Selective Beam Research Articles

Beam Selection for Wideband Millimeter Wave MIMO Relying on Lens Antenna Arrays

Beamspace multi-input-multi-output (MIMO) relying on lens antenna arrays can significantly reduce the number of radio-frequency chains in millimeter-wave (mmWave) communication systems through beam selection. However, the beamforming gain is actually frequency-dependent in wideband mmWave MIMO systems. This phenomenon is called beam squint which will deteriorate the system's performance when traditional beam selection methods are used. To solve this problem, we propose a wideband beam selection method for mmWave MIMO systems relying on lens antenna arrays. First, we select one beam with the maximal energy averaged over the whole band for each user and then we sequentially select the beams that contribute the most to the sum-rate. The performance analysis of the proposed wideband beam selection method is also presented. Numerical results show that the proposed method achieves higher sum-rate and energy efficiency compared with its traditional counterparts.

Joint Beam and Resource Allocation in 5G mmWave Small Cell Systems

Resource allocation in mmWave small cell is a key issue of the fifth generation (5G) systems. To solve this problem, we first present a hybrid beamforming structure for base station of small cell, which consists of orthogonal frequency division multiplexing (OFDM), identity matrix and switched-beam. Next, we formulate the joint allocation of the beam and transmitted power on the sub-carriers into a mixed integer non-linear programming problem (MINLP). Due to the non-convexity of this problem, we decompose it into two subproblems which are the beam selection and the power allocation. For the beam selection, we propose an algorithm based on cooperative games. For the power allocation, we present an optimal and sub-optimal solution based on Lagrange duality and non-cooperative games respectively. Simulation results show that the beam allocation algorithm proposed in this paper can effectively improve the sum rate of the system, and the optimal power allocation solution is far superior to the sub-optimal one in sum rate.

Spatial overlapping index based joint beam selection for millimeter-wave multiuser MIMO systems

In this paper, beam selection for millimeter-wave multiuser multi-input multi-output (MIMO) systems that employ zero-forcing based analog-digital hybrid processing is investigated. The existing approaches have tackled neither the joint beam selection at both sides of the communication system nor the strong interference imposed by the mobile stations (MSs) which share beams with some other MSs. Hence, by first assuming full channel state information, the problem of joint beam selection is formulated and the concept of spatial overlapping index (SOI) is proposed to deal with the strong interference imposed by the MSs which share beams with some other MSs. Furthermore, by considering the realistic scenario of having channel estimation, the joint beam selection is divided and integrated into the channel estimation process, and the SOI is redefined based on the channel estimates. Finally, our analysis and simulations show that the upper bound of the sum rate increases with the number of MSs and the number of base station antennas, the proposed approach outperforms the existing approaches, and the computational complexity of the proposed approach is close to or lower than that of the existing approaches.

Spatio-Radio Resource Management and Hybrid Beamforming for Limited Feedback Massive MIMO Systems

In this paper, a joint spatio–radio frequency resource allocation and hybrid beamforming scheme for the massive multiple-input multiple-output (MIMO) systems is proposed. We consider limited feedback two-stage hybrid beamformimg for decomposing the precoding matrix at the base-station. To reduce the channel state information (CSI) feedback of massive MIMO, we utilize the channel covariance-based RF precoding and beam selection. This beam selection process minimizes the inter-group interference. The regularized block diagonalization can mitigate the inter-group interference, but requires substantial overhead feedback. We use channel covariance-based eigenmodes and discrete Fourier transforms (DFT) to reduce the feedback overhead and design a simplified analog precoder. The columns of the analog beamforming matrix are selected based on the users’ grouping performed by the K-mean unsupervised machine learning algorithm. The digital precoder is designed with joint optimization of intra-group user utility function. It has been shown that more than 50 % feedback overhead is reduced by the eigenmodes-based analog precoder design. The joint beams, users scheduling and limited feedbacK-based hybrid precoding increases the sum-rate by 27.6 % compared to the sum-rate of one-group case, and reduce the feedback overhead by 62.5 % compared to the full CSI feedback.

Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems With Limited Feedback Using ESPAR Antennas

We consider an opportunistic cognitive radio (CR) system consisting of a primary user (PU), secondary transmitter (SUtx), and secondary receiver (SUrx), where SUtx is equipped with an electrically steerable parasitic array radiator (ESPAR) antenna with beam steering capability for sensing and communication, and there is a limited feedback channel from SUrx to SUtx. Taking a holistic approach, we develop a framework for integrated sector-based spectrum sensing and sector-based data communication. Upon sensing the channel busy, SUtx determines the beam corresponding to PU's orientation. Upon sensing the channel idle, SUtx transmits data to SUrx, using the selected beam corresponding to the strongest channel between SUtx and SUrx. We formulate a constrained optimization problem, where SUtx- SUrx link ergodic capacity is maximized, subject to average transmit power and interference constraints, and the optimization variables are sensing duration, thresholds of channel quantizer at SUrx, and transmit power levels at SUtx. Since this problem is non-convex we develop a suboptimal computationally efficient iterative algorithm to find the solution. Our numerical results quantify the capacity improvement provided by the ESPAR antenna and demonstrate that our CR system yields lower outage and symbol error probabilities, compared with a CR system that its SUtx has an omni-directional antenna.

A decentralized beam selection for mmWave beamspace multi-user MIMO system

A millimeter beamspace multi-user multi-input-multi-output system is a key enabling technology of 5G to fulfil the demand for high data rate. But, it suffers from high RF complexity. However, RF Complexity can be reduced by the beam selection algorithm. Hence, few beam selection algorithms were proposed with a centralized approach. In this paper, a decentralized beam selection algorithm for millimeter wave beamspace multi-user MIMO is discussed. Unlike the centralized beam selection algorithm, the decentralized beam selection algorithm doesn’t require a central unit or access point to select beams. The users themselves play an active role to select beams by sharing the local information with the neighbour users. This is also the requirement of a dynamic network. The performance thoroughly confides on the network cooperation to select beams in an efficient manner. The proposed decentralized beam selection algorithm enables the access point to be free from handling of a large channel matrix. Therefore, this low complexity beam selection algorithm is a better alternative. The performance and complexity of the proposed beam selection algorithm are examined in the following section.

Scheme of high-resolution identification and selection of secondary ions for mass measurements with the Rare-RI Ring

To achieve high-resolution selection and separation of mono-isotopic beams through projectile fragmentation or in-flight fission and to efficiently transport the secondary beams to the Rare-RI Ring (R3) for mass determination, the BigRIPS separator combined with the High-resolution Achromatic (HA) beam-line of SHARAQ is served as a two-stage separator. The first stage from F0 to F2 is used for separation of the nuclei of interest through a Bρ-ΔE-Bρ method and the second stage from F3 to S0 is employed for identification of the beam with a Bρ-ΔE-TOF method. With this scheme, all the secondary ions can be well separated on an event by event basis and be utilized for mass measurements by two complementary methods: the conventional magnetic-rigidity-time-of-flight (Bρ-TOF) method employing the BigRIPS-HA beam-line to measure exotic nuclides within 1 μ s and the newly established isochronous mass spectrometry (IMS) approach via the R3 with a measurement duration less than 1 ms. This report presents the technique advances of the BigRIPS-HA-SHARAQ-R3 as a separator/spectrometer and give a brief description of its application to the complementary TOF methods for mass measurements at RIBF.

Tracking Position and Orientation Through Millimeter Wave Lens MIMO in 5G Systems

Millimeter wave signals and large antenna arrays are considered enabling technologies for future 5G networks. Despite their benefits for achieving high data rate communications, their potential advantages for tracking of the location and rotation angle of the user terminals are not well investigated. A joint heuristic beam selection and user position and orientation tracking approach is proposed. First, the user location is tracked in the uplink by joint beam selection together with time-of-arrival (TOA) and angle-of-arrival (AOA) tracking at the base station (BS). Then, the user rotation angle is obtained using the location information by joint beam selection and tracking at the mobile station (MS). The beam selection, TOA and AOA tracking, at the BS and MS are performed during the data transmission phase. Numerical results demonstrate that the proposed method performs close to the estimated position and rotation angle in the training phase with reduced complexity and reduced number of required pilots for the estimation.

