Channel Estimation for RIS-Aided mmWave Massive MIMO System Using Few-Bit ADCs
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Millimeter wave (mmWave) massive multiple-input multiple-output (massive MIMO) is one of the most promising technologies for the fifth generation and beyond wireless communication system. However, a large number of antennas incur high power consumption and hardware costs, and high-frequency communications place a heavy burden on the analog-to-digital converters (ADCs) at the base station (BS). Furthermore, it is too costly to equipping each antenna with a high-precision ADC in a large antenna array system. It is promising to adopt low-resolution ADCs to address this problem. In this letter, we investigate the cascaded channel estimation for a mmWave massive MIMO system aided by a reconfigurable intelligent surface (RIS) with the BS equipped with few-bit ADCs. Due to the low-rank property of the cascaded channel, the estimation of the cascaded channel can be formulated as a low-rank matrix completion problem. We introduce the Bayesian optimal inference framework to tackle with the information loss caused by quantization. To implement the estimator and achieve the matrix completion, we use efficient bilinear generalized approximate message passing (BiG-AMP) algorithm. Extensive simulation results verify that our proposed method can accurately estimate the cascaded channel for the RIS-aided mmWave massive MIMO system with low-resolution ADCs.The processing of signals received from an array of sensors, termed beamforming, can result in the improved performance of systems designed for the detection and estimation of propagating signals. Several approaches to sonar beamforming are presented. The basic concepts behind the beamforming of signals obtained from an array of sensors are presented and demonstrated. Conventional and modern beamforming approaches are motivated and defined, and the advantages and drawbacks of each are discussed. The potential power of modern beamforming techniques is illustrated through a computer simulation evaluating the ability of several beamforming techniques to resolve between two closely spaced sources. The need of beamforming algorithm evaluation in conditions characteristic of the undersea environment is highlighted.< >
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Triplet arrays are single line arrays with three hydrophones on a circular section of the array. The triplet structure provides immediate port-starboard (PS) discrimination. This paper discusses the theoretical and experimental performance of triplet arrays. Results are obtained on detection gain and PS discrimination in several environmental conditions: sea noise, flow noise, coastal reverberation, jammers. New algorithms on adaptive triplet beamforming are applied to data of a sea-trial with a low frequency active sonar. The adaptive beamforming results are compared to other triplet beamforming techniques (optimum gain and cardioid beamforming). It shows that adaptive triplet beamforming outperforms the other beamforming algorithms, either in PS discrimination or in detection. In conclusion, adaptive beamforming appears to be the ultimate solution for triplet beamforming.
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In this thesis, we study beamforming techniques that offer opportunities for 3D transesophageal echocardiography imaging, especially to achieve higher frame rates. In 3D TEE with a matrix transducer, two main challenges are to connect a large number of elements to a standard ultrasound system and to achieve a high volume rate (>200 Hz). We develop a prototype miniaturized matrix transducer for pediatric patients with micro-beamforming to reduce the channel count. Initially, we propose two dual stage beamforming techniques for 1D arrays to produce high-quality images with reduced channel count: one using fixed focused receive and another with a simple summation in receive (no delays). Because of their inapplicability to the prototype transducer, we propose multiline 3D ultrasound beamforming schemes that utilize the micro-beamforming capabilities. The proposed beamforming schemes use an angle-weighted combination of the neighboring overlapping sub-volumes to suppress the crossover artifacts that are typical for parallel beamforming and produce high-quality images at a high volume rate (~300 Hz). A similar beamforming scheme adapted for a newly designed prototype matrix adult TEE probe is used for in vivo 3D imaging of the heart of a healthy adult pig to produce good quality 3D images at a high frame rate. The proposed 3D beamforming scheme can easily be adapted for matrix probes with micro-beamforming capabilities to produce good quality volume images at a high volume rate, even for a very different layout of the transmit and receive arrays.
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Downlink beamforming for modile communication systems based on antenna arrays have been discussed. Computer simulations for circular array and linear array have also been carried out. The results of simulations show that circular array or linear array can be used in different downlink beamforming model, which means that circular array is suitable for switch-beam downlink beamforming, while linear array for selective downlink beamforming. If Chebyshev linear array in selective downlink beamforming model is adopt, the beamforming will be optimized. In addition, the complexity of system will be reduced greatly, which makes beamforming easier to be realized.
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Ever since the detection of radio signals, technology has strived to improve the performance of the hardware associated with detecting and observing faint radio sources by improving signal processing and detection techniques. Phased array feeds (PAFs) for radio telescopes can yield in an increase in the survey speed and field of view for reflector antennas. Beamforming, calibration, and imaging are some of the challenges that need to be addressed in order to further the development of PAFs. There is a trade-off between achieving high sensitivity and maintaining a stable clean beam pattern when it comes to beamforming design strategies. A new beamforming strategy is discussed in this paper which is sub optimal but can be improved with time.
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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.
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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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A beamforming method based on genetic algorithms (GAs) is proposed for antenna arrays in the presence of strong platform effects. A GA is used to maximize the mainbeam radiation and minimize sidelobe levels based on the active element patterns of the array. Simulation results show that the array excitations optimized by the GA can achieve superior beamforming performance than those from array theory or phase conjugation. Experimental results collected from a seven-element circular array further demonstrate the beamforming and direction finding performance of the GA based beamformer. In addition, an array element position optimization is carried out. Simulation results show further improvement in the beamforming performance.
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In this letter, the beamforming scheme based on random frequency diverse array (RFDA) is newly investigated to enhance the performance of covert mmWave communications. First, the closed-form expressions of covertness constraint are derived for the RFDA and the conventional phase array (PA) beamforming schemes, respectively. Then, the optimal transmit power and blocklength maximizing the average effective covert throughput (AECT) are derived for both beamforming schemes. Considering the pessimistic scenarios that Willie locates in its desired direction as Bob (but different distances), our examination shows the enhancement of maximum AECT by adopting the RFDA beamforming scheme. Besides, in this case, the maximum AECT for the RFDA beamforming scheme can be improved while that for the PA beamforming scheme remains unchanged as the number of antennas enlarges. Furthermore, it is revealed that the superior performance of the RFDA beamforming scheme is influenced by Willie's location, and the range of Willie in which the RFDA beamforming scheme outperforms the PA beamforming scheme is obtained.
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The conventional beamforming can only imaging sound source in far-field environment. In this paper,two different vector weightings are introduced to improve the effect of imaging based on near-field beamforming model. Inversely proportional weights beamforming and minimum variance distortion-less response beamforming are described. Two methods are simulated and their results show effectiveness.
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