The increasing wireless data traffic demands have driven the need to explore suitable spectrum regions for meeting the projected requirements. In the light of this, millimeter wave (mmWave) communication has received considerable attention from the research community. Typically, in fifth generation (5G) wireless networks, mmWave massive multiple-input multiple-output (MIMO) communications is realized by the hybrid transceivers which combine high dimensional analog phase shifters and power amplifiers with lower-dimensional digital signal processing units. This hybrid beamforming design reduces the cost and power consumption which is aligned with an energy-efficient design vision of 5G. In this paper, we track the progress in hybrid beamforming for massive MIMO communications in the context of system models of the hybrid transceivers’ structures, the digital and analog beamforming matrices with the possible antenna configuration scenarios and the hybrid beamforming in heterogeneous wireless networks. We extend the scope of the discussion by including resource management issues in hybrid beamforming. We explore the suitability of hybrid beamforming methods, both, existing and proposed till first quarter of 2017, and identify the exciting future challenges in this domain.

https://biblio.ugent.be/publication/8585223/file/8585225.pdf

A Survey on Hybrid Beamforming Techniques in 5G: Architecture and System Model Perspectives

5G roadmap

Millimeter wave (mm-wave) communication is expected to be widely deployed in fifth generation (5G) wireless networks due to the substantial bandwidth available for licensed and unlicensed use at mm-wave frequencies. To overcome the higher path loss observed at mm-wave bands, most prior work focused on the design of directional beamforming using analog and/or hybrid beamforming techniques in large-scale multiple-input multiple-output systems. Obtaining potential gains from highly directional beamforming in practical systems hinges on sufficient levels of channel estimation accuracy, where the problem of channel estimation becomes more challenging due to the substantial training overhead needed to sound all directions using a high-resolution narrow beam. In this paper, we consider the design of multi-resolution beamforming sequences to enable the system to quickly search out the dominant channel direction for single-path channels. The resulting design generates a multilevel beamforming sequence that strikes a balance between minimizing the training overhead and maximizing beamforming gain, where a subset of multilevel beamforming vectors is chosen adaptively to maximize the average data rate within a constrained time. We propose an efficient method to design a hierarchical multi-resolution codebook utilizing a Butler matrix, i.e., a generalized discrete Fourier transform matrix. Numerical results show the effectiveness of the proposed algorithm.

/pdf/multi-resolution-codebook-and-adaptive-beamforming-sequence-364952i5dy.pdf

Multi-Resolution Codebook and Adaptive Beamforming Sequence Design for Millimeter Wave Beam Alignment

In this paper, we develop a low-complexity channel estimation for hybrid millimeter wave (mmWave) systems, where the number of radio frequency (RF) chains is much less than the number of antennas equipped at each transceiver. The proposed mmWave channel estimation algorithm first exploits multiple frequency tones to estimate the strongest angle-of-arrivals (AoAs) at both base station (BS) and user sides for the design of analog beamforming matrices. Then, all the users transmit orthogonal pilot symbols to the BS along the directions of the estimated strongest AoAs in order to estimate the channel. The estimated channel will be adopted to design the digital zero-forcing (ZF) precoder at the BS for the multi-user downlink transmission. The proposed channel estimation algorithm is applicable to both the non-sparse and sparse mmWave channel environments. Furthermore, we derive a tight achievable rate upper bound of the digital ZF precoding with the proposed channel estimation algorithm scheme. Our analytical and simulation results show that the proposed scheme obtains a considerable achievable rate of fully digital systems, where the number of RF chains equipped at each transceiver is equal to the number of antennas. Besides, considering the effect of various types of errors, i.e., random phase errors, transceiver analog beamforming errors, and equivalent channel estimation errors, we derive a closed-form approximation for the achievable rate of the considered scheme. We illustrate the robustness of the proposed channel estimation and multi-user downlink precoding scheme against the system imperfection.

Multi-User Precoding and Channel Estimation for Hybrid Millimeter Wave Systems

Massive multiple-input multiple-output (MIMO) systems combined with beamforming antenna array technologies are expected to play a key role in next-generation wireless communication systems (5G), which will be deployed in 2020 and beyond. The main objective of this review paper is to discuss the state-of-the-art research on the most favourable types of beamforming techniques that can be deployed in massive MIMO systems and to clarify the importance of beamforming techniques in massive MIMO systems for eliminating and resolving the many technical hitches that massive MIMO system implementation faces. Classifications of optimal beamforming techniques that are used in wireless communication systems are reviewed in detail to determine which techniques are more suitable for deployment in massive MIMO systems to improve system throughput and reduce intra- and inter-cell interference. To overcome the limitations in the literature, we have suggested an optimal beamforming technique that can provide the highest performance in massive MIMO systems, satisfying the requirements of next-generation wireless communication systems.

