High SNR Research Articles

Outage Probability Analysis and Altitude Optimization of a UAV-Enabled Triple-Hop Mixed RF-FSO-Based Wireless Communication System

In this paper, we present the evaluation of network parameters for the unmanned aerial vehicle (UAV)-enabled triple-hop mixed RF/FSO-based wireless communication system, where one relay is a fixed relay and the second relay is a UAV which acts as decode-and-forward relay for communication from the base station (B) to the multiple mobile users (Mi), i∈{1,2⋯N}. The first hop from B to fixed relay (R1) is the radio frequency (RF) link modeled using α−κ−μ fading distribution, the second hop from the relay R1 to the UAV relay (R2) is a free space optics (FSO) link modeled using Gamma-Gamma fading, and the third hop from R2 to the Mi is, again, an RF link modeled using the Rayleigh fading model. The direct communication between the B and the Mi is not feasible due to the very large distance. We derive the closed form analytical expression for the outage probability of the proposed system and find the effect of the base system parameters on the performance of the system. We also analyze the outage probability of the system at high SNR values to get further insights of the system performance. In addition, altitude optimization of UAV is carried out to know the optimal elevation angle in correspondence with UAV’s optimal altitude in order to maximize performance of the system.

On the Capacity of the Peak-Limited and Band-Limited Channel.

We investigate the peak-power limited (PPL) Additive White Gaussian Noise (AWGN) channels in which the signal is band-limited, and its instantaneous power cannot exceed the power P. This model is relevant to many communication systems; however, its capacity is still unknown. We use a new geometry-based approach which evaluates the maximal entropy of the transmitted signal by assessing the volume of the body, in the space of Nyquist-rate samples, comprising all the points the transmitted signal can reach. This leads to lower bounds on capacity which are tight at high Signal to Noise Ratios (SNRs). We find lower bounds on capacity, expressed as power efficiency, that were higher than the known ones by a factor of 3.3 and 8.6 in the low-pass and the band-pass cases, respectively. The gap to the upper bounds is reduced to a power ratio of 1.5. The new bounds are numerically evaluated for FDMA-style signals with limited duration and also are derived in the general case as a conjecture. The penalty in power efficiency due to the peak power constraint is roughly 6 dB at high SNRs. Further research is needed to develop effective modulation and coding for this channel.

Multi-spectral autofluorescence variability of the individual retinal pigmented epithelial cells in healthy aging eyes

The retinal pigment epithelium (RPE) is vital for the healthy function of the retina. Cellular level changes in the RPE are not visualized with current clinical techniques due to a lack of spatial resolution. Fluorescence adaptive optics scanning light ophthalmoscopy (AOSLO) can image RPE cells by utilizing their intrinsic autofluorescence (AF). The RPE AF has been imaged with only a few discrete excitation and emission bands and the multi-spectral AF has not been interrogated systematically at the level of single cells. In this study, we imaged 16 healthy eyes (ages 20-75) with AOSLO to investigate the multi-spectral AF as a function of age and wavelength with excitation from 650 - 805 nm. Quantitative analysis showed that 720 nm light produced images with the highest SNR (65.0 dB). Spatial AF variability showed a trend to increase with aging, suggesting increased heterogeneity in RPE AF with age. Spatial variability in the multi-spectral fluorescence of RPE cells with age may be a consequence of normal age-related loss of RPE cells. Multi-spectral fluorescence AOSLO provides new insight into aging related changes to RPE cells and may be a useful tool for studying diseases that affect the RPE, such as age-related macular degeneration (AMD).

Improved abdominal T1 weighted imaging at 0.55T.

