Basic concepts and security at the physical layer

Question 1

What is a signal?

Answer 1

A signal is a function that conveys information about the behavior or attributes of some phenomenon. It can vary over time, space, or another independent variable.

It can be:
* Analog signal – continuous in time and amplitude (e.g., audio waveform).
* Digital signal – discrete in time and amplitude (e.g., binary code: 0s and 1s).

Question 2

How can a signal be represented?

Answer 2

There are different ways to represent a signal since the time representation is always effective for many applications.

A signal, for example, can be represented as a lineare combination of basis functions (sum of elementary signals). It means that:
* the signal will be represented as the sum of M components
* each component is the product between the i-th component w_i of a complete orthonormal basis for x(t) and a parameter alpha_i
* alpha_i is the result of the scalar product between x(t) and w_i. The meaning of this coefficient is “how much of the i-th signal is needed to make x(t)”

Notes:
* w(t) is composed by “elementary” signals
* the scalar product associates a (complex) scalar number to a pair of vectors or signals that measures theur “similarity”. If the scalar product is zero the signals are said to be orthogonal
* The scalar product is useful to associate signals with vector coefficients (modulations) or with frequency components (spectral analysis).
* If the signal x(t) is represented with vector coefficients such as x = (a_1, a_2, …, a_M) then x is a base that can result in different signals by asociating the base with different coefficients.

Question 2

What is the general model of a Digital Communication System like?

Answer 2

TX -> encoder -> modulator -> channel -> demodulator -> decoder -> RX

It can be divided in three sections:
- user: digital signals
- interface: to transform bits into signals having the wanted characteristics -> to have them we use compression, encoding, association and other methodologies
- channel: to propagate analog waveforms that convey info

Components:
* encoder: it implements source and channel encoding to limit respectively the amount of data transmitted and the effects of channel disturbances
* modulator: converts the digital signal to an analog one
* channel: transmits the analog signals
* demodulator: converts the analog signals into a SEQUENCE OF SAMPLES. to be processed by the decoder
* decoder: it implements source and channel decoding to resectively expand the compressed data and limit the effects of channel errors

Question 3

Fourier Analysis

Answer 3

The core idea is that any complex, periodic or non-periodic signal can be decomposed into a series of simpler sine and cosine waves. These simpler waves make up the frequency components of the original signal.
In essence, Fourier analysis transforms a signal from the time domain to the frequency domain.
So:
* for each signal there is a spectral representation
* for each operation over a signal there are equivalent effects in the frequency domain
* finite duration signals have infinite support in the frequency domain

TODO: come si arriva alla trasformata

Question 4

Bandwidth

Answer 4

The bandwidth is the interval of frequencies occupied by a signal. Signals have always infinite support in frequency domain but many signals are characterized by quasi-null frequencies out of the main lobes.

One of the most popular definitions of bandwidth is related to the square of the modulus |X(f)|^2 ->
3dB bandwidth: it is the frequency range between the two points on the frequency response curve where the output power falls to half (i.e., -3 dB) of its maximum value.

Question 5

Linear systems and filters

Answer 5

A set of operations applied to ignals can be modeled as a system.
Systems can be Lineare-time-invariant (LTI): these systems are modeled by a frequency response commonly noted as H(f) -> Y(f) = H(f)X(f)

When a system is used to pass or to remove particular frequencies of the singal it is regarded as a filter. They are useful to model desired and undesired effects.

Question 6

Signal modulation and demodulation (theoretical)

Answer 6

Modulation is an operation that allows to move a signal spectral content to a different center frequency. This is done by multiplying the signal BY a sinusoidal function, which results in a frequency shift.

y(t) = x(t)cos(2 pi f_0 t)
F(x(t)cos(2 pi f_0 t)) = 1/2 [X(f-f0) + X(f+f0)]
(look at drawings)

This result is fundamental for most wireless modulations to move the spectral content of the original signal to the most appropriate frequency band: thy way multiple signals can be received on the same shared medium and the be separated. -> FDM

The original signal, when received, can be recovered by first multiplying it for a sinusoid at the same frequency and then using a low pass filtering H(f) which selects just the component centered at the frequency f

Question 7

Frequency multiplexing (FDM)

Answer 7

Thanks to modulation, different signals with overlapping bandwidths can be frequency-modulated in different portions of the spectrum. Once they are received they can be de-multiplexed without distortions.

Question 8

Analog-to-digital conversion and Sampling Theorem

Answer 8

1. analog signal
2. sampling
3. quantization
4. digital signal

Nyquist theorem: a continuous time signal can be sampled and perfectly reconstructed from its samples if the sampling frequency is greater than twice the band of the signal.

“perfectly reconstructed”… actually not because the signal bandwidth is infinite, but in general is quasi-null outside the main lobes.

So:
- if the sampling frequency is f_c = 1/T_c
- and f_c has to be > 2B
- this means that T_c < 1/2B

B is the one-side bandwidth of the analog signal.

Question 9

Modulation process: definition and types of modulation

Answer 9

Modulation is the process of varying one or more properties of a periodic waveform, called the carrier signal, with a separate signal called the modulation signal, that typically contains information to be transmitted.

