Open-Loop Wide-Bandwidth Phase Modulation Techniques

The ever-increasing growth in the bandwidth of wireless communication channels requires the transmitter to be wide-bandwidth and power-efficient. Polar and outphasing transmitter topologies are two promising candidates for such applications, in future. Both these architectures require a wide-bandwidth phase modulator. Open-loop phase modulation presents a viable solution for achieving wide-bandwidth operation. An overview of prior art and recent approaches for phase modulation is presented in this paper. Phase quantization noise cancellation was recently introduced to lower the out-of-band noise in a digital phase modulator. A detailed analysis on the impact of timing and quantization of the cancellation signal is presented. Noise generated by the transmitter in the receive band frequency poses another challenge for wide-bandwidth transmitter design. Addition of a noise transfer function notch, in a digital phase modulator, to reduce the noise in the receive band during phase modulation is described in this paper.

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A Low Phase Noise Open Loop Fractional-N Frequency Synthesizer With Injection Locking Digital Phase Modulator

IEEE Transactions on Circuits & Systems II Express Briefs ◽

10.1109/tcsii.2019.2913023 ◽

2020 ◽

Vol 67 (3) ◽

pp. 455-459

Author(s):

Chenggang Yan ◽

Jianhui Wu ◽

Jie Sun ◽

Jin Jin ◽

Chen Hu

Keyword(s):

Phase Noise ◽

Frequency Synthesizer ◽

Open Loop ◽

Injection Locking ◽

Phase Modulator ◽

Digital Phase ◽

Low Phase Noise

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Impact of Carbohydrate Counting Error on Glycemic Control in Open-Loop Management of Type 1 Diabetes: Quantitative Assessment Through an in silico Trial

Journal of Diabetes Science and Technology ◽

10.1177/19322968211012392 ◽

2021 ◽

pp. 193229682110123

Author(s):

Chiara Roversi ◽

Martina Vettoretti ◽

Simone Del Favero ◽

Andrea Facchinetti ◽

Pratik Choudhary ◽

...

Keyword(s):

Type 1 Diabetes ◽

Glycemic Control ◽

In Silico ◽

Open Loop ◽

Random Errors ◽

Linear Regression Models ◽

Reference Case ◽

Counting Error ◽

The Impact

Background: In the management of type 1 diabetes (T1D), systematic and random errors in carb-counting can have an adverse effect on glycemic control. In this study, we performed an in silico trial aiming at quantifying the impact of different levels of carb-counting error on glycemic control. Methods: The T1D patient decision simulator was used to simulate 7-day glycemic profiles of 100 adults using open-loop therapy. The simulation was repeated for different values of systematic and random carb-counting errors, generated with Gaussian distribution varying the error mean from -10% to +10% and standard deviation (SD) from 0% to 50%. The effect of the error was evaluated by computing the difference of time inside (∆TIR), above (∆TAR) and below (∆TBR) the target glycemic range (70-180mg/dl) compared to the reference case, that is, absence of error. Finally, 3 linear regression models were developed to mathematically describe how error mean and SD variations result in ∆TIR, ∆TAR, and ∆TBR changes. Results: Random errors globally deteriorate the glycemic control; systematic underestimations lead to, on average, up to 5.2% more TAR than the reference case, while systematic overestimation results in up to 0.8% more TBR. The different time in range metrics were linearly related with error mean and SD ( R2>0.95), with slopes of [Formula: see text], [Formula: see text] for ∆TIR, [Formula: see text], [Formula: see text] for ∆TAR, and [Formula: see text], [Formula: see text] for ∆TBR. Conclusions: The quantification of carb-counting error impact performed in this work may be useful understanding causes of glycemic variability and the impact of possible therapy adjustments or behavior changes in different glucose metrics.

