Low Complexity 3D Ultrasound Imaging Using Synthetic Aperture Sequential Beamforming
Jian ZhouSiyuan WeiRichard J. SampsonMing YangRungroj JintamethasawatOliver D. KripfgansJ. Brian FowlkesThomas F. WenischChaitali Chakrabarti
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Synthetic aperture sequential beamforming (SASB) is a technique to achieve range-independent resolution in 2D images with lower computational complexity compared to synthetic aperture ultrasound (SAU). It is a two stage process, wherein the first stage performs fixed-focus beamforming followed by dynamic-focus beamforming in the second stage. In this work, we extend SASB to 3D imaging and propose two schemes to reduce its complexity:(1) reducing the number of elements in both transmit and receive and (2) implementing separable beamforming in the second stage. Our Field-II simulations demonstrate that reducing transmit and receive apertures to 32×32 and 16×16 elements, respectively, and using separable beamforming reduces 3D SASB computational complexity by 15× compared to the 64×64 aperture case with almost no loss in image quality. We also describe a hardware architecture for 3D SASB that performs first-stage beamforming in the scan head, reducing the amount of data that must be transferred for offchip processing in the second stage beamformer by up to 256×. We describe an implementation approach for the second stage that performs an optimized in-place update for both steps of separable beamforming and is well suited for GPU.Keywords:
Aperture (computer memory)
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Beamforming is a well-known signal processing technique to increase the received signal strength to a chosen direction. Recently, the three dimensional (3D) beamforming technique has gained a growing interest due to its potential to enable various strategies like user specific elevation beam-forming and vertical sectorization. Compared with conventional horizontal beamforming, 3D beamforming exploits the channel's degrees of freedom in the elevation direction with the active antenna system (AAS). Currently, 3GPP is on the study phase of this advanced MIMO technique and is working on the 3D channel model specification. In this paper, we propose a new 3D beamforming algorithm which combines conventional horizontal beamforming and elevation beamforming. Simulations are used to evaluate our proposed beamforming algorithm in urban macro environment with different inter-site distance (ISD).
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In this work, coordinated beamforming and power allocation schemes are proposed for multicell downlink non-orthogonal multiple access (NOMA) systems. Beamforming is adopted at the base-station to mitigate both intercell and intracell interference whereas power-domain multiplexing between a pair of users is considered in each spatial dimension. Given the beamforming vectors, intra-pair power allocation is first determined by maximizing the weighted sum rate under worst-case interference. Then, two coordinated beamforming schemes that take into consideration the effect of power-domain multiplexing are proposed, namely, the coordinated scheduling with pair-wise zero-forcing (CSPZF) and the maximum pair-wise signal-to-leakage-plus-noise ratio (PSLNR) beamforming schemes. CSPZF beamforming utilizes the available spatial degrees of freedom at each base-station to separate signals intended for intracell user pairs as well as to eliminate strong out-of-cell interference. PSLNR beamforming, on the other hand, enhances the signal intended for each user pair while suppressing its leakage towards other users (including those in other cells). CSPZF is shown to outperform PSLNR beamforming in the high SNR regime where the performance is interference-limited and, vice versa.
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Beamforming-array signal processing is a powerful means of increasing capacity and coverage of the mobile communication networks. It supports the next generation broadband cellular system to efficiently carry populated traffic over a limited spectrum due to its co-channel interference mitigation capability. This paper presents performance comparison of three beamforming methods namely null steering, minimum variance distortionless response (MVDR) and minimum mean square error (MMSE) beamforming. It is observed that MMSE beamforming is most suitable for practical non-line-of-sight multipath environment. The work is further extended to downlink beamforming problem for multicell network which is formulated as minimization of transmitted power by all base stations (BSs) subject to SINR constraints at each mobile. The conventional per cell basis beamforming and coordinated multicell beamforming are implemented to achieve downlink transmit power optimization using downlink beamforming. Both algorithms use uplink (UL)-downlink (DL) duality concept to solve complicated DL beamforming by using dual uplink problem. Per cell basis beamforming treats intercell interferences as a part of background noise while coordinated multicell beamforming considers intercell interferences for weight vector calculation. Thus, per cell basis optimization does not lead to a joint optimal solution which is possible by coordinated multicell beamforming. The important feature of coordinated beamforming algorithm is that, it leads to distributed implementation in time division duplex (TDD) system. The distributed implementation is less complex and requires only beamforming level coordination unlike centralized implementation which requires system level coordination and thus it is more complex. Thus, in this paper per cell basis beamforming and coordinated multicell beamforming has been implemented and compared for mobile wimax multicell network. The simulation results proved that coordinated beamforming outperforms per cell basis beamforming for different values of SINR and user locations.
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This paper presents a distributed beamforming technique that addresses the effect of inter-cell interference on the downlink of cellular communications systems. The beamforming weights are computed in a distributed manner at each transmit sector antenna array without the need for inter-sector communication. The beamforming weights are chosen to compromise between maximizing the power to the served user from each sector while minimizing the interference caused to users served in adjacent sectors. The extensions of this method for variable levels of channel state information feedback and multiple receiver antennas are introduced. Beamforming codebooks with power variations across antennas are presented. We show how users can additionally feed back the fraction of interference caused by each interfering sector to incorporate the urgency of interference avoidance into the transmitter optimization.
