Short notes

Companding Short Notes

Inside a G.711 PCM codec used in every telephone exchange, weak speech signals would be buried in quantisation noise if uniform quantisation were used. Companding fixes this by compressing the signal at the transmitter before 8-bit quantisation and then expanding it at the receiver — the combined compress-and-expand action is what gives the technique its name. The μ-law encoder used in North America and the A-law encoder standardised for Europe by ITU-T are the two variants you will see in every exam.

ECE, EI

How it works

A compressor applies a logarithmic input–output characteristic before the ADC. For μ-law (μ = 255, used in North America and Japan), the compressed output is y = ln(1+μ|x|)/ln(1+μ) · sgn(x). A-law (A = 87.6, ITU-T G.711 Europe) uses a piecewise linear approximation with 13 segments for implementation ease in digital hardware. Both laws allocate more quantisation levels to small-amplitude signals, improving SNR for low-level speech. The expander at the receiver applies the exact inverse characteristic. Quantisation noise power becomes approximately proportional to signal power, making SNR nearly constant across the dynamic range.

Key points to remember

Companding improves dynamic range by approximately 40 dB compared with uniform PCM at the same number of bits. μ = 255 and A = 87.6 are the standard constants you must memorise for ITU-T G.711. A-law has better small-signal SNR, while μ-law handles overload more gracefully. Both laws approximate logarithmic compression with 8-bit, 256-level quantisation, giving 13-segment (A-law) or 15-segment (μ-law) piecewise linear digital implementations. The term "instantaneous companding" means compression is applied sample by sample, as opposed to syllabic companding used in analog voice processors.

Exam tip

The examiner always asks you to state the values of μ and A, sketch the compressor characteristic curve, and explain why SNR is more uniform — write all three in your answer even if the question only asks one.

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