Noise Figure Research Articles

A Direct Conversion Frontend With Bandwidth Extension and Linearity Enhancement for 5G Receivers

ABSTRACTIn this paper, a new frontend for 5G receivers is proposed. In the presented work, a new bandwidth enhancement technique for low‐noise transconductance amplifiers and for wireless frontends has been proposed. The proposed frontend achieves low noise figure (NF) by using a noise cancelation scheme in the newly proposed LNTA. The linearity of the frontend is also improved by increasing the DC gain and the bandwidth of the opamp used in the transimpedance amplifier and by exploiting a linearity improvement method for the LNTA. The frontend has been implemented in a standard 0.18 μm CMOS process. The post‐layout simulation results prove the gain of 38 dB with less than 3 dB deviation in the pass‐band over a 6.5 GHz bandwidth. The results also show that NF is less than 8 dB, the worst‐case IIP3 is −2 dBm, the maximum S11 is equal to −9.5 dB while the frontend consumes 9.95 mW DC power from a single 1.8‐V supply, and the occupied area is 0.813 mm2.

Optimizing prediction accuracy in dynamic systems through neural network integration with Kalman and alpha-beta filters.

In the realm of dynamic system analysis, the Kalman filter and the alpha-beta filter are widely recognized for their tracking and prediction capabilities. However, their performance is often limited by static parameters that cannot adapt to changing conditions. Addressing this limitation, this paper introduces innovative neural network-based prediction models that enhance the adaptability and accuracy of these conventional filters. Our approach involves the integration of neural networks within the filtering algorithms, enabling the dynamic augmentation of parameters in response to performance feedback. We present two modified filters: a neural network-based Kalman filter and an alpha-beta filter, each augmented to incorporate neural network-driven parameter tuning. The alpha-beta filter is enhanced with neural network outputs for its α and β parameters, while the Kalman filter employs a neural network to optimize its internal parameter R and noise factor F. We assess these advanced models using the root mean square error (RMSE) metric, where our neural network-based alpha-beta filter demonstrates a significant 38.2% improvement in prediction accuracy, and the neural network-based Kalman filter achieves a 53.4% enhancement. Hence, our novel approach of integrating neural networks into filtering algorithms stands out as an effective strategy to significantly enhance their performance in dynamic environments.

MDM‐Incorporated Quad Donut Modes OCDMA‐FSO Scheme for Secure High‐Altitude Platforms‐To‐Satellite Scenarios

ABSTRACTThe next generation of communication networks is envisioned to be driven by high‐altitude platform (HAP)‐to‐satellite systems. License‐free narrow beam free space optics (FSO) can provide uninterrupted connectivity in satellite‐enabled Internet of Things scenarios. This work proposes a HAP‐to‐satellite hybrid mode division multiplexing–optical code division multiple access (MDM‐OCDMA) scheme employing zero cross‐correlation (ZCC) and multidiagonal (MD) codes. In high‐speed satellite communications, a 12 × 10‐Gbps hybrid MDM‐OCDMA scheme carrying four donut modes (0, 1, 2, and 3) enables high channel capacity, sufficient spectral efficiency, and data security under severe link conditions. Based on simulations, the hybrid MDM‐OCDMA scheme using the ZCC code achieves a greater FSO link distance of 420 m compared with when using the MD code at a 10e‐9 error correction limit under clear air and weak turbulent scenario. The reliable transmission distance of 250 m is achievable with the 120‐Gbps proposed system, assuming pointing errors of 2 mrad, 1‐dB receiver, and 2.5‐dB transmitter losses. The results also show that the system can sustain an additional loss of 1.5–2 dB over 250 m for all donut modes. Additionally, the system using ZCC code contributes to low power consumption over MD and variable weight ZCC code and thus requires a minimum received power of −4.02 dBm. It also offers high optical signal to noise of 42–52 dB, −11.58 to −22.20 dB of gain, 11.58–22.20 dB of noise figure, and −48.11 to −58.73 dBm of signal power at output over 200–700 m range up to 2 dB of additional loss. Comparative analysis indicates that the proposed system is more efficient, less complex, adequately distance‐friendly (=420 m), and capable of higher data rates (=120 Gbps) compared with other works. This makes it a promising solution for future high‐speed satellite communications considering the impact of link losses and atmospheric conditions.

