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Idiot's guide to ELEC4402 communication systems
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\end{align*}
GWGN(f)Gx(f)Gx(f)Gx(f)Gx(f)PxPxP[Acos(2πft+ϕ)]ExRx(τ)=2N0=∣H(f)∣2Gw(f) (PSD)=G(f)Gw(f) (PSD)=T→∞limT∣XT(f)∣2 (PSD)=F[Rx(τ)] (WSS)=σx2=∫RGx(f)dfFor zero mean=σx2=t→∞limT1∫−T/2T/2∣x(t)∣2dtFor zero mean=2A2Power of sinusoid =∫−∞∞∣x(t)∣2dt=∫−∞∞∣X(f)∣2dfParseval’s theorem=F(Gx(f))PSD to Autocorrelation
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Coherent detection system.
Minimum distance between any two point
Different from bit error since a symbol can contain multiple bits
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Entropy for discrete random variables
H(x)≥0H(x)=−∑xi∈AxpX(xi)log2(pX(xi))H(x,y)=−∑xi∈Ax∑yi∈AypXY(xi,yi)log2(pXY(xi,yi))Joint entropyH(x,y)=H(x)+H(y)Joint entropy if x and y independentH(x∣y=yj)=−∑xi∈AxpX(xi∣y=yj)log2(pX(xi∣y=yj))Conditional entropyH(x∣y)=−∑yj∈AypY(yj)H(x∣y=yj)Average conditional entropy, equivocationH(x∣y)=−∑xi∈Ax∑yi∈AypX(xi,yj)log2(pX(xi∣y=yj))H(x∣y)=H(x,y)−H(y)H(x,y)=H(x)+H(y∣x)=H(y)+H(x∣y)\begin{align*}
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Input has probability distribution pX(ai)=P(X=ai)p_X(a_i)=P(X=a_i)pX(ai)=P(X=ai)
Channel maps alphabet ‘{a1,…,aM}→{b1,…,bN}‘`\{a_1,\dots,a_M\} \to \{b_1,\dots,b_N\}`‘{a1,…,aM}→{b1,…,bN}‘
-Output has probabiltiy distribution pY(bj)=P(y=bj)p_Y(b_j)=P(y=b_j)pY(bj)=P(y=bj)
+Output has probability distribution pY(bj)=P(y=bj)p_Y(b_j)=P(y=b_j)pY(bj)=P(y=bj)
pY(bj)=∑i=1MP[x=ai,y=bj]1≤j≤N=∑i=1MP[X=ai]P[Y=bj∣X=ai][pY(b0)pY(b1)…pY(bj)]=[pX(a0)pX(a1)…pX(ai)]×P\begin{align*}
p_Y(b_j) &= \sum_{i=1}^{M}P[x=a_i,y=b_j]\quad 1\leq j\leq N \\
&= \sum_{i=1}^{M}P[X=a_i]P[Y=b_j|X=a_i]\\
@@ -2274,6 +2289,8 @@ M347 1759 V0 H263 V1759 v1800 v1759 h84z"/>Rb⟹RbN0Ebηηη<C<Wlog2(1+N0WPs)For bandwidth limited AWGN channel>η2η−1SNR per bit required for error-free transmission=WRbSpectral efficiency (bit/(s-Hz))≫1Bandwidth limited≪1Power limited
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Channel code
Note: Define XOR (⊕\oplus⊕) as exclusive OR, or modulo-2 addition.
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## Noise performance
Coherent detection system.
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| $I(t)$ (Odd, 1st bits) | ![QPSK bits](/images/qpsk-it.svg) |
| $Q(t)$ (Even, 2nd bits) | ![QPSK bits](/images/qpsk-qt.svg) |
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## Matched filter
### 1. Filter function
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- Minimum distance between any two point
- Different from bit error since a symbol can contain multiple bits
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## Information theory
### Entropy for discrete random variables
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## Channel code
Note: Define XOR ($\oplus$) as exclusive OR, or modulo-2 addition.
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