Beamforming Design in SWIPT-Based Joint Multicast-Unicast mmWave Massive MIMO With Lens-Antenna Array

In this letter, we study the beamforming design in a lens-antenna array-based joint multicast-unicast millimeter wave massive MIMO system, where the simultaneous wireless information and power transfer at users is considered. First, we develop a beam selection scheme based on the structure of the lens-antenna array and then, the zero forcing precoding is adopted to cancel the inter-unicast interference among users. Next, we formulate a sum rate maximization problem by jointly optimizing the unicast power, multicast beamforming, and power splitting ratio. Meanwhile, the maximum transmit power constraint for the base station and the minimum harvested energy for each user are imposed. By employing the successive convex approximation technique, we transform the original optimization problem into a convex one, and propose an iterative algorithm to solve it. Finally, simulation results are conducted to verify the effectiveness of the proposed schemes.

Research on image monitoring method of electron beam selection melting

In order to overcome the problem that the lack of real-time detection technology and the existing detection methods cannot select the process area flexibly in the process of electron beam selective melting, this paper presents a digital electronic imaging method which can monitor the roughness and tiny flaws on the surface of components layer by layer. The digital electronic images were produced by detecting both secondary electrons (SE) and backscattered electrons (BSE) originating from interactions between the electron beam and the metal powder. The imaging principle and the hardware circuit of the system are introduced in detail. Finally, the effectiveness of this design is verified by the experiments.

Acoustic Beam Characterization and Selection for Optimized Underwater Communication

To increase underwater acoustic signal detectability and conserve energy, nodes leverage directional transmissions. In addition, nodes operate in a three-dimensional (3D) environment that is categorized as inhomogeneous where a propagating signal changes its direction based on the observed sound speed profile (SSP). Coupling 3D directional transmission with frequent node drifts and the varying underwater SSP complicates the process of selecting suitable transmission angles to maintain underwater communication links. Fundamentally, utilizing directional transmission while nodes are drifting causes breaks in established communication links and thus nodes need to find new angles to reestablish these links. Moreover, selecting arbitrary transmission angles may lead to overlapping beams or result in leaving an underwater region uncovered. To tackle the abovementioned challenges, this paper proposes an autonomous beam selection approach that optimizes underwater communication by selecting non-overlapping beams while mitigating the possibility of missing a region, i.e., maximize coverage. Such optimization is achieved by utilizing a structured angle selection mechanism that accounts for the capability of the used transducer. Moreover, we introduce an algorithm suited for resource constrained nodes to classify rays into different types. Then we divide the underwater medium into regions where each region is identified by the limits of the coverage area of each ray type. Finally, we utilize the limits of these regions to aid nodes in selecting the best ray to reestablish communication with drifted nodes. We validate our contribution through simulation where actual SSPs are leveraged to validate the beam classification process.

Multi-Armed Bandit Beam Alignment and Tracking for Mobile Millimeter Wave Communications

We propose a novel beam alignment and tracking algorithm for time-varying millimeter wave channels with a dynamic channel support. Millimeter wave beam alignment is challenging due to the expected large number of antennas. A multi-armed bandit training beam selection policy is used to balance exploration of the set of feasible beams. We track the channel using a synthesis of sparse Bayesian learning and Kalman filtering and smoothing. Results show our algorithm has a more rapid rate of initial beam alignment compared to other beam selection policies and, for dynamic channel support, long-term beamforming gain commensurate to omni-directional training.

A Novel Two-Stage Beam Selection Algorithm in mmWave Hybrid Beamforming System

A hybrid beamforming structure, which consists of digital precoding and analog beamforming, is a low-cost solution to millimeter wave (mmWave) large-scale antenna systems. In this letter, we study the sum rate maximization problem where an analog beamformer is selected from a discrete codebook. A two-stage scheme is proposed in order to avoid an exhaustive search. First, the lower bound of the sum rate is derived, and the trace inverse of the equivalent channel is determined as a novel metric for beam selection. Based on this metric, we formulate a convex problem to derive an initial beam set. Finally, an iterative algorithm is designed to update beams for further performance improvement. Simulation results demonstrate that the proposed scheme achieves a near-optimal sum rate performance and outperforms existing schemes.

