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+RFCS2/ICD MPW-4 Projects
+========================
 
+Backscattering Integration for On-Chip Wireless Power Transfer (WPT) Receivers
+------------------------------------------------------------------------------
 
-[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) [![CI](https://github.com/efabless/caravel_user_project_analog/actions/workflows/user_project_ci.yml/badge.svg)](https://github.com/efabless/caravel_user_project_analog/actions/workflows/user_project_ci.yml) [![Caravan Build](https://github.com/efabless/caravel_user_project_analog/actions/workflows/caravan_build.yml/badge.svg)](https://github.com/efabless/caravel_user_project_analog/actions/workflows/caravan_build.yml)
+### **Introduction**
 
----
+Proposed project implement WPT system having the capability of a passive
+backscattering using the single power transfer coils. The design goal of
+project will be to implement an on-chip resonant WPT system that capable
+of harvesting energy from external off chip coils, harvest the megnteic
+energy using an active recitifier and derive a load.
 
+![](media/1.png){width="3.5194444444444444in"
+height="1.5597222222222222in"}
 
-### Pakistan 1,2,3 Tapeout Projects
-### 1)	Backscattering Integration for On-Chip Wireless Power Transfer (WPT) Receivers
-### Introduction
-Proposed project  implement WPT system having the capability of a passive backscattering using the single power transfer coils. The design goal of project will be to implement an on-chip resonant WPT system that capable of harvesting energy from external off chip coils, harvest the megnteic energy using an active recitifier and derive a load.
+Wireless Power Transmission (WPT) is realized using resonant coils.
+Primary and Secondary coils are loaded with capacitors which are tuned
+at same frequency. Despite of low coupling coefficients MCR-WPT provides
+high power transfer at a single resonant frequency . Active
+rectification was used technique for improving the efficiency
+of [rectification](https://en.wikipedia.org/wiki/Rectifier) by
+replacing [diodes](https://en.wikipedia.org/wiki/Diode) with actively
+controlled switches with or power [bipolar junction
+transistors](https://en.wikipedia.org/wiki/Bipolar_junction_transistor). 
+Normal semiconductor diodes have a roughly fixed voltage drop of around
+0.5-1 volts, active rectifiers behave as resistances, and can have
+arbitrarily low voltage drop. The voltage drop across the transistor is
+then much lower, which reduces the power loss. Finally an off chip
+'backscattered signal' is used to change the impedence of coils.
 
-![results](Pictures/Top1.png)  
-Wireless Power Transmission (WPT) is realized using resonant coils. Primary and Secondary coils are loaded with capacitors which are tuned at same frequency. Despite of low coupling coefficients MCR-WPT provides high power transfer at a single resonant frequency . Active rectification was used technique for improving the efficiency of rectification by replacing diodes with actively controlled switches with or power bipolar junction transistors.  Normal semiconductor diodes have a roughly fixed voltage drop of around 0.5-1 volts, active rectifiers behave as resistances, and can have arbitrarily low voltage drop. The voltage drop across the transistor is then much lower, which reduces the power loss. Finally an off chip ‘backscattered signal’ is used to change the impedence of coils.
+### **Circuit Schematic**
 
-### Circuit Schematic
-![results](Pictures/top2.png)  
+![](media/2.png){width="5.284722222222222in"
+height="2.3333333333333335in"}
 
-### Layout
-![results](Pictures/top3.png)  
+### **Layout**
 
-### 2)	Bi-Directional Amplifier Architecture for Sub-6 GHz 5G
-### Introduction
-TDD (Time division duplexing) RF front ends operate in such a manner that during Transmission, receiver side is isolated using and switch and power amplifier is driving the transmission antenna, During Reception, transmitter chain is isolated and the received signal from the antenna is fed to a low noise amplifier.
+![](media/3.png){width="5.115277777777778in"
+height="3.291488407699038in"}
 
-![results](Pictures/top4.png)   ![results](Pictures/top5.png)  
+Bi-Directional Amplifier Architecture for Sub-6 GHz 5G
+------------------------------------------------------
 
-Figure below shows the 2-stage amplifier that is used to provide voltage gain in the circuit. In the first stage Transistors M0 and M1 provide transconductance. Transistor M1 also reduces current through M2 and increases the value of Resistor and drain of M2. Due to this cascode and current re-use technique we obtain a large voltage gain. Transistor M4 is used to provide voltage to current feedback from output to input such that the input impedance is governed transistor M4. Transistor M5 establishes bias voltage for the gate of M0. The second stage combines the differential output from stage 1 in such a way that the noise contribution of transistor M4 is cancelled
+### **Introduction**
 
-![results](Pictures/top6.png)  
-### Circuit Schematic
-![results](Pictures/top7.png)  
-### Circuit Layout
-![results](Pictures/top8.png)  
+TDD (Time division duplexing) RF front ends operate in such a manner
+that during Transmission, receiver side is isolated using and switch and
+power amplifier is driving the transmission antenna, During Reception,
+transmitter chain is isolated and the received signal from the antenna
+is fed to a low noise amplifier.
 
