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Time-shifting property of DTFS

Short answer

If x[n] ↔ a_k, then x[n - n0] ↔ a_k e^{-j k (2π/N) n0}. Proof: substitute m = n - n0 in the analysis summation. Magnitudes stay same, phase changes linearly.

State and prove the time-shifting property for discrete-time Fourier series pair.

Statement

If x[n]x[n] is periodic with period NN and x[n]⟷FSakx[n] \overset{FS}{\longleftrightarrow} a_k, then

x[n−n0]⟷FSak e−jk(2π/N)n0x[n - n_0] \overset{FS}{\longleftrightarrow} a_k\, e^{-jk(2\pi/N)n_0}

A shift in time multiplies each coefficient by a linear phase term; the magnitudes ∣ak∣|a_k| do not change.

Proof

x[n−n0]x[n - n_0] is also periodic with period NN. Its coefficients are

bk=1N∑n=⟨N⟩x[n−n0] e−jk(2π/N)nb_k = \frac{1}{N}\sum_{n=\langle N\rangle}x[n - n_0]\,e^{-jk(2\pi/N)n}

Put m=n−n0m = n - n_0, so n=m+n0n = m + n_0. As nn runs over one period, mm also runs over one period:

bk=1N∑m=⟨N⟩x[m] e−jk(2π/N)(m+n0)=e−jk(2π/N)n0[1N∑m=⟨N⟩x[m]e−jk(2π/N)m]=e−jk(2π/N)n0 ak\begin{aligned} b_k &= \frac{1}{N}\sum_{m=\langle N\rangle}x[m]\,e^{-jk(2\pi/N)(m + n_0)} \\ &= e^{-jk(2\pi/N)n_0}\left[\frac{1}{N}\sum_{m=\langle N\rangle}x[m]e^{-jk(2\pi/N)m}\right] \\ &= e^{-jk(2\pi/N)n_0}\,a_k \end{aligned}

Interpretation

  • ∣bk∣=∣ak∣|b_k| = |a_k|: the magnitude spectrum is unchanged by a shift.
  • ∠bk=∠ak−k2πNn0\angle b_k = \angle a_k - k\frac{2\pi}{N}n_0: the phase changes linearly with kk.

Example: x[n]=cos⁡(2πn/N)x[n] = \cos(2\pi n/N) has a±1=1/2a_{\pm1} = 1/2. Then x[n−1]x[n-1] has b1=12e−j2π/Nb_{1} = \frac{1}{2}e^{-j2\pi/N} and b−1=12ej2π/Nb_{-1} = \frac{1}{2}e^{j2\pi/N}, still of magnitude 1/21/2.

✓ Answer checked by Claude Opus 5.5 (high effort)

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