Channel Capacity (Shannon)
Calculate the maximum channel capacity by the Shannon-Hartley law, C = B·log₂(1 + SNR), from the bandwidth B (Hz) and the signal-to-noise ratio SNR (linear value, not in dB). The result, in bits per second, is the absolute theoretical limit of error-free data rate a noisy channel can support — no modulation or coding can beat it. It shows the two paths to more speed: widen the bandwidth or improve the signal-to-noise ratio. It is a pillar of information theory and digital communication system design. Enter the bandwidth and the linear SNR.
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Channel capacity (Shannon-Hartley)
In 1948, Claude Shannon established the fundamental limit of any communication channel: there is a maximum data rate that can be transmitted with arbitrarily small error, and no amount of clever modulation or coding can push past it. That channel capacity is given by the Shannon-Hartley law: C = B·log₂(1 + SNR), where B is the bandwidth (Hz) and SNR is the signal-to-noise ratio as a linear value (careful: not in dB — if your SNR comes in dB, convert it first with 10^(SNR_dB/10)). The result is the capacity in bits per second. The formula reveals the two roads to more throughput: widen the band (a linear relationship) or improve the SNR (only logarithmic — doubling the transmit power buys very little). That is why modern systems chase spectrum (5G in millimetre waves, Wi-Fi 6E) instead of simply cranking up power, and why technologies such as MIMO, which effectively create multiple parallel channels, are so valuable. Shannon capacity is the yardstick against which the efficiency of any real transmission scheme is measured. Enter the bandwidth and the linear SNR.
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