Eb/N0

E_b/N_0 is closely related to the carrier-to-noise ratio (CNR or \frac{C}{N}), i.e. the signal-to-noise ratio (SNR) of the received signal, after the receiver filter but before detection: \frac{C}{N} = \frac{E_\text{b}}{N_0} \frac{f_\text{b}}{B} wheref_b is the channel data rate (net bit rate) and is the channel bandwidth. The equivalent expression in logarithmic form (dB): \text{CNR}_\text{dB} = 10\log_{10}\left(\frac{E_\text{b}}{N_0}\right) + 10\log_{10}\left(\frac{f_\text{b}}{B}\right) Caution: Sometimes, the noise power is denoted by N_0/2 when negative frequencies and complex-valued equivalent baseband signals are considered rather than passband signals, and in that case, there will be a 3 dB difference. == Relation to Es/N0 ==

E_b/N_0 can be seen as a normalized measure of the energy per symbol to noise power spectral density (E_s/N_0): \frac{E_b}{N_0} = \frac{E_\text{s}}{\rho N_0} where E_s is the energy per symbol in joules and is the nominal spectral efficiency in (bits/s)/Hz. E_s/N_0 is also commonly used in the analysis of digital modulation schemes. The two quotients are related to each other according to the following: \frac{E_\text{s}}{N_0} = \frac{E_\text{b}}{N_0} \log_2(M) where is the number of alternative modulation symbols, e.g. M = 4 for QPSK and M = 8 for 8PSK. This is the energy per bit, not the energy per information bit. E_s/N_0 can further be expressed as: \frac{E_\text{s}}{N_0} = \frac{C}{N}\frac{B}{f_\text{s}} where\frac{C}{N} is the carrier-to-noise ratio or signal-to-noise ratio, is the channel bandwidth in hertz, andf_s is the symbol rate in baud or symbols per second. == Shannon limit ==

The Shannon–Hartley theorem says that the limit of reliable information rate (data rate exclusive of error-correcting codes) of a channel depends on bandwidth and signal-to-noise ratio according to: I where is the information rate in bits per second excluding error-correcting codes, is the bandwidth of the channel in hertz, is the total signal power (equivalent to the carrier power ), and is the total noise power in the bandwidth. This equation can be used to establish a bound on E_b/N_0 for any system that achieves reliable communication, by considering a gross bit rate equal to the net bit rate and therefore an average energy per bit of E_b = S/R, with noise spectral density of N_0 = N/B. For this calculation, it is conventional to define a normalized rate R_l = R/(2B), a bandwidth utilization parameter of bits per second per half hertz, or bits per dimension (a signal of bandwidth can be encoded with 2B dimensions, according to the Nyquist–Shannon sampling theorem). Making appropriate substitutions, the Shannon limit is: {R \over B} = 2 R_l Which can be solved to get the Shannon-limit bound on E_b/N_0: \frac{E_\text{b}}{N_0} > \frac{2^{2R_l} - 1}{2R_l} When the data rate is small compared to the bandwidth, so that R_l is near zero, the bound, sometimes called the ultimate Shannon limit, is: \frac{E_\text{b}}{N_0} > \ln(2) which corresponds to −1.59dB. This often-quoted limit of −1.59 dB applies only to the theoretical case of infinite bandwidth. The Shannon limit for finite-bandwidth signals is always higher. == Cutoff rate ==

For any given system of coding and decoding, there exists what is known as a cutoff rate R_0, typically corresponding to an E_b/N_0 about 2 dB above the Shannon capacity limit. The cutoff rate used to be thought of as the limit on practical error correction codes without an unbounded increase in processing complexity, but has been rendered largely obsolete by the more recent discovery of turbo codes, low-density parity-check (LDPC) and polar codes. == References ==