/pdf/beamforming-techniques-for-massive-mimo-systems-in-5g-5autfewekh.pdf

Beamforming techniques for massive MIMO systems in 5G: overview, classification, and trends for future research

A 2D antenna array introduces a new level of control and additional degrees of freedom in multiple-input-multiple-output (MIMO) systems particularly for the so-called “massive MIMO” systems. To accurately assess the performance gains of these large arrays, existing azimuth-only channel models have been extended to handle 3D channels by modeling both the elevation and azimuth dimensions. In this paper, we study the channel correlation matrix of a generic ray-based 3D channel model, and our analysis and simulation results demonstrate that the 3D correlation matrix can be well approximated by a Kronecker production of azimuth and elevation correlations. This finding lays the theoretical support for the usage of a product codebook for reduced complexity feedback from the receiver to the transmitter. We also present the design of a product codebook based on Grassmannian line packing.

Kronecker product correlation model and limited feedback codebook design in a 3D channel model

Massive multiple-input multiple-output (MIMO) systems can attain a high channel capacity and spectral efficiency by using a very large antenna array at the base station (BS) However, the cost of having one radio frequency (RF) chain behind every antenna element can be prohibitive In addition, the overall power consumption of the RF hardware can be excessively high A hybrid analog-digital structure can be utilized to reduce the required number of RF chains at the BS In this paper, we present achievable rates of hybrid beamforming in multi-user MIMO (MU-MIMO) when employing only one RF chain per user The analysis and simulation results show that the asymptotic signal-plus-interference-to-noise ratio (SINR) of hybrid beamforming is reduced by a factor of π/4 compared to conventional beamforming methods, and the resulting achievable sum-rate degradation can be compensated by simply employing 27% more transmit antennas

Hybrid structure in massive MIMO: Achieving large sum rate with fewer RF chains

Mobile handsets, classified as portable devices, are regulated on the amount of user electromagnetic exposure The widely accepted exposure measurement is the specific absorption rate (SAR) Despite the prevalence of SAR constraints throughout the world, there has been barely any work on the design and analysis of communication signals for SAR-constrained wireless systems In this paper, we show that multiple-antenna systems greatly reduce the SAR measurements when proper precoders are used Fifth-generation (5G) and beyond cellular systems will be expected to support high rate uplinks, making multiple transmit antennas on user equipment a necessity Our proposed SAR-aware transmission for multiple-antenna systems can be applied in 5G handsets to reduce the SAR and increase the rate Assuming that channel knowledge is available at the transmitter and the receiver, we perform capacity analysis for multiple-antenna systems under both transmit power and SAR constraints Analytical and numerical results demonstrate substantial performance improvements over schemes that ignore the SAR constraint Our work shows that SAR-constrained precoders have structures similar to precoders designed for spatially correlated channels

Closed-Loop Precoding and Capacity Analysis for Multiple-Antenna Wireless Systems With User Radiation Exposure Constraints

A 2D antenna array introduces a new level of control and additional degrees of freedom in multiple-input-multiple-output (MIMO) systems particularly for the so-called "massive MIMO" systems. To accurately assess the performance gains of these large arrays, existing azimuth-only channel models have been extended to handle 3D channels by modeling both the elevation and azimuth dimensions. In this paper, we study the channel correlation matrix of a generic ray-based 3D channel model, and our analysis and simulation results demonstrate that the 3D correlation matrix can be well approximated by a Kronecker production of azimuth and elevation correlations. This finding lays the theoretical support for the usage of a product codebook for reduced complexity feedback from the receiver to the transmitter. We also present the design of a product codebook based on Grassmannian line packing.

Kronecker Product Correlation Model and Limited Feedback Codebook Design in a 3D Channel Model

Fifth generation (5G) and beyond cellular systems are expected to support multiple uplink transmit antennas. Previous research demonstrates that designing waveforms satisfying near field user exposure constraints affects the far-field data rates achievable by portable devices using multiple transmit antennas. Therefore, user exposure constraints need to be taken into account in the uplink transmission covariance matrix design (e.g., precoder design) for 5G. Specific absorption rate (SAR) is a widely accepted user exposure measurement used in wireless communication regulations throughout the world. In this paper, we perform sum-rate analysis for a multi-user multiple-input multiple-output (MIMO) system with SAR constraints enforced at each user. The maximum achievable sum rates for various channel state information at the transmitter scenarios are studied in this paper. The SAR-aware MIMO transmission methods are based on the modified waterfilling algorithm. Simulation results show our proposed methods outperform the conventional transmission strategy for the two user case.

Ying Dawei

Papers

Kronecker product correlation model and limited feedback codebook design in a 3D channel model

Hybrid structure in massive MIMO: Achieving large sum rate with fewer RF chains

Closed-Loop Precoding and Capacity Analysis for Multiple-Antenna Wireless Systems With User Radiation Exposure Constraints

Kronecker Product Correlation Model and Limited Feedback Codebook Design in a 3D Channel Model

Sum-Rate Analysis for Multi-User MIMO Systems With User Exposure Constraints