Single-Input Multiple-Output (SIMO) Cascode Low-Noise Amplifier with Switchable Degeneration Inductor for Carrier Aggregation.

This paper presents a single-input multiple-output (SIMO) cascode low-noise amplifier with inductive degeneration for inter- and intra-band carrier aggregation. The proposed low-noise amplifier has two output ports for flexible operation in carrier aggregation combinations for band 30 and band 7. However, during inter- and intra-band operation, gain variation occurs depending on the output mode. To compensate for this, a switching circuit is proposed to adjust the degeneration inductor, optimizing gain performance for both modes. The switching operation can minimize the control for the dynamic range in the receiver system to support carrier aggregation. The designed low-noise amplifier was fabricated using a 65 nm CMOS process, occupying an area of 2.1 mm2. In inter-band operation, the small-signal gain was measured by 18.9 dB for band 30 and 18.6 dB for band 7, with the noise figures of 1.03 dB and 1.07 dB, respectively. For intra-band operation, the small-signal gain was 17.3 dB and 17.2 dB, with the noise figures of 1.3 dB and 1.41 dB. The IIP3 values were measured by -7.6 dBm and -6.7 dBm for inter-band, and -6.3 dBm and -6.2 dBm for intra-band. Power consumption was 8.04 mW and 7.68 mW in inter-band, and 17.04 mW and 17.64 mW in intra-band depending on the output configuration.

Suppression of the Petermann noise factor in a chiral optical mode converter without encircling an exceptional point

The engineering of exceptional points (EP) in gain-loss-assisted optical systems has recently garnered considerable attention for the development of unconventional photonic components. Moreover, the substantial noise associated with EPs poses a significant challenge to realizing their full potential in applications. There is a gap in the exploration of asymmetric mode conversion phenomena in the close proximity of the dynamical encirclement around an EP. In response, we propose the design of a fabrication-feasible dual-mode optical planar waveguide. Non-Hermiticity, in terms of a customized gain-loss profile, is introduced to modulate the interaction between the coupled modes. Contrary to previous assumptions, we establish that the dynamical encirclement of an EP is not a prerequisite for achieving asymmetric mode conversion. Furthermore, we calculate the Petermann factor (K) near the EP and demonstrate a significant two orders of magnitude reduction in the Petermann noise factor when we do not dynamically encircle the EP. Hence, we propose a new scheme to reduce the inherent noise.

A Compact V-Band Temperature Compensation Low-Noise Amplifier in a 130 nm SiGe BiCMOS Process.

This paper presents a compact V-band low-noise amplifier (LNA) featuring temperature compensation, implemented in a 130 nm SiGe BiCMOS process. A negative temperature coefficient bias circuit generates an adaptive current for temperature compensation, enhancing the LNA's temperature robustness. A T-type inductive network is employed to establish two dominant poles at different frequencies, significantly broadening the amplifier's bandwidth. Over the wide temperature range of -55 °C to 85 °C, the LNA prototype exhibits a gain variation of less than 1.5 dB at test frequencies from 40 GHz to 65 GHz, corresponding to a temperature coefficient of 0.01 dB/°C. At -55 °C, 25 °C, and 85 °C, the measured peak gains are 25.5 dB, 25 dB, and 24.4 dB, respectively, with minimum noise figures (NF) of 3.0 dB, 3.5 dB, and 4.2 dB, and DC power consumptions of 22.3 mW, 27.6 mW, and 34.4 mW. Moreover, the total silicon area of the LNA chip is 0.37 mm2, including all test pads, while the core area is only 0.09 mm2.

Wind turbine condition monitoring dataset of Fraunhofer LBF

Fraunhofer wind turbine dataset contains monitoring data from a 750 W wind turbine, including accelerometers and tachometer, to capture structural response, bearing vibrations and rotational velocity. Additionally, temperatures, wind speed and wind direction have been measured, while weather conditions have been acquired from selected sources. Various damage scenarios, including mass imbalance, and aerodynamic imbalance as well as damages on bearings’ outer race, inner race and roller element have been implemented. The availability of time series data makes the dataset well suited for both machine learning and signal processing-based condition monitoring applications. The availability of heterogeneous sensors has created a dataset particularly suited for information fusion, data fusion, multi-sensor approaches, and holistic monitoring. Experiments were conducted in real-world conditions outside of a controlled laboratory environment, thereby introducing challenges such as variable rotor speed, noise, overloads, and other environmental factors. Consequently, the dataset is qualified for tasks involving uncertainty quantification and signal pre-processing. This document will detail the test equipment, experimental procedures, simulated damage cases and measurement parameters.