Breath-held fat-suppressed volumetric T1-weighted MRI is an important and widely-used technique for evaluating the abdomen. Both fat-saturation and Dixon-based fat-suppression methods are used at conventional field strengths; however, both have challenges at lower field strengths (<1.5T) due to insufficient fat suppression and/or inadequate resolution. Specifically, at lower field strengths, fat saturation often fails due to the short T1 of lipid; and Cartesian Dixon imaging provides poor spatial resolution due to the need for a long ΔTE, due to the smaller Δf between water and lipid. The purpose of this work is to demonstrate a new approach capable of simultaneously achieving excellent fat suppression and high spatial resolution on a 0.55T whole-body system. We applied 3D stack-of-spirals Dixon imaging at 0.55T, with compensation of concomitant field phase during reconstruction. The spiral readouts make efficient use of the requisite ΔTE. We compared this with 3D Cartesian Dixon imaging. Experiments were performed in 2 healthy and 10 elevated liver fat volunteers. Stack-of-spirals Dixon imaging at 0.55T makes excellent use of the required ΔTE, provided high SNR efficiency and finer spatial resolution (1.7 × 1.7 × 5 mm3) compared Cartesian Dixon (3.5 × 3.5 × 5 mm3), within a 17-s breath-hold. We observed successful fat suppression, and improved definition of structures such as the liver, kidneys, and bowel. We demonstrate that high-resolution single breath-hold volumetric abdominal T1-weighted imaging is feasible at 0.55T using spiral sampling and concomitant field correction. This is an attractive alternative to existing Cartesian-based methods, as it simultaneously provides high-resolution and excellent fat-suppression.

Improving signal-to-noise ratio of Raman measurements based on ensemble learning approach.

Raman spectroscopy is an extensively explored vibrational spectroscopic technique to analyzethebiochemical composition and molecular structure of samples, which is often assumed to be non-destructive when carefully using proper laser power and exposure time. However, the inherentlyweak Raman signal and concurrent fluorescence interference often lead to Raman measurements withalow signal-to-noise ratio (SNR), especially for biological samples. Great efforts have been made to develop experimental approaches and/or numerical algorithms to improvetheSNR. In this study, we proposed an ensemble learning approach to recover and denoise Raman measurements withalow SNR. The proposed ensemble learning approach was evaluated on 986 pairs of Raman measurements, each pair of which consists of a low SNR Raman spectrum and a high SNR reference Raman spectrum from the exact same fungal sample but uses 200 timestheintegration time. Compared with conventional methods, the Raman measurementsrecoveredby the proposed ensemble learning approach are more identical to high SNR reference Raman measurements, with anaverage RMSE and MAE of only 1.337 × 10-2 and 1.066 × 10-2, respectively; thus, the proposed ensemble learning approach is expected to be a powerful tool for numerically improving the SNR of Raman measurements and further benefits rapid Raman acquisition from biological samples.

Fabrication of (K,Rb)2CuCl3 and (K,Rb)2CuBr3 Single Crystal Scintillators with Efficient Luminescence

Scintillators are phosphor materials that emit many low-energy photons upon exposure of high-energy ionizing radiation such as X- and γ-rays. They have been utilized in combination with photodetectors for radiation measurements, including medical imaging [1], underground resources exploration [2], luggage inspection [3], and structural analysis of materials [4]. The required characteristics of scintillators are different depending on the applications. For example, high light yield (LY) for high energy resolution and high signal-noise ratio, short decay time for high time resolution, large effective atomic number for high interaction probability with ionizing radiation, and low hygroscopicity for long-term usability are important. Halide crystals such as Tl-doped CsI and NaI have been utilized as practical scintillators because of their high LY owing to the medium bandgap energy (5.8–6.3 eV) [4, 5]. However, most halide crystals have issues related to chemical instability due to hygroscopicity. Thus, novel non-hygroscopic scintillators with high LY have been desired. Nowadays, Cu-based halide scintillators have received attention owing to good properties such as high photoluminescence quantum yield (PLQY), scintillation LY, and no hygroscopicity. We have focused on the alkali copper halide group such as A 2CuX 3 (A = K, Rb X = Cl, Br). They showed high PLQY (~100%) attributed to the recombination of self-trapped excitons under UV and X-ray irradiations [6, 7]. However, their scintillation LYs under γ-rays have not been clarified. According to Hume-Rothery rules [8], a continuous solid solution containing two or more components can be easily formed when two substances with similar ionic radius and crystal structure are partially mixed in the matrix. In continuous solid solutions, emission properties of phosphors were improved by optimizing energy levels in the bandgap and lattice defects involved in the luminescence [9]. On the basis of the rules, the continuous solid solutions of (K,Rb)2CuCl3 and (K,Rb)2CuBr3 can be grown. Thus, we fabricated (K,Rb)2CuCl3 and (K,Rb)2CuBr3 to enhance the scintillation properties. In this presentation, the scintillation properties such as the X-ray-induced scintillation spectra, the scintillation decay curves, afterglow curves, and pulse-height spectra of 1 37Cs γ-rays (662 keV) measurements will be presented.[1] C.W. Eijk., Phys. Med. Biol., 47 (2002) R85. [2] A. Nikitin et.al., IEEE Nucl. Sci. Symp. Med. Imag. Conf. (2010) 1214. [3] V.D. Ryzhikov et.al., IEEE Symposium Conference Record Nuclear Science (2004) 4291. [4] V.V. Nagarkar et.al., IEEE Trans. Nucl. Sci. 45 (1998) 492. [5] M. Moszynski et.al., Nucl. Instrum. Methods Phys. Res. A (2004) 4291. [6] T.D Creason et.al., Chem. Mater. 32 (2020).

