Computer network basics: Physical Layer

Today, let's talk about the physical layer under the five-layer structure of the Computer Network. The physical layer is mainly to convert the information encapsulated at the data link layer into analog signals and transmit it to the terminal through the media, the digital signal required at the upper layer of the terminal's physical layer.

First, starting from the transmission of analog signals, physical layer signals are transmitted through various analog signals, and various irregular curves are intertwined (from the time domain perspective ), each electrical signal can be viewed as a sine wave. the superposition of multiple waveforms forms a waveform similar to a square wave. The waveform is converted to a digital signal by the modem, the Fourier transform is used to parse different signals in the frequency field, and then the sampling and quantization are used to convert them into bit, which further forms the code element for transmission.

The so-called sampling refers to the division of the simulated signal on the timeline to form a discrete point, and the division of the interval at which the discrete point can completely simulate the original signal. Here, nycept puts forward the ideal interval t = 1/2f (max ), this optimal interval means that the discrete points separated to this extent are enough to restore the original analog signal, and the effect of <t is similar to that of the original analog signal. However, in this ideal situation, noise is excluded. The superposition of noise increases the value of F (max), thus reducing the time interval, of course, this reduction is meaningless for message restoration, and for the quantization of sampling, this split is a waste of resources.

For quantization, discrete points are divided into different levels, which means the number of BITs is used to represent different points. Therefore, the quantization task is to digitize analog signals, it becomes the bit we use in the computer.

We all know that the higher the data transmission rate, the worse the signal quality, but the reason is that it is related to the frequency and the number of harmonic values that can be included at different rates. Some data analysis can show that, the characteristic of their changes is that the speed is proportional to the 1/quality. And when the speed reaches a certain number, it can contain 0 harmonic digits, that is, it does not contain any data.

The ideal and realistic conditions are taken into account for the calculation of the data transmission rate. under ideal conditions, it is also the calculation formula V = 2hlog2v proposed by niquest, h indicates the signal bandwidth through the low-pass filter, which is determined by the transmission medium. V indicates the number of discrete levels after the data is quantified, therefore, what log2v calculates is how many bits are used to represent this signal. For the actual situation, we need to consider the impact of noise. Therefore, the signal-to-noise ratio (S/N = signal/noise) is introduced ), the signal-to-noise ratio may be unfamiliar. For decibels, I believe everyone is familiar with it. decibels are units of signal-to-noise ratio (db) = 10lg (S/N) (db ). Based on the signal-to-noise ratio (SNR), Shannon proposed the ultimate information transmission rate of the channel C = hlog2 (1 + S/N) (BPS ).

The next concept is bandwidth. Each network has its own bandwidth. The larger the bandwidth, the wider the signal frequency. The current control source of network bandwidth is a filter, which is a filter parameter. When the bandwidth exceeds the set value, the high-frequency signal will be discarded and the remaining signal will be sent to the receiver. Generally, noise is the most frequently used wave, and low-frequency wave is truly valuable.

 

Computer network basics: Physical Layer