduced strategy as opposed to the conventional orthogonal pilot-data approach. Meanwhile, the pilot power allocation, as well as different transmitting and receiving strategies are investigated to offer various trade-off points between the uplink and downlink transmission.

Multi-Cell Multi-User Massive FD-MIMO: Downlink Precoding and Throughput Analysis

In this paper, downlink (DL) precoding and power allocation strategies are identified for a time-division-duplex (TDD) multi-cell multi-user massive Full-Dimension MIMO (FD-MIMO) network. Utilizing channel reciprocity, DL channel state information (CSI) feedback is eliminated and the DL multi-user MIMO precoding is linked to the uplink (UL) direction of arrival (DoA) estimation through estimation of signal parameters via rotational invariance technique (ESPRIT). Assuming non-orthogonal/non-ideal spreading sequences of the UL pilots, the performance of the UL DoA estimation is analytically characterized and the characterized DoA estimation error is incorporated into the corresponding DL precoding and power allocation strategy. Simulation results verify the accuracy of our analytical characterization of the DoA estimation and demonstrate that the introduced multi-user MIMO precoding and power allocation strategy outperforms existing zero-forcing based massive MIMO strategies.

Elevation Beamforming With Full Dimension MIMO Architectures in 5G Systems: A Tutorial

Full dimension (FD) multiple-input multiple-output (MIMO) technology has attracted substantial research attention from both wireless industry and academia in the last few years as a promising technique for next-generation wireless communication networks. FD-MIMO scenarios utilize a planar 2-D active antenna system (AAS) that not only allows a large number of antenna elements to be placed within feasible base station (BS) form factors, but also provides the ability of adaptive electronic beam control over both the elevation and the traditional azimuth dimensions. This paper presents a tutorial on elevation beamforming analysis for cellular networks utilizing FD massive MIMO antenna arrays. In contrast to existing works that focus on the standardization of FD-MIMO in the 3rd generation partnership project (3GPP), this tutorial is distinguished by its depth with respect to the theoretical aspects of antenna array and 3-D channel modeling. In an attempt to bridge the gap between industry and academia, this preliminary tutorial introduces the relevant array and transceiver architecture designs proposed in the 3GPP Release 13 that enable elevation beamforming. Then it presents and compares two different 3-D channel modeling approaches that can be utilized for the performance analysis of elevation beamforming techniques. The spatial correlation in FD-MIMO arrays is characterized and compared based on both channel modeling approaches and some insights into the impact of different channel and array parameters on the correlation are drawn. All these aspects are put together to provide a mathematical framework for the design of elevation beamforming schemes in single-cell and multi-cell scenarios. Simulation examples associated with comparisons and discussions are also presented. To this end, this paper highlights the state-of-the-art research and points out future research directions.

Optimization of Massive Full-Dimensional MIMO for Positioning and Communication

Massive full-dimensional multiple-input multiple-output (FD-MIMO) base stations (BSs) have the potential to bring multiplexing and coverage gains by means of three-dimensional (3D) beamforming. The key technical challenges for their deployment include the presence of limited-resolution front ends and the acquisition of channel state information (CSI) at the BSs. This paper investigates the use of FD-MIMO BSs to provide simultaneously high-rate data communication and mobile 3D positioning in the downlink. The analysis concentrates on the problem of beamforming design by accounting for imperfect CSI acquisition via time division duplex-based training and for the finite resolution of analog-to-digital converter and digital-to-analog converter at BSs. Both unstructured beamforming and a low-complexity Kronecker beamforming solution are considered, where for the latter the beamforming vectors are decomposed into separate azimuth and elevation components. The proposed algorithmic solutions are based on the Bussgang theorem, rank-relaxation, and successive convex approximation (SCA) methods. Comprehensive numerical results demonstrate that the proposed schemes can effectively cater to both data communication and positioning services, providing only minor performance degradations compared to the conventional cases in which either only the data communication or only positioning is implemented. Moreover, the proposed low-complexity Kronecker beamforming is seen to guarantee a limited performance loss in the presence of a large number of BS antennas.

Advanced Quantizer Designs for FDD-Based FD-MIMO Systems Using Uniform Planar Arrays

Massive multiple-input multiple-output (MIMO) systems, which utilize a large number of antennas at the base station, are expected to enhance network throughput by enabling improved multiuser MIMO techniques. To deploy many antennas in reasonable form factors, base stations are expected to employ antenna arrays in both horizontal and vertical dimensions, which is known as full-dimension (FD) MIMO. The most popular two-dimensional array is the uniform planar array (UPA), where antennas are placed in a grid pattern. To exploit the full benefit of massive MIMO in frequency division duplexing (FDD), the downlink channel state information (CSI) should be estimated, quantized, and fed back from the receiver to the transmitter. However, it is difficult to accurately quantize the channel in a computationally efficient manner due to the high dimensionality of the massive MIMO channel. In this paper, we develop both narrowband and wideband CSI quantizers for FD-MIMO taking the properties of realistic channels and the UPA into consideration. To improve quantization quality, we focus on not only quantizing dominant radio paths in the channel, but also combining the quantized beams. We also develop a hierarchical beam search approach, which scans both vertical and horizontal domains jointly with moderate computational complexity. Numerical simulations verify that the performance of the proposed quantizers is better than that of previous CSI quantization techniques.

