# Daily Report day 2
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21/07/2021
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## 1. Aspects : Fundamental Knowledge for Wireless Communications
Wireless Technology

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### A. Communication layer
Open System Interconnection (OSI) by ISO (ISO) (International Standart Organization). To implements to wirelees system we have 7 layers. From Physical layer to Application layer. In wireless technology we have to implements the Physical layer and Data Link layer.

<center>Fig. 1.A.1. OSI Layer</center>
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### B. Smartphone Block Diagram
At user equipment, the important element to handle communication are Digital Base Band Processor and RF / IF Interface.
<center>Fig. 1.B.1 Smartphone Block Diagram</center>

Digital baseband is using to process communication.
<center>Fig. 1.B.2 Transceiver Physical Layer</center>
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### C. Wireless System Architecture BTS

#### 1. One Type of Wireless BTS Architecture
<center>Fig. 1.C.1 One Type of Wireless BTS Architecture</center>

#### 2. Base Station
<center>Fig. 1.C.2 Base Station</center>

#### 3. OFDM Point to Point
<center>Fig. 1.C.2 OFDM Point to Point</center>

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### D. Digital Communication System Model

<center>Fig. 1.D.1 Model of a Digital Communication System</center>
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### E. Shannon's Definition of Communication

"The fundamental problem of communication is that of reproducting at one point either exactly or approximately a message selected at another point."
"Frequently the messages have meaning"
"... [which is] irrelevant to the engineering problem."
Shannon wants to find a way for "reliably" transmitting data throughout the channel at 'maximum' possible rate.
So he has digital communication system model to be :

<center>Fig. 1.E Shannon Vision</center>

#### 1. Entropy Function
Using Probability Theory, Shanon showed that there is way to measure information in terms of number of bits :
called the entropy function.

#### 2. Shanon's Source Coding Theorem
"To reliably store the information generated by some random source X, you need no more/less than, on the average, H(x) bits for each outcome."

#### 3. Simple Comparison

#### 4. Huffman Code
Huffman codes are used in nearly every application that involveds the compression and transmission of digital data, which is a method to achieve the optimal compression ratio guaranteed by Shannon.
Huffman Coding have 2 steps algorith :
1. Iterate:
a. Merge the least probable symbols.
b. Sort.
2. Assign bits.

#### 5. Binary Erasure Channel
Impairment like "packet loss" can be view as Erasures.

#### 6. Shannon Channel Coding Theorem
"Give me a channel and i can compute a quantity called capacity, C for that channel. Then reliable communication is possible only if your data rate stays below C."
He calculated the channel capacity: C = 1-p
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### F. Noisy Channel
In practice channels are always noisy (sometimes this could be ignored). There are several types of noisy channels one can consider. We will restric attention to binary symmetric channels.
<center>Fig. 1.F.1 Binary symmetric channels</center>
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## 2. Summary
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### A. Wireless Communications Summary

<iframe src="https://drive.google.com/file/d/12f0nWxehFa_WIGVB69VUv7CaXqkHPf-Y/preview" width="100%" height="400"></iframe>

<center>Wireless Communications Summary</center>
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## 3. Comment
Fundamentals of Wireless Communication is a terrific introduction to principles of physical-layer design for state-of-the-art wireless systems.

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# <center>Discussion with Team</center>
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