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Non-uniform quantization; PCM numerical (4 kHz, ±2.4 V, 64 kHz)

Short answer

Non-uniform quantization uses small steps for low amplitudes and large steps for high amplitudes, realized by companding (compressor + uniform quantizer + expander). For 4 kHz audio at 64 kbps, fs = 8 kHz, bits per sample = 8, quantization noise power Nq = 2.93×10⁻⁵ V², SQNR = 49.93 dB. TDM of 10 signals requires minimum bandwidth 320 kHz.

Explain basic process of Non-uniform quantization including companding technique of its realization. An audio signal of frequency 4 kHz and maximum dynamic range of ±2.4 V is digitized by PCM system with its bit rate of 64 kHz. Calculate numbers of bits per sample, quantization noise power and SQNR_dB. Estimate the minimum bandwidth required for TDM of 10 such audio signals (assume no extra framing and synchronization bits).

Non-uniform quantization and companding

In non-uniform quantization the step size is small for low amplitudes and large for high amplitudes. Since speech has mostly small amplitudes and a wide dynamic range, this keeps SQNR nearly constant for loud and soft talkers.

It is realised by companding:

m(t)->[Compressor]->[Uniform Q + encoder]->channel
out <-[Expander]<---[Decoder]<-------------+
  1. Compressor applies a logarithmic gain: weak signals amplified more than strong ones. µ-law: y=sgn(x)ln⁡(1+μ∣x∣)ln⁡(1+μ)y = \text{sgn}(x)\dfrac{\ln(1 + \mu|x|)}{\ln(1 + \mu)}, μ=255\mu = 255; or A-law with A=87.6A = 87.6.
  2. Uniform quantizer then acts on the compressed signal; equal steps in yy are small steps in xx near zero.
  3. Expander at the receiver applies the inverse law, restoring the original amplitude relation. In practice the curve is a 13-segment (A-law) or 15-segment (µ-law) piecewise linear approximation.

Numerical

Given: W=4W = 4 kHz, range ±2.4\pm 2.4 V (mp=2.4m_p = 2.4 V), Rb=64R_b = 64 kbps. Assume sampling at the Nyquist rate and a full-scale sinusoidal signal.

Bits per sample

fs=2W=8 kHzn=Rbfs=64 0008000=8 bits,L=28=256\begin{aligned} f_s &= 2W = 8\ \text{kHz} \\ n &= \frac{R_b}{f_s} = \frac{64\,000}{8000} = 8\ \text{bits}, \quad L = 2^8 = 256 \end{aligned}

Quantization noise power

Δ=2mpL=4.8256=0.01875 VNq=Δ212=(0.01875)212=2.93×10−5 V2\begin{aligned} \Delta &= \frac{2m_p}{L} = \frac{4.8}{256} = 0.01875\ \text{V} \\ N_q &= \frac{\Delta^2}{12} = \frac{(0.01875)^2}{12} = 2.93 \times 10^{-5}\ \text{V}^2 \end{aligned}

SQNR

S=mp22=2.422=2.88 V2SQNR=2.882.93×10−5=98 304SQNRdB=10log⁡1098 304=49.93 dB\begin{aligned} S &= \frac{m_p^2}{2} = \frac{2.4^2}{2} = 2.88\ \text{V}^2 \\ \text{SQNR} &= \frac{2.88}{2.93 \times 10^{-5}} = 98\,304 \\ \text{SQNR}_{dB} &= 10\log_{10}98\,304 = 49.93\ \text{dB} \end{aligned}

(Check: 1.76+6.02×8=49.921.76 + 6.02 \times 8 = 49.92 dB.)

Minimum bandwidth for TDM of 10 signals

Rb,total=10×64=640 kbpsBT,min=Rb,total2=320 kHz\begin{aligned} R_{b,total} &= 10 \times 64 = 640\ \text{kbps} \\ B_{T,min} &= \frac{R_{b,total}}{2} = 320\ \text{kHz} \end{aligned}

Answer: n=8n = 8 bits; Nq=2.93×10−5N_q = 2.93 \times 10^{-5} V² (normalised to 1 Ω); SQNR = 49.93 dB; BT=320B_T = 320 kHz.

✓ Answer checked by Claude Opus 5.5 (high effort)

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