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Opportunistic beamforming is a promising technique for downlink channels in cellular systems. When opportunistic beamforming is to support multiple users at a time, it is important to form multiple beams with as little interference as possible. In the conventional approach with limited feedback of channel state information from users, the best beamforming matrix can be selected from a set of multiple beamforming matrices. Thus, at each time when a different set of users are selected by a scheduler, a new beamforming matrix has to be found, which may require excessive complexity. To avoid this problem, in this paper, we propose an opportunistic beamforming approach with a single fixed beamforming matrix for stationary users. Since the beams are fixed, we only need to perform user selection (and power allocation if necessary). It is also shown that the proposed approach is suited for a distributed virtual antenna array built by multiple base station or access point units, since the intercorrelation between the users' channel vectors in this case allows effective opportunistic beamforming based on user classification in conjunction with a single beamforming matrix.
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In the search for enhanced wireless communication systems, multibeam phased array receivers have gained prominence. They promise to significantly boost data rates, reduce latency, and improve reliability. However, implementing multibeam receivers with traditional beamforming techniques can be challenging due to the high computational demands and the need for multiple radio frequency (RF) chains. Hybrid beamforming combines the advantages of digital and analog beamforming to strike a balance between performance and complexity. Our research delves into the following aspects of Hybrid beamforming for multibeam phased array receivers: Reduced Hardware Complexity: By blending digital and analog beamforming, we reduce the number of required RF chains, making multibeam receivers more cost-effective. Enhanced Beam Steering: Hybrid beamforming maintains precise control over multiple beams, ensuring efficient signal reception and transmission. Real-World Applications: We discuss practical applications in 5G and beyond, satellite communications, and radar systems. The paper delves into the fundamental concepts of analog and digital beamforming, illustrating their respective strengths and limitations. It then presents the architecture of hybrid beamforming systems, emphasizing the synergistic integration of analog and digital components. Special attention is given to the design considerations of beamforming networks, antenna arrays, and the beam steering mechanism. KEYWORDS Hybrid Beamforming , Phased Array , Multi-Beam , Analog Beamforming , Digital Beamforming , Beamforming Networks , Antenna Array , Beam Steering , Spatial Multiplexing , Precoding , Channel Estimation , Interference Mitigation , Power Consumption , Millimeter Wave (mmWave) , 5G and Beyond .
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This chapter focuses on the beamforming mechanism and protocols that enables fast link setup in 5G Millimeter (mm) Wave directional links. In general, there are two kinds of beamforming: adaptive beamforming and switched beamforming. There are three kinds of beamforming architectures, namely, analog beamforming, digital beamforming, and the hybrid beamforming. Beamsearching in the switched beamforming only depends on the measured signal quality of each predefined beams. Transmitter and receiver devices exchange their training packet to measure the channel quality for each beam candidate. Switched beamforming requires predefined codebook so that the beam candidates can be generated directly from the codebook. Codebook is defined specifically in IEEE 802.15.3c, but there is no specific codebook defined in IEEE 802.11ad. N-phase beamforming is similar to IEEE 802.15.3c. However, this beamforming is designed to accommodate the availability of higher phase shift resolution. Digital Fourier Transmorm (DFT)-based beamforming gives more flexible beams where each beam can reach the same maximum gain.
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As the demand for data rate increases, interference management becomes more important, especially in small cell environment of emerging wireless communication systems. In this paper, we investigate the machine learning-based beamforming design in two-user MISO interference channels. To see the possibilities of machine learning in beamforming design, we consider simple beamforming, where each user chooses one between two popular beamforming schemes, which are the maximum ratio transmission (MRT) beamforming and the zero-forcing (ZF) beamforming. We first propose a machine learning structure that takes transmit power and channel vectors as input and then recommends two users' choices between MRT and ZF as output. The numerical results show that our proposed machine learning-based beamforming design well finds the best beamforming combination and achieves the sum-rate more than 99.9% of the best beamforming combination.
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Opportunistic beamforming is a promising technique for downlink channels in cellular systems. When opportunistic beamforming is to support multiple users at a time, beams should be formed to avoid interference and this requires the feedback of channel state information (CSI) from users to a base station (BS). With limited feedback, to minimize the impact of interference, the best beamforming matrix can be selected from a set of multiple beamforming matrices. Thus, when a different set of users are to be supported by a scheduler, a new beamforming matrix has to be selected, which may require excessive complexity. To avoid this problem, in this paper, we propose an opportunistic beamforming approach with single beamforming matrix. In addition, we show that the proposed approach suits for a virtual antenna array where multiple BS units form a transmit antenna array.
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This paper proposes a scheme combining multi-cell downlink joint transmission(JT) with 3- Dimensional(3D) beamforming. The proposed scheme is based on the following two observations: 1) The performance of multi-cell joint transmission is highly dependent on the received signal strength from the coordinated cells, 2) Interference may become more severe at the cell boundary due to the extremely flat beams serving the cell edge users with 3D beamforming. In the proposed scheme, users at the cell boundary are served with JT and 3D beamforming simultaneously, and those at the cell center are served with 3D beamforming. Simulation results based on LTE-Advanced systems show that significant gains can be achieved by the scheme, with about 14% gain on cell average spectral efficiency and about 58% gain on edge user spectral efficiency compared to traditional single cell transmission with 2-Dimensional(2D) beamforming.
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