Showing 6 results for Beamforming
Sayed Mahmoud Sakhaei, A.mahlooji Far, Hassan Ghassemian,
Volume 2, Issue 2 (4-2006)
Abstract
Contrast resolution and detail resolution are two important parameters in
ultrasound imaging. This paper presents a new method to enhance these parameters,
simultaneously. A parallel auxiliary beamformer has been employed whose weightings are
such that an estimation of the leaked signal through the main beamformer is obtained. Then
the output of main beamformer is modified according to the estimated leaked signal. The
efficiency of our adaptive method is demonstrated by applying it over an experimental data
set and provided an enhancement of about 22 percent in lateral resolution and 15-20 dB in
contrast resolution. This method also has the advantages of simplicity and possibility of real
time implementation.
M. Dosaranian Moghadam, H. Bakhshi, G. Dadashzadeh,
Volume 6, Issue 3 (9-2010)
Abstract
In this paper, we propose smart step closed-loop power control (SSPC)
algorithm and base station assignment based on minimizing the transmitter power (BSAMTP)
technique in a direct sequence-code division multiple access (DS-CDMA) receiver in
the presence of frequency-selective Rayleigh fading. This receiver consists of three stages.
In the first stage, with conjugate gradient (CG) adaptive beamforming algorithm, the
desired users’ signal in an arbitrary path is passed and the inter-path interference is
canceled in other paths in each RAKE finger. Also in this stage, the multiple access
interference (MAI) from other users is reduced. Thus, the matched filter (MF) can be used
for the MAI reduction in each RAKE finger in the second stage. Also in the third stage, the
output signals from the matched filters are combined according to the conventional
maximal ratio combining (MRC) principle and then are fed into the decision circuit of the
desired user. The simulation results indicate that the SSPC algorithm and the BSA-MTP
technique can significantly improve the network bit error rate (BER) in comparison with
other algorithms. Also, we observe that significant savings in total transmit power (TTP)
are possible with our proposed methods.
N. Noori,
Volume 10, Issue 2 (6-2014)
Abstract
In this paper, an optimal approach to design wideband tapped-delay line (TDL) array antenna is proposed. This approach lets us control the array angular and frequency response over a wide frequency band. To this end, some design restrictions are defined and a multi-objective optimization problem is constructed by putting the individual restrictions together. The optimal weights of the TDL processor are determined through solving this multi-objective problem. A design example is presented to show performance of the proposed method and compare the array response with those previously published in the literature.
P. Ramezanpour, M. Aghababaie, M. R. Mosavi, D. M. de Andrés,
Volume 18, Issue 2 (6-2022)
Abstract
Through beamforming, the desired signal is estimated by calculating the weighted sum of the input signals of an array of antenna elements. In the classical beamforming methods, computing the optimal weight vector requires prior knowledge on the direction of arrival (DoA) of the desired signal sources. However, in practice, the DoA of the signal of interest is unknown. In this paper, we introduce two different deep-neural-network-based beamformers which can estimate the signal of interest while suppressing noise and interferences in two/three stages when the DoAs are unknown. Employing deep neural networks (DNNs) such as convolutional neural networks (CNNs) and bidirectional long short-term memory (bi-LSTM) networks enables the proposed method to have better performance than existing methods. In most cases, the output signal to interference and noise ratio (SINR) of the proposed beamformer is more than 10dB higher than the output SINR of the classical beamformers.
Tadele A Abose, Thomas O Olwal, Abel D Daniel, Murad R Hassen,
Volume 20, Issue 3 (9-2024)
Abstract
Due to cost and energy concerns with digital beamformers, much of the beamforming is done by hybrid beamformers in mm-wave (mm) massive multiple input multiple output (MIMO). Various works in hybrid beamforming structures considered either phase shifters, switches, or radio frequency lenses individually as switching mechanisms between antennas and precoding systems. Works that consider the hybrid use of phase shifters, switches, and radio frequency lenses need further investigation since there is a tradeoff between cost and system performance in each switching mechanism. The main aim of this research is to analyze the performance of a hybrid switch, a 1-bit phase shifter, and radio frequency (RF)-Lens in a hybrid beamforming network as a switching network. Simulation results showed that the hybrid of three has a spectral efficiency (SE) performance of 59.04 bps/Hz, which increases by 6.9 bps/Hz from that of the switch and lens antenna array network. The energy efficiency (EE) of the switch, phase shifter, and lens showed a performance of 46.41 bps/Hz/W, while the switch and lens antenna array, phase shifter, and lens antenna array showed a performance of 48.52 bps/Hz/W. The result also shows that the hybrid network achieves optimum performance at the expense of higher computational complexity.
Mousa Abdollahvand, Sima Sobhi-Givi,
Volume 21, Issue 1 (3-2025)
Abstract
This paper introduces a new method for improving wireless communication systems by employing beyond diagonal reconfigurable intelligent surfaces (BD-RIS) and unmanned aerial vehicle (UAV) alongside deep reinforcement learning (DRL) techniques. BD-RIS represents a departure from traditional RIS designs, providing advanced capabilities for manipulating electromagnetic waves to optimize the performance of communication. We propose a DRL-based framework for optimizing the UAV and configuration of BD-RIS elements, including hybrid beamforming, phase shift adjustments, and transmit power coefficients for non-orthogonal multiple access (NOMA) transmission by considering max-min fairness. Through extensive simulations and performance evaluations, we demonstrate that BD-RIS outperforms conventional RIS architectures. Additionally, we analyze the convergence speed and performance trade-offs of different DRL algorithms, emphasizing the importance of selecting the appropriate algorithm and hyper-parameters for specific applications. Our findings underscore the transformative potential of BD-RIS and DRL in enhancing wireless communication systems, laying the groundwork for next-generation network optimization and deployment.