Low-Complexity Beam Selection Algorithms for Millimeter Wave Beamspace MIMO Systems

We consider the downlink multi-user multiple-input multiple-output (MIMO) systems, operating at millimeter-wave frequencies and equipped with a large number of antenna elements at the access point. Beamspace MIMO with beam selection offers an attractive solution for reducing the number of required radio frequency chains in such systems. We propose two beam selection algorithms. The first one is a heuristic greedy algorithm that enjoys low computational complexity with moderate performance. By modeling beam selection as maximum weight matching over a bipartite graph, we propose beam selection based on the Kuhn–Munkres algorithm and, importantly, introduce a new formal framework for beam selection.

Joint User Scheduling and Beam Selection for Maritime Large-scale Antenna Systems

Since the overall distribution of users in the sea area is sparse, it will appear densely in a local angle domain. Specifically, the 3D massive MIMO antenna system are established, which are with the ability to distinguish users in the same horizontal direction as well as vertical direction. According to this, a joint user scheduling and beam selection scheme based on the automatic identification system (AIS) is proposed to solve the problems that of the interference cancellation for the users in the angle domain. In particular, the proposed scheme divides the beam according to the users’ location information. Furthermore, we select the user with the highest priority in the beam to form a set of the users in serving, in the meanwhile, the greedy algorithm is used to schedule the user combination to achieve the greatest sum rate. By means of the numerical results, it is shown that the proposed scheme can be used to schedule and serve users in the case of crowded angle domain, and the scheme can obtain near-optimal sum rate.

Standalone and Non-Standalone Beam Management for 3GPP NR at mmWaves

The next generation of cellular networks will exploit mmWave frequencies to dramatically increase the network capacity. The communication at such high frequencies, however, requires directionality to compensate the increase in propagation loss. Users and base stations need to align their beams during both initial access and data transmissions, to ensure the maximum gain is reached. The accuracy of the beam selection, and the delay in updating the beam pair or performing initial access, impact the end-to-end performance and the quality of service. In this paper we will present the beam management procedures that 3GPP has included in the NR specifications, focusing on the different operations that can be performed in Standalone (SA) and in Non-Standalone (NSA) deployments. We will also provide a performance comparison among different schemes, along with design insights on the most important parameters related to beam management frameworks.

Transmit Beam Selection Scheme for Massive MIMO Using Expected Beam Responses

Transmit Beam Selection Scheme for Massive MIMO Using Expected Beam Responses

OC-0182 Automated (non-coplanar) beam selection for IMRT in young female lymphoma patients reduces OAR doses

OC-0182 Automated (non-coplanar) beam selection for IMRT in young female lymphoma patients reduces OAR doses

Beam Selection Based on Sequential Competition

We present a novel M-ary sequential test for beam selection when knowledge about the SNR operating point is not available. The proposed sequential test adaptively changes the test length (the number of observations) according to the SNR operating point to achieve the desired performance. Moreover, to achieve the same performance in terms of captured signal power, the sequential competition test requires on average less observations (particularly in the lower SNR regime) in comparison to a perfectly tuned fixed length test assuming genie knowledge.

Evaluation of Multi-Beam Massive MIMO Considering MAC Layer Using IEEE802.11ac and FDD-LTE

Massive multiple-input multiple-output (MIMO) transmission has attracted attention as a key technology for use in fifth-generation mobile communication systems. Multi-beam massive MIMO systems that apply beam selection in analog components and blind algorithms in digital components to eliminate the requirement for channel state information have been proposed as a method for reducing overhead. In this study, we developed an adaptive modulation scheme for implementing multi-beam massive MIMO and used computer simulation to compare it with digital and analog–digital hybrid beam-forming methods. The effectiveness of the proposed system was verified in a medium access control layer based on the IEEE802.11ac and frequency division duplex-LTE representative wireless communication standards.