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Broadband GaAs FET power amplifier for L and S bands applications

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    This article describes a methodology for designing broadband high‐efficiency GaN HEMT power amplifier (PA) which is suitable for base stations and modern wireless communication based on the Class‐EF mode. To achieve both efficiency enhancement and bandwidth extension for the PA, the load‐pull technique is employed to acquire the optimum impedance regions of the second harmonic. Especially, considering the influences of the harmonic control network on the accuracy of obtaining the fundamental impedance, the load‐pull technique is performed to obtain the optimal fundamental impedance again after the harmonic control circuit is determined. In addition, the theory of multiple frequencies matching is also employed to manipulate six desired fundamental frequency points concurrently. Based on the proposed theory, the Class‐EF PA prototype is designed and fabricated. The measurement results exhibits a drain efficiency (DE) of 60%–75% in the range of 2.1–3.6 GHz while having an output power of 38–40.5 dBm and gain of larger than 8 dB.

     

    When using a unity gain operational amplifier (op amp) to buffer a voltage standard, what should I know to be sure that the voltage out is exactly the same as the voltage in?

     

    In this paper, targeting at improving the energy efficiency (EE) for Quality-of-Service (QoS)-guaranteed wireless communications, we develop new adaptive modulation and data scheduling algorithms for delay-sensitive bursty data. Assuming a-priori knowledge on data arrivals and latency requirements, the problem is formulated as a mix-integer programming that minimizes the total energy consumption at the transmitter with a non-linear Doherty power amplifier (PA) and non-negligible circuit power. According to the different properties of the PA in different output power regions, we decouple the formulated problem and solve it in two stages. In the first stage, assuming the PA has a linear efficiency, we develop an optimal modulation and data scheduling scheme (MDS) relying on convex relaxation and the resultant optimality conditions. The MDS is able to reveal the specific structure of the optimal policy in a computationally efficient and graphical manner. On top of that, a heuristic MDS scheme (HMDS) is proposed to adjust the MDS when the PA works in the non-linear region in the second stage, where a quadratic function is obtained to approximate the non-linear PA model. The offline HMDS algorithm is further extended to practical online scenarios in a well-structured way, where the modulation and data scheduling policy is produced on-the-fly. Simulation corroborates that the proposed offline algorithm can achieve the exactly same performance as the standard CVX solver, while requiring only 0.69% of its computational time.

     

    Specific transmitter identification (SEI) is a technology that uses a received signal to identify to which individual radiation source the transmitted signal belongs. It can complete the identification of the signal transmitter in a non-cooperative scenario. Therefore, there are broad application prospects in the field of wireless-communication-network security, spectral resource management, and military battlefield-target communication countermeasures. This article demodulates and reconstructs a digital modulation signal to obtain a signal without modulator distortion and power-amplifier nonlinearity. Comparing the reconstructed signal with the actual received signal, the coefficient representation of the nonlinearity of the power amplifier and the distortion of the modulator can be obtained, and these coefficients can be used as the fingerprint characteristics of different transmitters through a convolutional neural network (CNN) to complete the identification of specific transmitters. The existing SEI strategy for changing the modulation parameters of a test signal is to mix part of the test signal with the training signal so that the classifier can learn the signal of which the modulation parameter was changed. This method is still data-oriented and cannot process signals for which the classifier has not been trained. It has certain limitations in practical applications. We compared the fingerprint features extracted by the method in this study with the fingerprint features extracted by the bispectral method. When SNR < 20 dB, the recognition accuracy of the bispectral method dropped rapidly. The method in this paper still achieved 86% recognition accuracy when SNR = 0 dB. When the carrier frequency of the test signal was changed, the bispectral feature failed, and the proposed method could still achieve a recognition accuracy of about 70%. When changing the test-signal baud rate, the proposed method could still achieve a classification accuracy rate of more than 70% for four different individual radiation sources when SNR = 0 dB.

     

    Regardless of the type of amplifier, its performance needs to comply with the frequency range, amplitude and other parameters outlined by industry standards in order to successfully carry out its intended function.

     

    Power amplifier (PA) nonlinearity is typically unique at the radio frequency (RF) front-end for particular emitters. It can play a crucial role in the application of specific emitter identification (SEI). In this paper, under the Multi-Input Multi-Output (MIMO) multipath communication scenario, two data-aided approaches are proposed to identify multi-antenna emitters using PA nonlinearity. Built upon a memoryless polynomial model, the first approach formulates a linear least square (LLS) problem and presents the closed-form solution of nonlinear coefficients in a MIMO system by means of singular value decomposition (SVD) operation. Another alternative approach estimates nonlinear coefficients of each individual PA through nonlinear least square (NLS) solved by the regularized Gauss–Newton iterative scheme. Moreover, there are some practical discussions of our proposed approaches about the mismatch of the order of PA model and the rank-deficient condition. Finally, the average misclassification rate is derived based on the minimum error probability (MEP) criterion, and the proposed approaches are validated to be effective through extensively numerical simulations.

     

    This article presents a compact broadband high‐efficiency power amplifier (PA) with a filtering structure. Unlike the cascaded filter behind the traditional PA, the proposed cascaded branch load coupling microstrip line structure is used to design the output matching network (OMN) of the PA. It plays the roles of impedance matching and filtering, which is called a filtering OMN, the overall size of the circuit will be reduced. Two coupled microstrip lines cascaded are used to extend the working bandwidth, and a microstrip line is loaded to the port of the coupled microstrip lines to ensure high selectivity and good out‐of‐band performance. For verification, a broadband high‐efficiency PA is designed and manufactured by using CGH40010F GaN HEMT. Measurements demonstrate that in the range from 1.2 to 3.6 GHz, the saturated output power is from 39.8 to 41.8 dBm, the drain efficiency (DE) with a 62%–73%, and the gain is between 9.9 and 11.7 dB.

     

    It depends on what you are trying to do. Generally you can produce a 100 MHz signal by making an oscillator. You can make a tuned amplifier oscillate at whatever power level you want to design for. The frequency stability of the output depends on the Q of the resonant circuit(s). The frequency will also vary with the load. This approach may be suitable if the output is used to heat a load.

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