Post on 29-May-2017
transcript
Presentation on 4.5GHz Differential LNA Design and 8th order FIR Filter Design
Presented byMohammad Abu Raihan Miah
Student ID: 0413062226
What is LNA
• Low Noise Amplifier• First component of antenna receiver• Not only amplifies the signal but also decrease
the effect of noise• Noise of LNA itself must be minimized as it is
directly added to the overall Noise figure.
Consideration during Design
• Gain• Band width• Reverse Isolation parameter• s parameter• Noise Figure• Linearity (IIP3)• Power calculation
Designed Differential LNA
Input impedance
gs
sm
gssgin
sgs
inmings
ingin
sgsmings
inginin
CLg
sCLLsI
sLsC
IgIsC
IsLI
sLVgIsC
IsLIV
1)(
)1(1
)(1
Zin
gs
sm
gssgin C
LgsC
LLsZ 1)(
gssg CLL )(12
0
sgs
sm RCLg
Design Consideration
• Opertaing frequency - • Input matching (Sweeping Lg)• Output matching (Sweeping Rd, Cout)• Cascode stage – Gain rises due to sammation
of the transconductances gm of two MOSFETs.• Biasing Voltage – For power consideration
BalUn Circuit
Gain (s21db)
s11 and s22
Reverse isolation parameter (s12)
Noise Figure
Power and IIp3
Summary
Parameters Value
Gain 12.7 dB
Center Frequency 4.5 GHz
Bandwidth 1.41 GHz
Power Consumption 10.5 mW
IIP3 -35
1 dB compression point -25 dBm
Noise Figure 1.65dB
Digital Filter
• Digital filters are used to remove noise and other unwanted signal components.
• Two common architecture (i) Finite Impulse Response (FIR) (ii) Infinite impulse Response (IIR)
FIR Filter• Impulse response is of finite duration.• Output is a weighted sum of the current and a
finite number of previous values of the input.• Moving average filters as output at any time
index depends on a window containing only the most recent N samples of the input
FIRx[n] y[n]
FIR FilterOutput sequence in terms of input x(n) can be written as
x(n) = Input signaly(n) = Output signalN = Filter orderb = Filter coefficient
FIR Filter
Matlab Code• clear all;• clc;clf;• format long • • fs=48000; %Sampling Frequency• %Hamming Window Filter• b=fir1(8,0.6) %cutoff frequency=0.6*48/2= 14.4kHz• freqz(b,1,200,fs)• • range=max(b)-min(b);• interval_size=range/128;• partition=[min(b)+interval_size:interval_size:max(b)];• codebook=[0:127];• quants = quantiz(b,partition,codebook) %Quantized filter coefficients• • n=0:100;• x=sin(2*pi*n*500/fs)+sin(2*pi*n*18000/fs);• figure• subplot(2,1,1), stem(n,x);xlabel('Sampling Number(n)');ylabel('Input(x)');• y=filter(b,1,x);• subplot(2,1,2), stem(n,y);xlabel('Sampling Number(n)');ylabel('Output(y)');
Magnitude and Phase Response
Coefficients from MATLAB
Verilog Code• module FIR_Hamming_Lowpass (Data_out, Data_in, clock, reset);• • parameter order = 8;• parameter word_size_in = 8;• parameter word_size_out = 2*word_size_in+2;• parameter b0=8'd11;• parameter b1=8'd7;• parameter b2=8'd0;• parameter b3=8'd61;• parameter b4=8'd127;• parameter b5=8'd61;• parameter b6=8'd0;• parameter b7=8'd7;• parameter b8=8'd11;• output[word_size_out-1:0] Data_out;• input[word_size_in-1:0] Data_in;• input clock, reset;• reg [word_size_in-1:0] Samples[1:order];• integer k;• assign
Data_out=b0*Data_in+b1*Samples[1]+b2*Samples[2]+b3*Samples[3]+b4*Samples[4]+b5*Samples[5]+b6*Samples[6]+b7*Samples[7]+b8*Samples[8];
• always @ (posedge clock)• if (reset==1) begin for (k=1;k<=order;k=k+1) Samples [k]=0; end• else begin• Samples[1]<=Data_in;• for (k=2;k<=order;k=k+1) Samples[k]<=Samples[k-1];• end• endmodule
RTL Diagram
Input and Output
THANK YOU