Automatic transmit power control for power efficient communications in UAS

Nowadays, unmanned aerial vehicles (UAV) have become one of the most popular tools that can be used in commercial, scientific, agricultural and military applications. As drones become faster, smaller and cheaper, with the ability to add payloads, the usage of the drone can be versatile. In most of the cases, unmanned aerials systems (UAS) are equipped with a wireless communication system to establish a link with the ground control station to transfer the control commands, video stream, and payload data. However, with the limited onboard calculation resources in the UAS, and the growing size and volume of the payload data, computational complex signal processing such as deep learning cannot be easily done on the drone. Hence, in many drone applications, the UAS is just a tool for capturing and storing data, and then the data is post-processed off-line in a more powerful computing device. The other solution is to stream payload data to the ground control station (GCS) and let the powerful computer on the ground station to handle these data in real-time. With the development of communication techniques such as orthogonal frequency-division multiplexing (OFDM) and multiple-input multiple-output (MIMO) transmissions, it is possible to increase the spectral efficiency over large bandwidths and consequently achieve high transmission rates. However, the drone and the communication system are usually being designed separately, which means that regardless of the situation of the drone, the communication system is working independently to provide the data link. Consequently, by taking into account the position of the drone, the communication system has some room to optimize the link budget efficiency. In this master thesis, a power-efficient wireless communication downlink for UAS has been designed. It is achieved by developing an automatic transmit power control system and a custom OFDM communication system. The work has been divided into three parts: research of the drone communication system, an optimized communication system design and finally, FPGA implementation. In the first part, an overview on commercial drone communication schemes is presented and discussed. The advantages and disadvantages shown are the source of inspiration for improvement. With these ideas, an optimized scheme is presented. In the second part, an automatic transmit power control system for UAV wireless communication and a power-efficient OFDM downlink scheme are proposed. The automatic transmit power control system can estimate the required power level by the relative position between the drone and the GCS and then inform the system to adjust the power amplifier (PA) gain and power supply settings. To obtain high power efficiency for different output power levels, a searching strategy has been applied to the PA testbed to find out the best voltage supply and gain configurations. Besides, the OFDM signal generation developed in Python can encode data bytes to the baseband signal for testing purpose. Digital predistortion (DPD) linearization has been included in the transmitter’s design to guarantee the signal linearity. In the third part, two core algorithms: IFFT and LUT-based DPD, have been implemented in the FPGA platform to meet the real-time and high-speed I/O requirements. By using the high-level synthesis design process provided by Xilinx Corp, the algorithms are implemented as reusable IP blocks. The conclusion of the project is given in the end, including the summary of the proposed drone communication system and envisioning possible future lines of research

Topoisomerase II trapping agent teniposide induces apoptosis and G2/M or S phase arrest of oral squamous cell carcinoma

BACKGROUND: Teniposide (VM-26) has been widely used in the treatment of small cell lung cancer, malignant lymphoma, breast cancer, etc. However, there are few reports on VM-26 against oral cancers. The present study was designed to identify the effect of VM-26 against oral squamous cell carcinoma in vitro, and to provide evidence for the feasibility and effectiveness of VM-26 for application to the patients with oral cancer. METHODS: Human tongue squamous cell carcinoma cell line, Tca8113, was used. Cells were incubated with different concentrations of VM-26 for a variety of time span. Cisplatin (CDDP) was employed as a control reagent. MTT assay was used to assess the inhibitory rate of Tca8113 growth. Flow cytometer (FCM), transmission electronic microscope (TEM) and fluorescence staining were employed for determining the cell apoptotic rate. Cell cycle distribution of Tca8113 incubated with VM-26 was examined by flow cytometer assay. Statistic software (SAS 6.12, USA) was used for one-way ANOVA. RESULTS: The IC50 of VM-26 against Tca8113 cells was 0.35 mg/l and that of CDDP was 1.1 mg/l. The morphological changes of Tca8113 cells were observed with fluorescence microscope and TEM. Apoptotic morphological feature could be found in the nucleus. Apoptotic rate of Tca8113 cells incubated with 5.0 mg/l of VM-26 for 72 hours was 81.67% and cells waere arrested at S phase. However, when exposed to 0.15 mg/l of VM-26 for 72 hours, G2/M phase increased from 12.75% to 98.71%, while the apoptotic rate was 17.38%, which was lower than that exposed to 5.0 mg/l of VM-26. CONCLUSION: VM-26 could significantly induce apoptosis of oral squamous cell carcinoma and inhibit cell growth. There may be another pathway to induce apoptosis of oral squamous cell carcinoma cells except for G2/M phase arrest

