The spectrum analyzer's display average noise level (DANL) sensitivity of 172dBm/Hz is only 2dB away from the theoretical thermal noise limit of -174dBm. What kind of black technology is used in modern spectrum analyzers?
Generally speaking, the test sensitivity refers to the minimum signal that can be tested, which is generally 4 to 5 dB larger than the noise floor of the instrument, which means that the test sensitivity is mainly determined by the noise floor. When testing small signals, if the noise floor of the spectrum analyzer is high, the small signal will be buried in a noise floor and cannot be observed. At this point, the sensitivity of the spectrum analyzer becomes very important.
For instrumentation, the weak signal being measured can be considered as a signal close to the instrument's noise floor or below the noise floor. Most spectrum analyzer users know that signals that are measured within 20 dB of the average noise level of the analyzer will be affected by the noise floor of the instrument, making the measurement worse.
The result of the spectrometer measurement is the superposition of the RF input signal spectrum and the instrument noise spectrum. Is it possible to measure the noise floor noise floor and then subtract the noise floor from each measurement result of the spectrum analyzer?
The noise floor extension technique is a correction algorithm that improves the measurement accuracy by using the noise floor of a known instrument, and is a measurement method that subtracts the noise floor of the front end and analyzes and displays only the power level of the input signal. Not only can the measurement accuracy be improved, but also the dynamic range can be extended.
Assume that when there is no signal input (N), the instrument display power level is -90dBm. When the signal to be measured is input (S+N), the instrument display power level is -87 dBm. If the signal is not correlated, N is the initial measurement result. S+N second measurement result, then what is the exact power value of the measured signal (S)?
Known: N = -90dBm = 10-9mW;
S+N = -87dBm = 2&TImes; 10-9mW;
It is concluded that: S = 10-9mW = -90dBm;
Assume that when the signal under test is input, the display power level is -89dBm, ie
S+N = -89dBm = 1.259&TImes;10-9mW;
Then S = 0.259 & TImes; 10-9mW = -95.87dBm;
It can be seen that the power of the signal under test is nearly -6dBm lower than the noise floor power of the instrument. This seems impossible, but it is calculated based on the law of conservation of energy. The figure below shows the adjacent channel power measurement when the noise correction function is turned off.
Figure 1 Adjacent channel power measurement results when noise correction function is not used
Spectrum analyzer noise correction function: In the first step, press the [Measurement Settings] button on the front panel of the spectrum analyzer; in the second step, find the [Noise Correction Switch] in the [Measurement Settings] soft menu to ensure that the noise correction is on. At this point, the spectrum analyzer automatically measures the noise floor of the current instrument. Wait patiently for the measurement results. Figure 2 shows the adjacent channel power measurement results when the noise correction function is turned on.
Figure 2 Adjacent channel power measurement results when the noise correction function is turned on
It is very effective to measure noise-like signals using the noise correction function, especially for low-power signals, which can extend the dynamic range of channel power and adjacent channel power measurement by nearly 10 dB.
Application-Specific Integrated Circuit refers to an integrated circuit specifically designed to perform a specific computing task. It is very common to use ASIC for mining in the field of blockchain. This article will analyze the principle of ASIC mining and why it should be anti-ASIC.
For Bitcoin, mining has gone through four stages: CPU, GPU, FPGA and ASIC. GPU is naturally suitable for parallel simple operations, so the execution of SHA256 is much higher than the CPU. FPGA is a programmable hardware, because it has a certain degree of universality, so the unit price will be relatively expensive. ASIC has a large initial design investment, but the unit price will be cheaper after mass production. Therefore, if you can determine that the market size is relatively large, the use of ASIC technology will be the most cost-effective.
This is the basic principle of ASIC.
In a nutshell, mining is running complicated calculations in the search for a specific number. Whether it`s an ASIC miner or a GPU mining rig, mining hardware must run through many calculations before finding that number. In proof of work systems like Bitcoin, the first one to find that number gets a reward - at the time of writing, 12.5 Bitcoins worth around $96,850. That reward will fall to 6.25 Bitcoins in May 2020.
There are so many people and powerful computing systems trying to mine Bitcoin that miner groups form to find that number and share the profit. Even more, the faster your hardware, the more you earn. That`s why people who can afford it opt for ASIC miners because it gives them the greatest chance of earning cryptocurrency in exchange for their investment.
Each cryptocurrency has its own cryptographic hash algorithm, and ASIC miners are designed to mine using that specific algorithm. Bitcoin ASIC miners are actually designed to calculate the SHA-256 hash algorithm. In the case of Litecoin, it uses Scrypt. That means technically they could mine any other coin that`s based on the same algorithm, though typically, people who buy ASIC hardware designed for Bitcoin mine that specific digital currency.
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