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A simplified coherent-detected radio-over-fiber link with intensity and phase modulation and simple digital phase noise cancellation

Optics Communications ◽

10.1016/j.optcom.2020.126700 ◽

2021 ◽

Vol 484 ◽

pp. 126700

Author(s):

Huixing Zhang ◽

Aijun Wen ◽

Wu Zhang ◽

Weipeng Zhang ◽

Wenjie Li

Keyword(s):

Phase Noise ◽

Phase Modulation ◽

Noise Cancellation ◽

Radio Over Fiber ◽

Digital Phase ◽

Fiber Link

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Highly Power-Efficient Active-RC Filters With Wide Bandwidth-Range Using Low-Gain Push-Pull Opamps

IEEE Transactions on Circuits and Systems I Regular Papers ◽

10.1109/tcsi.2012.2215700 ◽

2013 ◽

Vol 60 (1) ◽

pp. 95-107 ◽

Cited By ~ 44

Author(s):

Le Ye ◽

Congyin Shi ◽

Huailin Liao ◽

Ru Huang ◽

Yangyuan Wang

Keyword(s):

Wide Bandwidth ◽

Power Efficient

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Combined assimilation of streamflow and snow water equivalent for mid-term ensemble streamflow forecasts in snow-dominated regions

10.5194/hess-2016-166 ◽

2016 ◽

Author(s):

Jean M. Bergeron ◽

Mélanie Trudel ◽

Robert Leconte

Keyword(s):

Data Assimilation ◽

State Vector ◽

Snow Water Equivalent ◽

Synthetic Data ◽

Hydrologic Model ◽

Open Loop ◽

The State ◽

Wide Range ◽

Snow Water ◽

The Impact

Abstract. The potential of data assimilation for hydrologic predictions has been demonstrated in many research studies. Watersheds over which multiple observation types are available can potentially further benefit from data assimilation by having multiple updated states from which hydrologic predictions can be generated. However, the magnitude and time span of the impact of the assimilation of an observation varies according not only to its type, but also to the variables included in the state vector. This study examines the impact of multivariate synthetic data assimilation using the Ensemble Kalman Filter (EnKF) into the spatially distributed hydrologic model CEQUEAU for the mountainous Nechako River located in British-Columbia, Canada. Synthetic data includes daily snow cover area (SCA), daily measurements of snow water equivalent (SWE) at three different locations and daily streamflow data at the watershed outlet. Results show a large variability of the continuous rank probability skill score over a wide range of prediction horizons (days to weeks) depending on the state vector configuration and the type of observations assimilated. Overall, the variables most closely linearly linked to the observations are the ones worth considering adding to the state vector. The performance of the assimilation of basin-wide SCA, which does not have a decent proxy among potential state variables, does not surpass the open loop for any of the simulated variables. However, the assimilation of streamflow offers major improvements steadily throughout the year, but mainly over the short-term (up to 5 days) forecast horizons, while the impact of the assimilation of SWE gains more importance during the snowmelt period over the mid-term (up to 50 days) forecast horizon compared with open loop. The combined assimilation of streamflow and SWE performs better than its individual counterparts, offering improvements over all forecast horizons considered and throughout the whole year, including the critical period of snowmelt. This highlights the potential benefit of using multivariate data assimilation for streamflow predictions in snow-dominated regions.

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Contracts and Information Structure in a Supply Chain with Operations and Marketing Interaction

International Game Theory Review ◽

10.1142/s0219198916500146 ◽

2016 ◽

Vol 18 (04) ◽

pp. 1650014 ◽

Cited By ~ 1

Author(s):

Fouad El Ouardighi ◽

Gary Erickson ◽

Dieter Grass ◽

Steffen Jørgensen

Keyword(s):

Supply Chain ◽

Information Structure ◽

Wholesale Price ◽

Revenue Sharing ◽

Open Loop ◽

The State ◽

Current State ◽

Marketing Activities ◽

Purchase Rate ◽

The Impact

The objective of the paper is to study how wholesale price and revenue sharing contracts affect operations and marketing decisions in a supply chain under different dynamic informational structures. We suggest a differential game model of a supply chain consisting of a manufacturer and a single retailer that agree on the contract parameters at the outset of the game. The model includes key operational and marketing activities related to a single product in the supply chain. The manufacturer sets a production rate and the rate of advertising efforts while the retailer chooses a purchase rate and the consumer price. The state of the game is summarized in the firms’ backlogs and the manufacturer’s advertising goodwill. Depending on whether the supply chain members have and share state information, they may either make decisions contingent on the current state of the game (feedback Nash strategy), or precommit to a plan of action during the whole game (open-loop Nash strategy). Given a contract type, the impact of the availability of information regarding the state of the game on the firms’ decisions and payoffs is investigated. It is shown that double marginalization can be better mitigated if the supply chain members adopt a contingent strategy under a wholesale price contract and a commitment strategy under a revenue sharing contract.

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