Design of Concurrent Dual Band Low Noise Amplifier for WLAN Applications

This paper presents a dual band LNA CMOS designed for a Wireless Local Area Network (WLAN) application using CMOS 0.13-µm Silterra technology. The proposed design incorporates forward body bias technique with cascode and notch filter configuration to achieve both low power consumption and high gain. The simulation results demonstrate a total power consumption of 2.39 mW at a low supply voltage of 0.5 V, with a gain of 16 dB at 2.4 GHz and 12 dB at 5.2 GHz. Additionally, input return loss of -12.3 dB and -14.2 dB with noise figures of 2.93 dBm and 4.23 dBm were obtained at 2.4 GHz and 5.2 GHz, respectively. Overall, this research contributes to the development of dual band LNA designs for WLAN applications.

Radiation influence on planar reconfigurable field effect transistor low noise amplifier performance

Abstract Many novel devices have been proposed in the literature to mitigate the short channel effect and the reconfigurable FET (RFET) is one of them. The circuits based on new devices need to be investigated when they are introduced. This work has two parts: (i) designing cascoded RFET low noise amplifiers (LNA) and their performance analysis; and (ii) single-event performance analysis of RFET-LNAs. The designed LNA has a gain of 12 dB and a noise figure of 2.42 dB. The device in the common gate configuration mode is more susceptible to heavy ion radiation and collects more charge (QC) compared to the device in the common source configuration mode. Through temporal and frequency analysis, the irradiation disturbance is examined. In the temporal analysis, the collected charge (QC) is used as a metric, and the spectrogram is used in the frequency analysis.

Analysis of diode mixers using the method of node potentials in generalized matrix form in the frequency domain. Part 2. Isolation between ports, miscondition effect, noise level

A method for theoretical analysis of “input-output” and “local oscillator-output” decouplings of three types of diode frequency converters is presented: balanced, double balanced, triple balanced. For two operating modes of the local oscillator – “non-intensive” and “intensive” – the dependences of the “input-output” decoupling of the balanced mixer on the load conductivity and on the amplitude of the local oscillator voltage were obtained. Theoretical analysis and modeling were carried out. It is shown that the error between the calculated results and the simulation results does not exceed 3 dB. Expressions are obtained for errors introduced by the technological spread of diode parameters, which make it possible to estimate the maximum achievable values of the mixer characteristics (transmission coefficient and port isolation). A method for analyzing the noise properties of mixers is presented, the output noise spectra are calculated for each of the circuit elements (input resistance, diodes and output resistance), and analytical expressions for noise coefficients are obtained. Theoretical noise figure estimates are confirmed by simulation results with an accuracy of 1 dB.

HDN-Net: A Hybrid Deep Neural Network to Improve Iris Recognition in Unconstrained Environments with Eyeglasses

Recently, the use of iris recognition technology for biometric authentication has gained widespread acceptance due to the rich texture of the iris region, which provides a reliable standard for recognising individuals, as well as the non-intrusive nature of this method. However, the presence of eyeglasses poses a significant challenge to the accuracy of such systems. In unrestricted environments, current iris recognition techniques cannot effectively extract distinguishing features of the iris. Eyeglasses introduce scratches, specular reflections, dirt, blurriness, and other noise factors over the image of the iris, resulting in low recognition accuracy. To tackle this challenge, researchers have proposed the HDN-Net architecture. This architecture employs a multi-CNN model to combine the features of both the right and left iris images, extracting more distinguishing features to improve the accuracy of the classification task in the presence of challenges caused by eyeglasses. Experiment results show that the proposed iris recognition system achieves more promising performance compared to previous methods used in this field. The overall performance of our suggested HDN-Net method on the UBIRIS.V2 and CASIA-Iris.V4-1000 databases achieved 97.89% and 98.79% accuracy, respectively. Thus, the proposed HDN-Net method consistently outperforms other traditional and deep learning approaches and has the possibility to improve the accuracy of iris recognition systems (IRS) in real-world scenarios.