Agnostic envelope linearization of dynamically supplied power amplifiers for mobile terminals

This paper presents an envelope linearization technique to compensate for the nonlinear distortion of envelope tracking (ET) power amplifiers (PAs) for 5G new radio (NR) mobile terminals. The proposed envelope optimization (EOPT) method is agnostic of the nonlinear distortion generated in the envelope supply path and can compensate for the nonlinear distortion at the ET PA output without the need to monitor the output at the envelope tracking modulator (ETM). The linearization system in the envelope path is based on the envelope generalized memory polynomial (EGMP) behavioral model. Since the ETM output is not available, an iterative nonlinear least squares solution inspired in the deep deterministic policy gradient (DDPG) algorithm is proposed to extract the coefficients of the EGMP model. The EOPT method is validated on a system-on-chip (SoC) ET PA board designed for mobile terminal applications. Experimental results show the suitability of the proposed method to guarantee the linearity requirements (i.e., adjacent channel power ratio below -36 dBc) with 16.8% of power efficiency when operating the ET PA with 5G new radio test signals of 60 MHz bandwidth operating at 2.55 GHz (band 7). The linearization performance of the proposed EOPT method is comparable to the envelope leakage cancellation (ELC) approach (but saving the need for an analog to digital converter to monitor the ETM output), and can outperform a conventional I-Q digital predistorter based on the generalized memory polynomial (GMP) behavioral model.This research was funded by Huawei Technologies from July 2020 to August 2021; and supported in part by the project PID2020-113832RB-C21 funded by MCIN/AEI/10.13039/50110001103 and in part by the Government of Catalonia and the European Social Fund under Grant 2021-FI-B-137.Peer ReviewedPostprint (published version

Reconfigurable DPD based on ANNs for wideband load modulated balanced amplifiers under dynamic operation from 1.8 to 2.4 GHz

This article proposes a methodology to ensure linear amplification of a load modulated balanced amplifier (LMBA) while keeping the power efficiency as high as possible over a frequency band ranging from 1.8 to 2.4 GHz and where the transmitted signals can present different bandwidth (BW) configurations. The proposed reconfigurable linearization methodology consists of, in a first step, tuning some free parameters (with dependence on the signal BW and frequency of operation) of the LMBA to trade-off linearity and power efficiency. In a second step, two multipurpose adaptive digital predistortion (DPD) linearizers are considered, properly combined with crest factor reduction (CFR) techniques, to meet the required linearity specifications. Either a DPD based on artificial neural networks or a DPD based on polynomials can be selected taking into account the compromise between computational complexity and linearization performance. Experimental results will validate the proposed methodology to guarantee the linearity levels (ACPR < -45 dBc and EVM < 1%) with high power efficiency in an LMBA under dynamic transmission, where both the signal BW (from 20 and up to 200-MHz instantaneous BW) and frequency of operation (in the range of 1.8-2.4 GHz) change.This work was supported in part by the Spanish Government (Ministerio de Ciencia, Innovación y Universidades) and FEDER (Fondo Europeo de Desarrollo Regional) under Grant TEC2017-83343-C4-2-R and in part by the Generalitat de Catalunya under Grant 2017 SGR 813. This paper is an expanded version from the International Workshop on Integrated Nonlinear Microwave and Millimetre-Wave Circuits (INMMiC), Cardiff, United Kingdom, July 2020.Peer ReviewedPostprint (author's final draft

Machine-learning assisted optimisation of free-parameters of a dual-input power amplifier for wideband applications

