Shannon Capacity Theorem

Shannon capacity theorem in which you will learn about the channel capacity with the bandwidth of the channel and SNR. The theorem states that for a given communication channel with a certain bandwidth and SNR, there exits a maximum achievable data rate, called the channel capacity.

1. QUAID-E-AWAM UNIVERSITY OF ENGINEERING SCIENCE AND TECHNOLOGY, NAWABSHAH DEPARTMENT OF ELECTRONIC ENGINEERING Title: Shannon’s Capacity Theorem: Name: Laiba Hasan Roll No: 19ES50 Department: Electronic Engineering Assigned By: Dr. Nadeem Naeem

2. Shannon’s Capacity Theorem: In reality, all channels are noisy. Shannon capacity theorem defines the theoretical highest data rate for a noisy channel: C = B log 2 (1 + SNR) C is the channel capacity in bits per second. B is the bandwidth of the channel in hertz. SNR is the signal to noise ratio.

3. Shannon’s Capacity Theorem: Data rate at which date can be communicated, in bits per second. Higher the signal-to-noise (SNR) ratio and more the channel bandwidth, the higher the possible data rate. Channel capacity C is the speed. There is no indication of the signal level.

4. Consider an extremely noisy channel in which the value of the signal-to-noise ratio is almost zero. In other words, the noise is so strong that the signal is faint. For this channel the capacity C is: This means that the capacity of this channel is zero regardless of the bandwidth. In other words, we cannot receive any data through this channel.

5. . A telephone line normally has a bandwidth of 3000. The signal-to-noise ratio is usually 3162. For this channel the capacity is: This means that the highest bit rate for a telephone line is 34.860 kbps.

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