It is a little unusual to describe a hardware radio on a website that focuses on software radios. But I was impressed with the functionality and performance of AT86RF215 transceivers by Microchip during my experiments. I have used them for node localization and they can be put to many other good uses, including, …. here is the surprise, …. as software defined radios. Through a little programming effort, I/Q samples from the digital frontend can be directly accessed using which you can run your own baseband on a digital signal processor. Although interfacing with an external device for I/Q samples

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## How to Compute SINAD in a Radio Receiver

In theory, the quantity that determines the performance of a radio receiver is the Signal to Noise Ratio (SNR). In linear terms, this is simply the ratio of the signal power versus the noise power appearing at the demodulator input. \[ SNR = 10\log_{10} \frac{P_S}{P_N} \] where $P_S$ is the signal power and $P_N$ is the noise power within the spectrum. However, when experimental measurements are carried out in order to verify the theoretical conclusions, SNR alone is not enough and there is another quantity, known as SINAD, that governs the receiver performance. What is SINAD SINAD stands for Signal

Continue reading## On Analog-to-Digital Converter (ADC), 6 dB SNR Gain per Bit, Oversampling and Undersampling

We have discussed before the sampling on time axis for analog to digital (A/D) conversion. An Analog to Digital Converter (ADC) produces the samples $x[n]$ of a continuous-time signal $x(t)$ at its input. Ideally, these samples are the exact values of the signal $x(t)$ at time instants $nT_s$ where $T_s=1/f_s$ is the sampling period. In practice, however, there are imperfections both on the y-axis and the x-axis. On y-axis, an ADC has a finite resolution depending on the number of bits used for quantization. On x-axis, there are issues of clock jitter that distort the samples produced. In this article,

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