A 2–36 GHz CMOS LNA with π-Network-Based wideband interstage matching technique for software-defined radio systems

With the advance in wireless communication, next-generation software-defined radio (SDR) systems require transceivers to operate in both sub-6GHz and millimeter-wave (mmWave) band and support multiple standards. However, bridging sub-6GHz frequencies with millimeter-wave bands exceeding 30 GHz remains a challenge for conventional wideband LNAs. To surmount this, a 2–36 GHz CMOS low-noise amplifier (LNA) designed for SDR systems is introduced in this paper. An innovative wideband input matching network capable of spanning both frequency domains is proposed. The methodology effectively mitigates the impact of vast parasitic capacitances, achieving wideband input matching against Electrostatic Discharge (ESD) and on-chip decoupling capacitor parasitic. In addition, a π-network-based wideband interstage matching technique is adopted to extend bandwidth of gain. A tri-stage prototype of the proposed LNA, designed using a 40-nm CMOS process, is designed to validate our design strategies. The post-simulation outcomes reveal a peak gain of 14 dB with a -3dB bandwidth ranging from 2 to 36 GHz, equating to a fractional bandwidth of 178 %. The Noise Figure (NF) is commendably uniform across the frequency spectrum, stabilizing at 5 dB. Furthermore, the third-order input intercept point (IIP3) is −4.2dBm to -3dBm across the bandwidth. The performance is achieved with a power of 19.4 mW and within a core area of 0.1 mm2.

Enhancing autumn greenway walking experience: Exploring the combined effects of noise and thermal environment.

The evaluation of outdoor green spaces is influenced by diverse sensory perceptions. Traffic noise and thermal conditions significantly impact greenway-walking satisfaction; their optimization is vital for improving user experience and encouraging outdoor engagement. The study examines a typical Beijing greenway during autumn, focusing on strategies to enhance the walking experience under the combined effects of noise and thermal environments through mobile measurements and surveys. The results show that: 1) The interplay between noise and thermal factors varies depending on the walking state. Upon arrival, an increase in noise significantly worsens thermal comfort; higher sound levels intensify warm thermal sensations, though this effect is not consciously perceived. Upon departure, the effect of noise on thermal perception is not obvious. In both walking states, thermal sensation significantly affects subjective noise perception, yet the trends of influence differ. Subjective noise loudness increases as thermal comfort worsens, showing significant correlation only upon departure. 2) During autumn greenway walks, acoustic factors exert a greater impact on Overall Environmental Satisfaction (OES), with subjective noise loudness being more influential than noise level, followed by air temperature (Ta). Greater noise decreases OES, while OES increases initially with Ta and then decreases. The integrated effects of noise-thermal factors on OES show significant changes. 3) To enhance the autumn greenway-walking experience, the advised parameters are A-weighted Sound Level (ASL) ≤ 59.12 dBA and 15.17°C ≤ Ta ≤ 18.75°C. Finally, three design strategies are proposed: reducing subjective noise loudness, differentiating design based on walking status and balancing acoustic-thermal perceptual preferences.

Weak signal ultrafast interrogation of a micro-nano FBG probe sensor based on the hybrid amplified dispersion Fourier-transform method