User scheduling for downlink FD-MIMO systems under Rician fading exploiting statistical CSI

In this paper, we consider the user scheduling algorithm for downlink full-dimension multiple-input multiple-output (FD-MIMO) system under Rician fading channels. We assume that two-dimensional (2D) large-scale antenna array is deployed at base station (BS). An approximation of users signal-to-interference-plus-noise ratio (SINR) and a lower bound of users average signal-to-leakage-plus-noise ratio (SLNR) are derived. Based on these, two user scheduling algorithms exploiting only statistical channel state information (CSI) are proposed. The proposed algorithms take both the achievable sum rate and fairness into account. Simulation results reveal that the proposed user scheduling algorithms can make good trade-off between the achievable rate and fairness.

Robust full-dimension MIMO transmission based on limited feedback angular-domain CSIT

In this paper, we propose robust multi-user beamforming and precoding techniques for full-dimension MIMO transmission based on limited feedback. We propose to employ an over-complete basis decomposition in the angular domain to approximate the channel matrices as sums of few dominant specular components, facilitating efficient channel state information (CSI) quantization at the users. The selected expansion vectors of such a sparse approximation, parametrized by azimuth and elevation angles, are relatively robust with respect to channel estimation errors as well as channel variations over time. Based on this CSI feedback, we propose incoherent beamforming/precoding methods that make use only of the azimuth and elevation angles as well as the norm of the expansion coefficients and do not rely on coherent multipath interference to eliminate inter-user interference. Our optimization aims at maximizing the signal power or the achievable rate of a user, while limiting the amount of interference leakage caused to other users. To further improve robustness, we account for uncertainty in the angular channel decomposition in the proposed precoder optimization.

Design of 5G Full Dimension Massive MIMO Systems

This paper discusses full-dimension multiple-input-multiple-output (FD-MIMO) technology, which is currently an active area of research and standardization in wireless communications for evolution toward Fifth Generation (5G) cellular systems. FD-MIMO utilizes an active antenna system (AAS) with a 2-D planar array structure that not only allows a large number of antenna elements to be packed within feasible base station form factors, but also provides the ability of adaptive electronic beamforming in the 3-D space. However, the compact structure of large-scale planar arrays drastically increases the spatial correlation in FD-MIMO systems. In order to account for its effects, the generalized spatial correlation functions for channels constituted by individual elements and overall antenna ports in the AAS are derived. Exploiting the quasi-static channel covariance matrices of users, the problem of determining the optimal downtilt weight vector for antenna ports, which maximizes the minimum signal-to-interference ratio of a multi-user multiple-input-single-output system, is formulated as a fractional optimization problem. A quasi-optimal solution is obtained through the application of semi-definite relaxation and Dinkelbach’s method. Finally, the user-group specific elevation beamforming scenario is devised, which offers significant performance gains as confirmed through simulations. These results have direct application in the analysis of 5G FD-MIMO systems.

Optimal Inter-Element Spacing of FD-MIMO Planar Array in Urban Macrocell with Elevation Channel Modelling

Full Dimension multiple input multiple output (FD-MIMO) architecture employs a planar array design at the Base Station (BS) to provide high order multi-user MIMO (MU-MIMO) via simultaneous data transmission to large number of users. With FD-MIMO, the BS can also adjust the beam direction in both elevation and azimuth direction to concentrate the energy on the user of interests while minimizing the interference leakage to co-scheduled users in the same cell or users in the neighboring cells. In a typical highly populated macrocell environment, modelling the elevation angular characteristics of three-dimensional (3D) channel is critical to understanding the performance limits of the FD-MIMO system. In this paper, we study the throughput performance of FD-MIMO system with varying elevation angular spread and inter-element spacing using a 3D spatial channel model. Our results show that for a typical urban scenario, horizontal beamforming with correlated antenna spacing achieves optimal performance but by restricting the spread of elevation angles of departure, elevation beamforming achieves high array gain with wide inter-element spacing. We also realize significant gains due to spatial array processing via modelling the elevation domain and varying the inter-element spacing for both the transmitter and receiver.

An Overview of Massive MIMO Technology Components in METIS

As the standardization of full-dimension MIMO systems in the Third Generation Partnership Project progresses, the research community has started to explore the potential of very large arrays as an enabler technology for meeting the requirements of fifth generation systems. Indeed, in its final deliverable, the European 5G project METIS identifies massive MIMO as a key 5G enabler and proposes specific technology components that will allow the cost-efficient deployment of cellular systems taking advantage of hundreds of antennas at cellular base stations. These technology components include handling the inherent pilot-data resource allocation trade-off in a near optimal fashion, a novel random access scheme supporting a large number of users, coded channel state information for sparse channels in frequency- division duplexing systems, managing user grouping and multi-user beamforming, and a decentralized coordinated transceiver design. The aggregate effect of these components enables massive MIMO to contribute to the METIS objectives of delivering very high data rates and managing dense populations.