High-resolution volumetric dynamic magnetic resonance imaging of the wrist using an 8-channel flexible receive coil.

Real-time imaging is useful for the evaluation of wrist instability. However, currently available real-time magnetic resonance imaging (MRI) methods are limited due to their 2D nature or provide insufficient temporal resolution and image quality for quantitative kinematic analysis. This work introduces a novel approach for volumetric dynamic MRI of the wrist joint during active motion and demonstrates the feasibility of tracking carpal bone motion. A flexible 8-element 3T wrist receive coil and 3D-printed support platform for guiding motion were designed for dynamic wrist imaging. 2D real-time images were acquired using a fat-saturated FLASH sequence with radial sampling and reconstructed with the GRASP algorithm. Corresponding volumetric dynamic wrist images were obtained by assembling 2D real-time images into 3D snapshots using autodetected MRI-visible markers for slice alignment. The proposed method was demonstrated for radial-ulnar deviation on five healthy volunteers. The flexible wrist coil provided high SNR while allowing a wide range of wrist movements. 2D real-time wrist images were acquired with a temporal resolution of 48ms/frame with negligible streaking artifacts. Carpal bones and metacarpal bones were properly aligned in the assembled dynamic volumes for all five subjects. The excellent bone-to-tissue contrast enabled accurate segmentation of the individual carpal bones on the assembled dynamic volumes. This work introduces a novel wrist coil and demonstrates that real-time volumetric dynamic examination of the moving wrist is feasible. The achieved image quality and high temporal resolution could enable automatic segmentation of carpal bones and quantitative kinematic assessment for evaluating wrist instability.

Romer-EPTI: Rotating-view motion-robust super-resolution EPTI for SNR-efficient distortion-free in-vivo mesoscale diffusion MRI and microstructure imaging.

To overcome the major challenges in diffusion MRI (dMRI) acquisition, including limited SNR, distortion/blurring, and susceptibility to motion artifacts. A novel Romer-EPTI technique is developed to achieve SNR-efficient acquisition while providing distortion-free imaging, minimal spatial blurring, high motion robustness, and simultaneous multi-TE imaging. It introduces a ROtating-view Motion-robust supEr-Resolution technique (Romer) combined with a distortion/blurring-free Echo Planar Time-resolved Imaging (EPTI) readout. Romer enhances SNR through simultaneous multi-thick-slice acquisition with rotating-view encoding, while providing high motion-robustness via a high-fidelity, motion-aware super-resolution reconstruction. Instead of EPI, the in-plane encoding is performed using EPTI readout to prevent geometric distortion, T2/T2*-blurring, and importantly, dynamic distortions that could introduce additional blurring/artifacts after super-resolution reconstruction due to combining volumes with inconsistent geometries. This further improves effective spatial resolution and motion robustness. Additional developments include strategies to address slab-boundary artifacts, achieve minimized TE and optimized readout for additional SNR gain, and increase robustness to strong phase variations at high b-values. Using Romer-EPTI, we demonstrated distortion-free whole-brain mesoscale in-vivo dMRI at both 3T (500-μm isotropic [iso] resolution) and 7T (485-μm iso resolution) for the first time. Motion experiments demonstrated the technique's motion robustness and its ability to obtain high-resolution diffusion images in the presence of subject motion. Romer-EPTI also demonstrated high SNR gain and robustness in high b-value (b = 5000 s/mm2) and time-dependent dMRI. The high SNR efficiency, improved image quality, and motion robustness of Romer-EPTI make it a highly efficient acquisition for high-resolution dMRI and microstructure imaging.