To elucidate the thermal transport mechanisms at interfaces in micro- and nanoscale electronic devices, real-time monitoring of temperature variations at the microscopic and nanoscopic levels is crucial. Micro-nano fiber Bragg grating (FBG) sensors have been demonstrated as effective in-situ optical temperature probes for measuring local temperatures. Time-stretch dispersion Fourier transform (TS-DFT) that enables fast, continuous, single-shot measurements in optical sensing has been integrated with a micro-nano FBG probe (FBGP) for local temperature sensing. However, its temperature sensitivity and interrogation resolution are limited by the detection sensitivity. In this paper, we propose a hybrid amplified dispersion Fourier transform (ADFT) method to achieve ultrafast interrogation of FBGP’s weak signal. Thanks to the combined effect of TS-DFT and hybrid optical amplification, the reflection signal of the FBGP is amplified, and the wavelength shift of the FBGP sensor is converted to a temporal spacing change between two dispersed pulses through dispersion-induced wavelength-to-time mapping. The proposed method uses a homemade dissipative soliton mode-locked laser as the light source. The hybrid optical amplification technique comprises a L-band erbium-doped fiber amplifier and a distributed Raman amplifier. Their noise figure and net gain for the FBGP are 4.81 dB and 15.93 dB, respectively. In addition, the temperature calibration experiments show that a sampling rate of 51.43 MHz and the maximum temperature measurement error of 1.98°C are achieved within the temperature range of 20.3°C to 97°C. The stability of the net gain provided by the hybrid ADFT system is demonstrated by the coefficient of variation, which ranges from 2.22% to 2.95% in the peak voltage signal of the FBGP. This approach applies to scenarios requiring the handling of weak optical signals, particularly in temperature measurement at the micro-nano scale.

Analyzing the Indirect Effects of Lightning on Unmanned Aerial Vehicle Navigation Receivers

To investigate the interference effects of lightning on unmanned aerial vehicle (UAV) navigation receivers, an analytical approach for the evaluation of indirect lightning effects is suggested. The blocking mechanism of lightning pulses on the receiver is analyzed using the vector method. A behavioral-level simulation model of the receiver’s radio frequency (RF) front-end is constructed, and a lightning pulse injection simulation is performed based on the advanced design system (ADS). The simulation results indicate that lightning pulses induce blocking interference on the RF front-end of the navigation receiver, reducing its sensitivity and dynamic range. This interference is attributed to gain compression and degradation of the noise figure in the low-noise amplifier (LNA). To further validate the simulation results, a pin injection test is carried out to examine the influence of lightning pulses with different peak voltages on receiver sensitivity. The test results indicate a notable reduction in the receiver sensitivity when the lightning pulse peak reaches 250 V. The sensitivity trends across various test panels are consistent, and the damage thresholds are similar. These findings confirm the accuracy of the simulation results.

A 6-mode pre-amplifier for turbulence-resistant free-space optical communication

A few-mode pre-amplifier with high gain and high coupling efficiency was suitable for the turbulence-resistant free-space optical (FSO) communication. Here, we first built and experimentally demonstrated a forward- and core-pumped 6-mode (6 M) pre-amplifier. By optimizing the 6 M erbium-doped fiber (EDF) length, we achieved over 28 dB of gain and a noise figure of less than 7 dB with an input intensity of −30 dBm. Moreover, we experimentally evaluated the 6 M pre-amplifier of 2.5 Gbps On-Off Keying (OOK) signal transmission with a homemade tunable turbulence emulator. The advantages of the 6 M pre-amplifier over the single-mode (SM) pre-amplifier varied with channel turbulence conditions in terms of communication performances. Compared with the SM pre-amplifier, the coupling efficiencies increased by 4.5 dB and 5.8 dB on average, and the median bit error rates (BERs) of the communication system improved by 2 and 5 orders of magnitude, respectively, in the presence of channels with the scintillation index σI2 of 0.3978 and 1.0553 (moderate to strong turbulence).

A 28 GHz balun‐first LNA with db‐linear 32 db gain range for 5 G applications

AbstractThis letter presents a 28 GHz balun‐first low noise amplifier (LNA) featuring a wide dB‐linear variable gain range. The architecture of LNA includes three‐stage cascode amplifiers. An integrated balun at the input stage provides RF ESD protection and converts a single‐ended signal to a differential one (S‐to‐D). A transformer‐based dual‐resonant matching network is designed and analyzed to achieve wideband performance. To realize a continuous dB‐linear variable gain range and consistent input/output matching, gain control is implemented in the second stage using a 5‐bit digital‐to‐analog converter (DAC) for a 32 dB gain range. The DAC can generate a nonlinear analog voltage to control the gate of the common‐gate transistor in the second cascode stage, inversely compensating for the nonlinear gain variations of the cascode amplifier. The LNA is fabricated in 65‐nm CMOS process with a core size of 0.154 mm². Measurement results exhibit a maximum gain of 33.5 dB and a minimum noise figure (NF) of 3.65 dB with a 3‐dB bandwidth of 23–29.5 GHz. The measured variable gain range is approximately 32 dB across 32 different gain states, with a linear gain step of ~1 dB per state and an IP1dB ranging from −6.5 dBm to −35.25 dBm. The power consumption is 35.4–48 mW from a 1.2 V supply voltage.

