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