Beam Management for Millimeter Wave Beamspace MU-MIMO Systems

Millimeter wave (mmWave) communication has attracted increasing attention as a promising technology for 5G networks. One of the key architectural features of mmWave is the use of massive antenna arrays at both the transmitter and the receiver sides. Therefore, by employing directional beamforming (BF), both mmWave base stations (MBSs) and mmWave users (MUEs) are capable of supporting multi-beam simultaneous transmissions. However, most researches have only considered a single beam, which means that they do not make full potential of mmWave. In this context, in order to improve the performance of short-range indoor mmWave networks with multiple reflections, we investigate the challenges and potential solutions of downlink multi-user multi-beam transmission, which can be described as a high-dimensional (i.e., beamspace) multi-user multiple-input multiple-output (MU-MIMO) technique, including multi-user BF training, simultaneous users' grouping, and multi-user multibeam power allocation. Furthermore, we present the theoretical and numerical results to demonstrate that beamspace MU-MIMO compared with single beam transmission can largely improve the rate performance of mmWave systems.Comment: The sixth IEEE/CIC International Conference on Communications in China (ICCC2017

A survey on hybrid beamforming techniques in 5G : architecture and system model perspectives

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

A Fast Effective Greedy Approach for MU-MIMO Beam Selection in mm-Wave and THz Communications

This paper addresses the beam-selection challenges in Multi-User Multiple Input Multiple Output (MU-MIMO) beamforming for mm-wave and THz channels, focusing on the pivotal aspect of spectral efficiency (SE) and computational efficiency. We introduce a novel approach, the Greedy Interference-Optimized Singular Vector Beam-selection (G-IOSVB) algorithm, which offers a strategic balance between high SE and low computational complexity. Our study embarks on a comparative analysis of G-IOSVB against the traditional IOSVB and the exhaustive Singular-Vector Beamspace Search (SVBS) algorithms. The findings reveal that while SVBS achieves the highest SE, it incurs significant computational costs, approximately 162 seconds per channel realization. In contrast, G-IOSVB aligns closely with IOSVB in SE performance yet is markedly more computationally efficient. Heatmaps vividly demonstrate this efficiency, highlighting G-IOSVB's reduced computation time without sacrificing SE. We also delve into the mathematical intricacies of G-IOSVB, demonstrating its theoretical and practical superiority through rigorous expressions and detailed algorithmic analysis. The numerical results illustrate that G-IOSVB stands out as an efficient, practical solution for MU-MIMO systems, making it a promising candidate for high-speed, high-efficiency wireless communication networks.Comment: Accepted for Lecture presentation at the 58th Annual Conference on Information Sciences and Systems, to be held at Princeton University from March 13-15, 202

Energy and spectral-efficient lens antenna subarray design in MmWave MIMO Systems

Lens antenna subarray (LAS) is one of the recently introduced technologies for future wireless networks that significantly improves the energy efficiency of multiple-input multiple-output (MIMO) systems while achieving higher spectral efficiency compared to single-lens MIMO systems. However, a control mechanism for the LAS-MIMO design is considered a challenging task to efficiently manage the network resources and serve multiple users in the system. Therefore, in this paper, a sub-grouped LAS-MIMO architecture along with a hybrid precoding algorithm are proposed to reduce the cost and hardware overhead of traditional hybrid MIMO systems. Specifically, the LAS structure is divided into sub-groups to serve multiple users with different requirements, and an optimization problem based on the achievable sum-rate is formulated to maximize the spectral efficiency of the system. By splitting the sum-rate problem into sub-rate optimization problems, we develop a low-complexity hybrid precoding algorithm to effectively control the proposed architecture and maximize the achievable sum-rate of each subgroup. The proposed precoding algorithm selects the beam of each lens from a predefined set within a subgroup that maximizes the subgroup sum-rate, while the phase shifters and digital precoders in each subgroup are computed independently. The link between subgroups is updated based on successive interference cancelation to minimize interference between users of different subgroups. Our analysis and simulation results show that the proposed precoding algorithm of the sub-grouped LAS-MIMO architecture performs almost as well as traditional fully-connected hybrid MIMO systems in terms of spectral efficiency at low and high signal-to-noise ratio (SNR). It also outperforms traditional fully-connected and sub-connected hybrid MIMO systems in terms of energy efficiency, even when a large number of lenses are employed.National Science Foundation (NSF

Non-Orthogonal Multiple Access For Near-Field Communications

The novel concept of near-field non-orthogonal multiple access (NF-NOMA) communications is proposed. The near-filed beamfocusing enables NOMA to be carried out in both angular and distance domains. Two novel frameworks are proposed, namely, single-location-beamfocusing NF-NOMA (SLB-NF-NOMA) and multiple-location-beamfocusing NF-NOMA (MLB-NF-NOMA). 1) For SLB-NF-NOMA, two NOMA users in the same angular direction with distinct quality of service (QoS) requirements can be grouped into one cluster. The hybrid beamformer design and power allocation problem is formulated to maximize the sum rate of the users with higher QoS (H-QoS) requirements. To solve this problem, the analog beamformer is first designed to focus the energy on the H-QoS users and the zero-forcing (ZF) digital beamformer is employed. Then, the optimal power allocation is obtained. 2) For MLB-NF-NOMA, the two NOMA users in the same cluster can have different angular directions. The analog beamformer is first designed to focus the energy on both two NOMA users. Then, a singular value decomposition (SVD) based ZF (SVD-ZF) digital beamformer is designed. Furthermore, a novel antenna allocation algorithm is proposed. Finally, a suboptimal power allocation algorithm is proposed. Numerical results demonstrate that the NF-NOMA can achieve a higher spectral efficiency and provide a higher flexibility than conventional far-field NOMA

Design Simulation and Performance Assessment of Improved Channel Estimation for Millimeter Wave Massive MIMO Systems

In this paper, we have optimize specificities with the use of massive MIMO in 5 G systems. Massive MIMO uses a large number, low cost and low power antennas at the base stations. These antennas provide benefit such as improved spectrum performance, which allows the base station to serve more users, reduced latency due to reduced fading power consumption and much more. By employing the lens antenna array, beam space MIMO can utilize beam selection to reduce the number of required RF chains in mm Wave massive MIMO systems without obvious performance loss. However, to achieve the capacity-approaching performance, beam selection requires the accurate information of beam space channel of large size, which is challenging, especially when the number of RF chains is limited. To solve this problem, in this paper we propose a reliable support detection (SD)-based channel estimation scheme. In this work we first design an adaptive selecting network for mm-wave massive MIMO systems with lens antenna array, and based on this network, we further formulate the beam space channel estimation problem as a sparse signal recovery problem. Then, by fully utilizing the structural characteristics of the mm-wave beam space channel, we propose a support detection (SD)-based channel estimation scheme with reliable performance and low pilot overhead. Finally, the performance and complexity analyses are provided to prove that the proposed SD-based channel estimation scheme can estimate the support of sparse beam space channel with comparable or higher accuracy than conventional schemes. Simulation results verify that the proposed SD-based channel estimation scheme outperforms conventional schemes and enjoys satisfying accuracy even in the low SNR region as the structural characteristics of beam space channel can be exploited