Ultrafast 3D synthetic aperture imaging with Hadamard-encoded aperiodic interval codes and aperiodic sparse arrays with separate transmitters and receivers

3D synthetic aperture (SA) imaging of volumes can be obtained using sparse 2D ultrasound arrays. However, even with just 256 elements, the volumetric imaging rate can be relatively slow due to having to transmit on each element in succession. Hadamard Aperiodic Interval (HAPI) codes can be used to image the full SA dataset in one extended transmit to speed up the synthetic aperture imaging, but their long nature produces large deadzones if the same elements are used as both transmitters and receivers. In this simulation study, we use a 2D Costas sparse array with separate transmitters and receivers to remedy the deadzone problem, and use it with the HAPI-coded imaging scheme to obtain fully transmit–receive focused, wide field-of-view 3D volumes with high-resolution and high SNR at ultrafast volumetric imaging rates of more than 500 volumes per second, almost nine times faster than non-coded SA imaging with the same imaging parameters. We show similar PSF performance compared to non-coded SA, and a 26 dB improvement in SNR with order-256 HAPI codes. We also present cyst simulations showing similar contrast for the HAPI-coded SA method compared to non-coded SA in the context of no noise, and improved contrast in the context of noise.

Multiple Defect-Induced High-Resolution Near-Infrared Mechanoluminescent Materials for Non-Destructive Detection of Blood Glucose and Lipids.

Mechanoluminescence (ML) materials, known for their ability to convert mechanical energy into light, are increasingly recognized for their potential applications, such as in intelligent stress sensing, in vivo bioimaging, and stress non-destructive monitoring. However, the low signal-to-noise ratio (SNR) and narrow-band emission of single-defect-induced ML materials usually limit their biological-related practical applications. Here, these limitations will be addressed by modulating the microstructure evolution in Y3Ga3MgSiO12:Cr3+ through the [Si4++Mg2+] → [Ga3++Ga3+] chemical substitution strategy. Density functional theory (DFT) calculation reveals the defect types and dynamic charge migration processes. In addition, Y3Ga3MgSiO12: Cr3+ with continuously distributed "shallow-deep" defects (0.68-1.61eV) can avoid persistent luminescence (PersL) and bright-field environment interference. Herein, such high SNR near-infrared broadband ML emission may provide a reliable way for high-quality biological non-destructive sensing and detection. Finally, benefiting from the different absorption of ML signals in glucose/lipid, one may find a novel non-invasive blood glucose/lipid testing technology in patients.

Giving the prostate the boost it needs: Spiral diffusion MRI using a high-performance whole-body gradient system for high b-values at short echo times.

To address key issues of low SNR and image distortions in prostate diffusion MRI (dMRI) by means of using strong gradients, single-shot spiral readouts and an expanded encoding model for image reconstruction. Diffusion-weighted spin echo imaging with EPI and spiral readouts is performed on a whole-body system equipped with strong gradients (up to 250 mT/m). An expanded encoding model including static off-resonance, coil sensitivities, and magnetic field dynamics is employed for image reconstruction. The acquisitions are performed on a phantom and in vivo (one healthy volunteer and one patient with prostate cancer). The resulting images are compared to conventional dMRI EPI with navigator-based image reconstruction and assessed in terms of their congruence, SNR, tissue contrast, and quantitative parameters. Using the expanded encoding model, high-quality images of the prostate gland are obtained across all b-values (up to 3 ms/μm2), clearly outperforming the results obtained with conventional image reconstruction. Compared to EPI, spiral imaging provides an SNR gain up to 45% within the gland and even higher in the lesion. In addition, prostate dMRI with single-shot spirals at submillimeter in-plane resolution (0.85 mm) is accomplished. The combination of strong gradients and an expanded encoding model enables imaging of the prostate with unprecedented image quality. Replacing the commonly used EPI with spirals provides the inherent benefit of shorter echo times and superior readout efficiency and results in higher SNR, which is in particular relevant for considered applications.

