Basic hardware comprehension of an artificial neural network (ANN), to a major scale depends on the proficientrealization of a distinctneuron. For hardware execution of NNs, mostly FPGA-designed reconfigurable computing systems are favorable .FPGA comprehension of ANNs through a hugeamount of neurons is mainlyan exigentassignment. This workconverses the reviews on various research articles of neural networks whose concernsfocused in execution of more than one input neuron and multilayer with or without linearity property by using FPGA. An execution technique through reserve substitution isprojected to adjust signed decimal facts. A detailed review of many research papers have been done for the <br /> proposed work.
This paper presents a bias modulation linearization technique for a 919-923 MHz CMOS power amplifier which employs driver voltage modulation and main amplifier split bias. Through the proposed linearization technique, it is observed that the peak third-order intercept point (OIP3) across the output power is shifting according to the bias conditions of the split-bias power amplifier (SBPA). The third-order transconductance (gm3) terms are suppressed at the output by phase cancellation achieved by optimization of the bias voltages of the PA. A high dynamic range bias circuit is integrated at the driver and split main to enhance the linearity of the CMOS PA, eradicating the need for pre-distortion linearizers. The two-stage SBPA is designed and fabricated in a 180 nm CMOS process with six-metal layers and a chip size of 1.820 x 1.771 mm 2 to operate at the supply voltage of 3.3 V. The bias voltages of both driver and split main stages are varied from 0 V to 2.0 V with a linear step size of 0.2 V. The proposed SBPA delivers a saturated output power (Pout) of 27 dBm with maximum power-added efficiency (PAE) of 44.4 % and peak OIP3 of 39 dBm. A maximum linear Pout of 21 dBm with 29 % PAE is achieved at an adjacent channel leakage ratio (ACLR) of -30 dBc and 4 % error vector magnitude (EVM), satisfying the LoRa specifications.INDEX TERMS Adjacent channel leakage ratio (ACLR), bias circuit, complementary metal-oxidesemiconductor (CMOS), error vector magnitude (EVM), intermodulation distortion (IMD), long-range (LoRa), power amplifier, radio frequency power amplifier (RFPA), third-order intercept point (OIP3)
LoRa (Short for Long Range) is the fastest growing technology attracting researcher's interest now a days. Long battery life, long distance communication and low cost application specific devices are main focus of the engineers, LoRa is quite suitable for these requirements. IoT system includes four explicit sections for example sensors/devices, connectivity, processing of information and a user interface. The scope of communication has become the basic part on the majority of the IoT system, particularly in Wi-Fi and Bluetooth based IoT system. With the rise of LoRa technology, further enhancements to uses of the Internet of Things (IoT) can be figured it out. By utilizing a single receiver in the LoRa network, it can deal with numerous hubs at various areas inside the region, dissimilar to Wi-Fi-based framework which needs to have many access point to cover large area. Both LoRa and Wi-Fi innovation has reduced total cost of IoT framework. For the wide range coverage of IoT system, LoRa is quite useful as compared to Wi-Fi and Bluetooth for short range. However, there are a few inconveniences on the speed of transmission and constraint on the size of the payload. The world when struggling with the COVID-19 pandemic, LoRa devices and the LoRaWAN protocol are playing an instrumental role in enabling public safety solutions to assist with contact tracing, ensuring healthcare regulation compliance in the workplace and addressing the needs of medical professionals. This paper presents a specialized work on LoRa/LoRaWAN innovation for IoT applications.
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