This paper presents an auto-tuning approach for dual-input power amplifiers using a combination of global optimisation search algorithms and adaptive linearisation in the optimisation of a multiple-input power amplifier. The objective is to exploit the extra degrees of freedom provided by dual-input topologies to enhance the power efficiency figures along wide signal bandwidths and high peak-to-average power ratio values, while being compliant with the linearity requirements. By using heuristic search global optimisation algorithms, such as the simulated annealing or the adaptive Lipschitz Optimisation, it is possible to find the best parameter configuration for PA biasing, signal calibration, and digital predistortion linearisation to help mitigating the inherent trade-off between linearity and power efficiency. Experimental results using a load-modulated balanced amplifier as device-under-test showed that after properly tuning the selected free-parameters it was possible to maximise the power efficiency when considering long-term evolution signals with different bandwidths. For example, a carrier aggregated a long-term evolution signal with up to 200 MHz instantaneous bandwidth and a peak-to-average power ratio greater than 10 dB, and was amplified with a mean output power around 33 dBm and 22.2% of mean power efficiency while meeting the in-band (error vector magnitude lower than 1%) and out-of-band (adjacent channel leakage ratio lower than −45 dBc) linearity requirements

Reconfigurable DPD based on ANNs for wideband load modulated balanced amplifiers under dynamic operation from 1.8 to 2.4 GHz

This article proposes a methodology to ensure linear amplification of a load modulated balanced amplifier (LMBA) while keeping the power efficiency as high as possible over a frequency band ranging from 1.8 to 2.4 GHz and where the transmitted signals can present different bandwidth (BW) configurations. The proposed reconfigurable linearization methodology consists of, in a first step, tuning some free parameters (with dependence on the signal BW and frequency of operation) of the LMBA to trade-off linearity and power efficiency. In a second step, two multipurpose adaptive digital predistortion (DPD) linearizers are considered, properly combined with crest factor reduction (CFR) techniques, to meet the required linearity specifications. Either a DPD based on artificial neural networks or a DPD based on polynomials can be selected taking into account the compromise between computational complexity and linearization performance. Experimental results will validate the proposed methodology to guarantee the linearity levels (ACPR < -45 dBc and EVM < 1%) with high power efficiency in an LMBA under dynamic transmission, where both the signal BW (from 20 and up to 200-MHz instantaneous BW) and frequency of operation (in the range of 1.8-2.4 GHz) change

The molecular mechanism of ferroptosis and its role in COPD

Ferroptosis, a new type of cell death, is mainly characterized by intracellular iron accumulation and lipid peroxidation. The complex regulatory network of iron metabolism, lipid metabolism, amino acid metabolism, p53-related signaling, and Nrf2-related signaling factors is involved in the entire process of ferroptosis. It has been reported that ferroptosis is involved in the pathogenesis of neurological diseases, cancer, and ischemia–reperfusion injury. Recent studies found that ferroptosis is closely related to the pathogenesis of COPD, which, to some extent, indicates that ferroptosis is a potential therapeutic target for COPD. This article mainly discusses the related mechanisms of ferroptosis, including metabolic regulation and signaling pathway regulation, with special attention to its role in the pathogenesis of COPD, aiming to provide safe and effective therapeutic targets for chronic airway inflammatory diseases

Performance modeling and shaping function extraction for dual-input load modulated power amplifiers

This paper proposes the method of extracting a shaping function for operating a family of Dual Input Power Amplifiers operating with modulated signals such as OFDM-based 5G new radio (NR) signals. The shaping function describing the drive profile for each input was implemented using a Look-Up Table (LUT) approach. This table can be constructed from the previously measured PA data to target various objectives, such as linearity or efficiency. The paper focuses on performance modelling to have a smooth mathematical equation to predict performance. Based on the prediction, we can extract the shaping function targeting the maximization of linearity or efficiency. Experimental results were conducted with a 100 MHz bandwidth 5G NR signal with a 30 kHz subcarrier spacing. The linearize ability of different objectives is evaluated with digital predistortion