Dual‐Low Technology in Coronary and Abdominal CT Angiography: A Comparative Study of Deep Learning Image Reconstruction and Adaptive Statistic Iterative Reconstruction‐Veo

ABSTRACTTo investigate the application advantages of dual‐low technology (low radiation dose and low contrast agent dose) in deep learning image reconstruction (DLIR) compared to the adaptive statistical iterative reconstruction‐Veo (ASIR‐V) standard protocol when combing coronary computed tomography angiography (CCTA) and abdominal computed tomography angiography (ACTA). Sixty patients who underwent CCTA and ACTA were recruited. Thirty patients with low body mass index (BMI) (&lt; 24 kg/m2, Group A, standard protocol) were reconstructed using 60% ASIR‐V, and 30 patients with high BMI (&gt; 24 kg/m2, Group B, dual‐low protocol) were reconstructed using DLIR at high strength (DLIR‐H). The effective dose and contrast agent dose were recorded. The CT values, standard deviations, signal‐to‐noise ratio (SNR), and contrast‐to‐noise ratio (CNR) were measured. The subjective evaluation criteria were scored by two radiologists using a blind Likert 5‐point scale. The general data, objective evaluation, and subjective scores between both groups were compared using corresponding test methods. The consistency of objective and subjective evaluations between the two radiologists were analyzed using Kappa tests. Group B showed a remarkable 44.6% reduction in mean effective dose (p &lt; 0.01) and a 20.3% decrease in contrast agent dose compared to Group A (p &lt; 0.01). The DLIR‐H demonstrated the smallest standard deviations and highest SNR and CNR values (p &lt; 0.01). The subjective score of DLIR‐H was the highest (p &lt; 0.01), and there was good consistency between the two radiologists in the subjective scoring of CCTA and ACTA image quality (κ = 0.751 ~ 0.919, p &lt; 0.01). In combined CCTA and ACTA protocols, DLIR can significantly reduce the effective dose and contrast agent dose compared to ASIR‐V while maintaining good image quality.

High-Fidelity OC-Seislet Stacking Method for Low-SNR Seismic Data

Seismic stacking is a core technique in seismic data processing, aimed at enhancing the signal-to-noise ratio (SNR) of data by utilizing seismic data acquisition with multifold geometry. Traditional stacking methods always have certain limitations, such as the reliance on the accuracy of velocity analysis for dip moveout (DMO) in common midpoint (CMP) stacking. The seislet transform, a compression technique tailored to nonstationary seismic data, can compress and stack along the prediction direction of seismic data, which provides a new technical idea for high-fidelity seismic imaging based on the effectiveness of the compression. This paper introduces a high-order OC-seislet stacking method for low-SNR seismic data, capable of achieving the high-fidelity stacking of reflection and diffraction waves simultaneously. With the multi-scale analysis advantages of the seislet transform, this method addresses the dependency of DMO stacking on velocity analysis accuracy. In the frequency–wavenumber–scale domain, the correction compensation of the high-order CDF 9/7 basis function is used to obtain the compression coefficients of the high-order OC-seislet transform. This approach simultaneously stacks frequency–wavenumber information of reflection and diffraction waves with high fidelity while implementing DMO processing. After normalizing the weighting coefficients and applying soft thresholding for denoising, the final result is transformed back to the original time–space domain, yielding high-fidelity stacking sections. The results of applying this method to both synthetic and field data show that, compared with conventional DMO stacking methods, the high-order OC-seislet stacking technique reasonably represents dipping layers and fault amplitudes, and it can achieve a balance of a high SNR and high fidelity in stacked profiles.

A user selection algorithm for downlink MU-MIMO systems using product of singular values of effective channels

User selection plays a crucial role when aiming to improve channel throughput in multiuser multiple- input multiple-output downlink systems with block diagonalization linear precoding. While an optimal group of users can be found by exhaustively searching all possible combinations of users, the process becomes prohibitively complex when there is a large number of users. In this paper, we propose a greedy suboptimal user selection algorithm, which iteratively selects a user to maximize the product of the singular values of the effective channels from a set of unselected users. The proposed algorithm is based on the iterative precoder design method, whereby interuser interference is perfectly cancelled with lower complexity than with the singular value decomposition-based precoding technique. Moreover, to avoid frequent use of singular value decomposition, the proposed algorithm applies QR decomposition to the selected channel matrices in order to obtain singular values, which are equivalent to the product of diagonal elements in the upper triangular matrix. Simulation results show that, under a high SNR regime, the proposed algorithm outperforms several other greedy algorithms and can provide the same performance as a capacity-based algorithm for both correlated and uncorrelated channels with significantly reduced complexity.