-### 3)	Variable Precision Fused Multiply Add Unit
+![](media/4.png){width="2.986111111111111in"
+height="1.7772911198600174in"}
+![](media/5.png){width="2.9166666666666665in"
+height="1.7161417322834647in"}
 
-### Introduction
-Higher precisions of floating point offer higher accuracy but are more expensive in terms of power and throughput. An efficient FMA may have higher throughput, but compromise much on precision of a floating-point number, while utilizing less power. Therefore, when an inputs are higher precision numbers and throughput is the main concern other than the accuracy. Arithmetic operations could be performed in lower precision datapaths, it would yield approximate results (Approximate Computing). This allows circuits to operate at higher throughput at lower power utilizing lower precision datapath. As an example, a double precision fused add unit can perform a single double precision operation, two single precision or four half precision operations in the same iteration, while performing exact calculations. While, we can perform two or four double precision approximate arithmetic operation while utilizing two single precision, or four half precision datapaths respective.
+Figure below shows the 2-stage amplifier that is used to provide voltage
+gain in the circuit. In the first stage Transistors M0 and M1 provide
+transconductance. Transistor M1 also reduces current through M2 and
+increases the value of Resistor and drain of M2. Due to this cascode and
+current re-use technique we obtain a large voltage gain. Transistor M4
+is used to provide voltage to current feedback from output to input such
+that the input impedance is governed transistor M4. Transistor M5
+establishes bias voltage for the gate of M0. The second stage combines
+the differential output from stage 1 in such a way that the noise
+contribution of transistor M4 is cancelled.
 
-![results](Pictures/top9.png)  
- ### Layout
-![results](Pictures/top10.png) 
+![](media/6.png){width="6.268055555555556in"
+height="3.0560597112860894in"}
+
+### **Circuit Schematic**
+
+![](media/7.png){width="4.673611111111111in"
+height="2.4419083552055993in"}
+
+### **Circuit Layout**
+
+![Graphical user interface, diagram Description automatically
+generated](media/8.png){width="6.268055555555556in"
+height="3.242451881014873in"}
+
+![A picture containing text, sky, screenshot, document Description
+automatically generated](media/9.png){width="6.268055555555556in"
+height="3.2555555555555555in"}
+
+![Chart, line chart Description automatically
+generated](media/10.png){width="6.268055555555556in"
+height="3.5243055555555554in"}
+
+![Graphical user interface, application, email Description automatically
+generated](media/11.png){width="6.268055555555556in"
+height="3.2194444444444446in"}
+
+![Chart, line chart Description automatically
+generated](media/12.png){width="6.268055555555556in"
+height="3.0419378827646546in"}
+
+![](media/13.png){width="6.268055555555556in"
+height="2.898507217847769in"}
+
+Operational Amplifier
+=====================
+
+Operational Amplifier is a fundamental analog circuit that is used in
+numerous applications. A conventional two stage opamp is implemented to
+be tested on chip and be further used in ADC circuits.
+
+![A picture containing graphical user interface Description
+automatically generated](media/14.png){width="6.268055555555556in"
+height="2.8722222222222222in"}
+
+![A picture containing graphical user interface Description
+automatically generated](media/15.png){width="6.268055555555556in"
+height="3.051388888888889in"}
+
+![A picture containing graphical user interface Description
+automatically generated](media/16.png){width="6.268055555555556in"
+height="3.665277777777778in"}
+
+![A picture containing graphical user interface Description
+automatically generated](media/17.png){width="6.268055555555556in"
+height="3.588888888888889in"}
+
+![Diagram, schematic Description automatically
+generated](media/18.png){width="6.268055555555556in"
+height="3.6118055555555557in"}
+
+![Chart, histogram Description automatically
+generated](media/19.png){width="6.268055555555556in"
+height="3.61875in"}
+
+  Differential Gain   60 dB
+  ------------------- ---------------
+  Common Mode Gain    5 dB
+  CMRR                55 dB
+  Voltage             $\pm \ 0.9$ V
+  GBW                 190MHz
+  Phase Margin        55 Degrees
+
+4)  Band Gap Reference
+    ------------------
+
+5)  Bandgap Reference (BGR) is general purpose IP block that generates a
+    constant dc voltage independent of all variations including supply,
+    temperature and process. **Analog circuits such as** opamps, DC-DC
+    converters, voltage control oscillators (VCO) and current mirrors
+    used **voltage references extensively.** The figure of merit for
+    these systems mainly depends on the accuracy and preciseness of
+    voltage reference.
+
+6)  ![](media/20.png){width="3.3916666666666666in"
+    height="3.4916666666666667in"}
+
+7)  Schematic:
+
+8)  ![](media/21.emf){width="3.058333333333333in"
+    height="3.441666666666667in"}
+
+9)  Explanation:
+
+10) The proposed first order BGR is auto start which eliminates the
+    start-up circuit. The cascode structure is designed to give a large
+    swing, which is not limited by the supply voltage headroom. This
+    design does not need a bias circuit. The V~DS~ voltage of MN1 and
+    MN2 is utilized to create the bias voltage for MP5 and MP4 instead
+    of employing a PMOS transistor. So, a complementary cross-coupled
+    structure is designed instead of simple cascode to create the
+    V\_Bias (at node B) voltage by itself, as illustrated in Fig. 1-1.
+    Furthermore, this architecture improves the gain of cascode stage
+    and accurately mirrors the PTAT, improving the temperature
+    coefficient and minimising the mismatches between node X and Y.
+
+11) ![Chart Description automatically generated with medium
+    confidence](media/22.png){width="6.268055555555556in"
+    height="3.401388888888889in"}
+
+12) ![Chart, line chart Description automatically
+    generated](media/23.png){width="6.266666666666667in"
+    height="3.2333333333333334in"}
+
+13) ![A picture containing chart Description automatically
+    generated](media/24.png){width="6.268055555555556in"
+    height="2.6840277777777777in"}
+
+14) 
+
+  V ref                     1.21 V
+  ------------------------- ----------------------
+  Temperature Range         -40 ^o^C to 140 ^o^C
+  Supply voltage            2.5 to 4 V
+  Temperature Coefficient   10 **ppm/°C**
+  Lin regulation            8 mV
+  Start-up time             40 µS
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