Application of Seismic Attribute Clustering Method Based on PCA-SOM in Identification of Paleochannels

Abstract Paleochannels are crucial reservoir types in continental oil and gas fields. The P oil layer in the Sanzhao Depression of the Songliao Basin is a typical example of river-controlled delta-phase deposition. The underwater diversion channel is highly developed and serves as the primary unit of the oil and gas reservoir. The stacking of the river channel creates a complex relationship. Identifying river channels has always been a challenging aspect of predicting sweet spot reservoirs due to the thinness of the sand, fault cutting, seismic acquisition and processing noise, low-resolution constraints, and other factors. This paper proposes a method for identifying river channels by combining principal component analysis (PCA) and self-organised mapping network (SOM) with seismic attribute clustering. The aim is to address the issue of difficult identification of paleochannels. The seismic attribute set, which contains multiple types of attributes, is first dimensionality reduced using principal component analysis. Then, a few principal components that can characterise the attribute set are extracted and used as inputs to the self-organising map (SOM). This reduces the dimensionality of the training sample set and simplifies the network structure. The self-organising neural network structure is designed based on the input sample features. Training is then carried out, and the network weights are updated. Attribute clustering is performed to obtain the river identification results. The effectiveness of this method for paleochannel recognition is verified by the clear morphology of the recognised paleochannels in the Songliao Basin, their conformity to geological understanding, and their matching with drilling information.

Road-traffic noise exposure and coronary atherosclerosis in the Swedish CArdioPulmonary bioImage Study (SCAPIS).

Road-traffic noise may influence the development of cardiovascular events such as stroke and myocardial infarction, but etiological mechanisms remain unclear. This study aimed to assess the relationship between long-term road-traffic noise exposure and coronary atherosclerosis in Sweden. In the Swedish CArdioPulmonary bioImage Study (SCAPIS) cohort, including 30,154 subjects aged 50-65 years, recruited between 2013 and 2018, coronary atherosclerosis was measured based on computer tomography (CT) scans as coronary artery calcium score, segment involvement score (SIS), and non-calcified plaques (NCP) at enrollment. Based on modified Nordic model, road-traffic noise exposure was modeled for 2000, 2013, and 2018 with interpolation for intermediate years. We investigated the association between time-weighted long-term exposure to road-traffic noise (Lden) and the prevalence of atherosclerosis using ordinal logistic regression models adjusting for potential socioeconomic, behavioral, and environmental confounders, including air pollution. No clear associations were found between road-traffic noise and coronary atherosclerosis. The odds ratio for coronary artery calcium score was 1.00 (95% confidence interval [CI] = 0.96, 1.04), SIS 0.99 (0.96, 1.03), and NCP 0.98 (0.90, 1.03) per interquartile range (9.4 dB Lden) for road-traffic noise exposure during 10 years before enrollment. No consistent associations were observed in site-specific analyses or using shorter exposure periods. Furthermore, exposure-response analyses revealed no clear trends, and there were no strong interactions between road-traffic noise and cardiovascular risk factors in relation to the atherosclerosis markers. Long-term exposure to road-traffic noise was not linked to coronary atherosclerosis or calcification in relatively healthy, middle-aged populations in Sweden.

Enhancement of single-photon level signal detection based on phase sensitive amplification strategy

Abstract We investigate the ability of phase-sensitive amplification (PSA) to noiselessly amplify the preferred quadrature components of single-photonsignals that are limited by phase fluctuations relative to the pump. We presenta PSA enhancement strategy that is more realistic for possible experimentalrealization and is expected to significantly improve the detection of weaksignals at the single-photon level and obtain more useful information. Our studyshows that with a large PSA gain, proper transmissivity allows both direct and
balanced homodyne detections to operate optimally simultaneously, and effectively improves the noise figure degradation owing to the internal losses and non-ideal detection efficiency.