STAR-RIS-NOMA empowered vehicle-to-vehicle communications: Outage and ergodic capacity analysis

This paper delves into the performance evaluation of a non-orthogonal multiple access (NOMA) enabled vehicle-to-vehicle (V2V) communication system empowered by simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS). Herein, we consider that a moving access point (AP) transmits superimposed signals to nearby and distant NOMA vehicles simultaneously via reflection and transmission through a STAR-RIS equipped vehicle with 2N reconfigurable elements, respectively. Specifically, by characterizing all V2V channels as double-Rayleigh fading distributed, we derive the outage probability (OP) and ergodic capacity (EC) expressions for each NOMA vehicle, by employing both perfect and imperfect successive interference cancellation (SIC) at nearby vehicle user. Furthermore, we present the asymptotic OP behavior at high signal-to-noise ratio (SNR) regime to gain deeper insights into the diversity order of NOMA vehicles. The findings reveal that the nearby vehicle under perfect SIC and far vehicle experience a diversity order of Nπ4256−π2, which is the function of number of reconfigurable elements (N) in the STAR-RIS. Whereas, a zero diversity order is obtained for nearby user under imperfect SIC case. Moreover, we analytically discuss the high SNR slopes of EC for both user vehicles. Furthermore, Monte-Carlo simulations are conducted to validate our analytical results under various channel and system parameter configurations. We also provide a comparison between the proposed scheme and STAR-RIS based orthogonal multiple access and cooperative relaying systems.

High dynamic range mapping for the evaluation of parallel transmit arrays.

Demonstration of a high dynamic-range and high SNR method for acquiring absolute maps from a combination of gradient echo and actual-flip-angle measurements that is especially useful during the construction of parallel-transmit arrays. Low flip angle gradient echo images, acquired when transmitting with each channel individually, are used to compute relative maps. Instead of computing these in a conventional manner, the equivalence of the problem to the ESPIRiT parallel image reconstruction method is used to compute maps with a higher SNR. Absolute maps are generated by calibration against a single actual flip-angle acquisition when transmitting on all channels simultaneously. Depending on the number of receiver channels and the location of the receive elements with respect to the subject being investigated, moderate to high gains in the SNR of the acquired maps can be achieved. The proposed method is especially suited for the acquisition of maps during the construction of transceiver arrays. Compared to the original method, maps with higher SNR can be computed without the need for additional measurements, and maps can also be generated using previously acquired data. Furthermore, easy adoption and fast estimation of receiver channels is possible because of existing highly optimized open-source implementations of ESPIRiT, such as in the BART toolbox.

A deep brain stimulation-conditioned RF coil for 3T MRI.

To develop and test an MRI coil assembly for imaging deep brain stimulation (DBS) at 3 T with a reduced level of local specific absorption rate of RF fields near the implant. A mechanical rotatable linearly polarized birdcage transmitter outfitted with a 32-channel receive array was constructed. The coil performance and image quality were systematically evaluated using bench-level measurements and imaging performance tests, including SNR maps, array element noise correlation, and acceleration capabilities. Electromagnetic simulations and phantom experiments were performed with clinically relevant DBS device configurations to evaluate the reduction of specific absorption rate and temperature near the implant compared with a circular polarized body coil setup. The linearly polarized birdcage coil features a block-shaped low electric field region to be co-aligned with the implanted DBS lead trajectory, while the close-fit receive array enables imaging with high SNR and enhanced encoding capabilities. The 3T coil assembly, consisting of a rotating linear birdcage and a 32-channel close-fit receive array, showed DBS-conditioned imaging technology with substantially reduced heat generation at the DBS implants.

Open-loop narrowband magnetic particle imaging based on mixed-frequency harmonic magnetization response.

