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In this paper, an independently tunable linearizer (ITL) is proposed to offer a continuous tuning and individual compensation of AM/AM and AM/PM distortion of power amplifiers (PAs). Two new operating modes of linearizer have been extended from conventional linearizer which has a correlated expansion characteristic of gain and phase, a derivative factor of the linearizer's forward S-parameter is presented to characterize the modes and aided the ITL design. By synthesizing these modes, an ITL prototype is designed and fabricated at a center frequency of 3.5 GHz. The restrictions of the derivative factors during the design are analyzed and presented first, then the ITL is tested with a continuous wave (CW) and several Long Term Evolution (LTE) signals with different bandwidth and Peak to Average Power Ratio (PAPR), respectively. The results show that the independent tuning range of AM/AM and AM/PM is measured by more than 3.4 dB and 33 degrees, and the ITL can significantly improve the linearity of PAs with wideband stimulated up to a bandwidth of 55 MHz. Two different PAs achieve over −40 dBc of Adjacent Channel Power Ratio (ACPR) with the ITL. Furthermore, the power consumption of ITL is less than 0.5 W, the performance improvement does not increase the cost compared to conventional analog linearization.INDEX TERMS Analog linearization, power amplifier (PA), independently tunable linearizer (ITL), Schottky diode, extended operating modes, derivative factor, wideband signals.

For higher data throughput, the Massive Multi-input Multi-output (MIMO) system has been widely used in modern communication systems. Due to the circuit size and power consumption, it is difficult to integrate one Radio Frequency (RF) chain for each power amplifier (PA). As a result, MIMO transmitters with hybrid beam-forming don't have enough RF chains, and this demands the digital predistortion (DPD) block to deal with several power amplifiers (PA) simultaneously, which causes a shared DPD problem. This paper presents an Analog Predistorter Averaged DPD (A 2-DPD) for hybrid beam-forming massive MIMO transmitters. To linearize more than one PAs with one shared digital predistortion unit, continuously tunable Analog Predistortion (APD) modules are employed to uniform the nonlinear behavior of PAs in each channel. Based on iterative learning control (ILC) technique, crossed normalized mean square error (CNMSE) is derived to judge the uniformity of PAs. By comparing the CNMSE of each PAs, the best similarity state of PAs can be found. The nonlinear behavior of PAs can be adjusted to a similar state by tuning the APD control voltage. The adjustment makes PAs easier to be linearized by a shared DPD. Furthermore, an averaged DPD algorithm is proposed to improve the total linearity performance for each PA. Simulations are performed to study the relationship between CNMSE and PA uniformity and further simulations show the ability of A 2-DPD to deal with a multi-PA scenario. In the end, to verify the feasibility of the proposed A 2-DPD, two class-AB PAs with operating frequency at 3.5 GHz with the same type transistor and similar design are tested. Experimental results show the proposed A 2-DPD can significantly improve the uniformity of PAs and the Adjacent Channel Power Ratio (ACPR) can be improved by 8 dB compared with using the DPD parameter of the other PA.

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The total phosphorus (TP) concentration is a key water quality parameter for water monitoring and a major indicator of the state of eutrophication in inland lakes. Using remote-sensing to estimate TP concentration is useful, as it provides a synoptic view of the entire water region; however, the weak optical characteristics of TP lead to difficulty in accurately estimating TP concentration. The differences in water characteristics and components between lakes mean that most TP estimation methods are not applicable to all lakes. An artificial neural network (ANN) model was created to represent the correlation between TP concentration and the spectral bands of Moderate Resolution Imaging Spectroradiometer (MODIS) images in different research areas. We investigated the causal inference under the potential outcome framework to analyze the sensitivity of each band with regard to the TP concentration of different lakes for the research of water characteristics. Our results show that the accuracy of the ANN-based TP concentration estimation, with R2 > 0.73, root mean squared error (RMSE) < 0.037 mg/L in Lake Okeechobee and R2 > 0.73, RMSE < 4.1 μg/L in Lake Erie, respectively, is much higher than traditional empirical methods, e.g., linear regression. We found that the sensitive bands of TP concentration in Lake Erie are blue bands, whereas the sensitive bands in Lake Okeechobee are green bands. Various TP concentration maps were drawn to indicate the distribution of TP concentration and its tendency to change. The maps show that the distribution of TP concentration closely corresponds to the shore land-use, and a high TP concentration corresponds to the latest algal blooms breakout. Our proposed approach shows good potential for the remote-sensing estimation of TP concentration for inland lakes. Identifying the sensitive bands not only help characterize the lakes, but will also help the researchers to further observe the TP concentration of specific lakes in an efficient way.

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