Magnetic particle imaging (MPI), a radiation-free, dynamic, and targeted imaging technique, has gained significant traction in both research and clinical settings worldwide. Signal-to-noise ratio (SNR) is a crucial factor influencing MPI image quality and detection sensitivity, and it is affected by ambient noise, system thermal noise, and the magnetization response of superparamagnetic nanoparticles. Therefore to address the high amplitude system and inherent thermal noise present in conventional MPI systems is essential to improve detection sensitivity and imaging resolution. This study introduces a novel open-loop, narrow-band MPI signal acquisition system based on mixed-frequency harmonic magnetization response. Allowing superparamagnetic nanoparticles to be excited by low frequency, high amplitude magnetic fields and high frequency, low amplitude magnetic fields, the excitation coil generates a mixed excitation magnetic field at a mixed frequency of 8.664 kHz (f H + 2f L ), and the tracer of superparamagnetic nanoparticles can generate a locatable superparamagnetic magnetization signal with rich harmonic components in the mixed excitation magnetic field and positioning magnetic field. The third harmonic signal is detected by a Gradiometer coil with high signal-to-noise ratio, and the voltage cloud image is formed. The experimental results show that the external noise caused by the excitation coil can be effectively reduced from 12 to about 1.5 μV in the imaging area of 30 mm × 30 mm, which improves the stability of the detection signal of the Gradiometer coil, realizes the detection of high SNR, and makes the detection sensitivity reach 10 μg Fe. By mixing excitation, the total intensity of the excitation field is reduced, resulting in a slight improvement of the resolution under the same gradient field, and the spatial resolution of the image reconstruction is increased from 2 mm under the single frequency excitation (20.7 kHz) in the previous experiment to 1.5 mm under the mixed excitation (8.664 kHz). These experimental results highlight the effectiveness of the proposed open-loop narrowband MPI technique in improving signal detection sensitivity, achieving high signal-to-noise ratio detection and improving the quality of reconstructed images by changing the excitation magnetic field frequency of the excitation coil, providing novel design ideas and technical pathways for future MPI systems.

Performance evaluation of compansion-based clipped OFDM systems

The peak-to-average power ratio (PAPR), commonly used to describe the amplitude variations of an OFDM (orthogonal frequency-division multiplex) signal, does not accurately reflect its impact on the system performance. This paper applies the mutual information as a metric to assess the effects of nonlinear PAPR reduction schemes on the performance of OFDM systems. Evaluation of the achieved mutual information shows that a significant capacity loss from clipping occurs only at high SNR (signal-to-noise ratio) and a simple compression/expansion technique is proposed to achieve close to optimal performance in this regime. The effectiveness of this method is validated through WER (word error rate) simulations with several modulation and coding schemes.

A Weighted AIMD Congestion Control Algorithm for Device-to-Device Communication in 5G Network

ABSTRACT Device-to-Device (D2D) communication offers promising benefits in 5G networks in terms of improved throughput and reduced latency. However, efficient congestion control remains a critical challenge to ensure optimal performance and resource utilization. Existing congestion control mechanisms often struggle with adapting to dynamic network conditions, leading to inefficiencies, such as underutilization of network resources or excessive packet loss. This paper addresses these challenges by proposing a novel Weighted AIMD congestion control algorithm tailored specifically for D2D communication in 5G networks (WACC-D2DC-5GN). Here, the Weighted AIMD Congestion Control Algorithm is proposed for estimating available bandwidth and Hunger Games Search Optimization to optimize the weight parameter of WACC. The proposed algorithm integrates weighted factors that dynamically adjust congestion window sizes based on real-time network feedback. Simulations are run on the NS3-mmWave module, NS3 LTE-A module. The simulation outcomes show that the proposed WACC-D2DC-5GN method attains 27.26%, 20.41%, and 23.26% higher SNR and 16.20%, 26.97%, and 30.34% higher Throughput when analysed with existing techniques like NexGen D-TCP: next generation dynamic TCP congestion control approach (NGD-TCP-CCA), user-centric channel allocation system for 5G higher-speed users by using ML to decrease handover rate (UCC-HSU-MLA), and efficient with reliable hybrid deep learning-allowed method for congestion control in 5G/6G networks (HDL-EMC-CN) respectively.