Modulation can be done both on digital and analog signals. In general, all the techniques are based on basic modulation types:
- Amplitude modulation: the amplitude of the carrier signal is varied according to the istantaneous amplitude of the modulation signal
- Frequency modulation: the carrier amplitude remain constant BUT the carrier frequency shifts proportionately to the AMPLITUDE of the information signal (as the modulating signal amplitude increases, the carrier frequency increases)
- Phase modulation: the phase of the carrier is modulated to follow the changing signal amplitude of the message signal. The peak and the frequency of the carrier are maintained constant, but as the amplitude of the message signal changes, the phase of the carrier changes accordingly

Similar ideas have been applied to digital signals:
- Amplitude shift keying (ASK)
- Frequency shift keying (FSK)
- Phase shift keying (PSK)

Question 10

Baseband and bandpass signals

Answer 10

Baseband: signals whose frequency spectrum is concentrated around zero

Bandpass: // around some f_c away from zero

Baseband signals can be converted to bandpass signals through modulation (mult. by some sinusoid with f_c)

Question 11

Pulse Amplitude Modulation (PAM) (2-PAM and M-ary PAM) and Solution for errors

Answer 11

In digital communication, baseband PAM refers to modulating a digital signal (like a sequence of 1s and 0s) without converting it to a high-frequency carrier. Instead, we shape the signal into pulses and transmit them directly over the channel.

𝑔(t) is the basic pulse shape—the building block. The most basic choice is a rectangular pulse: it consists of a constant value over a short time. In practice, more advanced pulse shapes (like sinc or raised cosine) are used to reduce bandwidth and minimize interference between symbols (ISI – Inter Symbol Interference).

2-PAM uses two amplitude levels to represent binary values:
- A pulse of amplitude +A represents a binary “1”
- A pulse of amplitude –A represents a binary “0”
So:
- If the bit is 1 → transmit 𝑠(t) = 𝑔(t)
- If the bit is 0 → transmit 𝑠(t) = −𝑔(t)

In M-ary PAM, instead of just two amplitude levels (like in 2-PAM), we use M different amplitudes. This allows us to send more than one bit per symbol.

Each signal is a scaled version of the basic pulse
s_i(t) = A_i * g(t)

Each amplitude (signal level) represents a unique bit pattern.

Number of bits per symbol: log_2(M)

Why Use M-PAM?
- Higher data rate: More bits per symbol.
- More efficient bandwidth usage.

Trade-Off: Higher M ⇒ Less noise tolerance
As the amplitude levels get closer together, it’s easier for noise to cause symbol errors.

Gray coding
It is a strategy for mapping bits to symbols so that the number of bit errors is minimized.
Considering that it is most likely to have symbol errors between adjacent levels, the goals is to minimize the number of bits that differ from one level ot the adjacent one.
This technique achieves 1 bit difference between adjacent levels.

• No gray coding: 01 10 -> two errors
• Gray coding: 01 11 -> one error

Question 12

Energy per bit

Answer 12

A measure of the energy efficiency of the modulation can be obtained from the average energy per bit
𝐸_𝑏 = 𝐸_𝑠/ log2 𝑀
- is the average energy per symbol divided by the number of bits carried by each symbol
- the energy needed to transmit information reliably depends also on the amount of noise in the system

E_s is the avarage energy per symbol: 𝐸_𝑠 = 𝐸_𝑚/𝑀
and E_m is the actual energy per symbol which is computed with the integral of S(m)^2 over [0, T].

For example, if
𝑀 = 4
and 𝐴1 = −3, 𝐴2 = −1, 𝐴3 = 1, 𝐴4 = 3
then 𝑠_𝑖 (𝑡) = 𝐴_𝑖 𝑔(𝑡)
and E_s = (9T + T + T + 9T) / 4 = 5T

The distance from the origin is proportional to the energy of the symbol.
For example 𝐴4 = 3 is more distant from 0 than 𝐴3 = 1

Question 13

Why there is the need to have a trade off between bandwidth efficiency and energy efficiency?

Answer 13

Generally, we want to choose the pulse shape 𝑔(𝑡) in order to put more energy in a small bandwidth.

For a pulse of duration 𝑇,
- the symbol rate is 𝑅_𝑠 = 1/𝑇
- There are log2(𝑀) bits per symbol, therefore the bitrate 𝑅𝑏 = log2(𝑀) 𝑅𝑠
- Roughly, the two-sided bandwidth is 𝐵𝑊 = 2R_s = 2/T
- the bandiwdth efficiency eta = R_b / BW = (log_2(M)/T) * (T/2) = log_2(M) / 2 𝑏𝑝𝑠/𝐻𝑧
- Increased BW efficiency with increasing M

Example:
M = 4 ⇒ BW efficiency = 1
M = 8 ⇒ BW efficiency = 3/2

However, as M increases we are more prone to errors as symbols are closer together (for a
given energy level)
=> Need to increase symbol energy level to
overcome errors
=> Tradeoff between BW efficiency and
energy efficiency

Question 14

Two dimensional modulations

Answer 14

Instead of using just one pulse shape (as in PAM), two-dimensional modulation uses two orthonormal basis functions (think of them like X and Y axes in a 2D space). Every symbol is a point (vector) in this 2D space.

• The set of all possible transmitted signals (or symbols) forms a constellation.
• Each symbol corresponds to a unique bit pattern.
• The position of each point in the 2D plane (based on amplitude and phase) determines the symbol being sent.
• More bits per symbol → higher data rate
• Efficient use of bandwidth
• Example: A 16-point constellation can represent 4 bits per symbol.
  But:
• Symbols are closer together → more sensitive to noise.
• Error probability increases as constellation gets denser.

Common constellations:
- QAM: Quadrature Amplitude Modulation such as a PAM in two dimensions
- PSK: Phase Shift Keying: special constellation where all symbols have equal power

Question 15

Symmetric M-QAM

Answer 15

Here M is the totl number of signal points / symbols. Radice of M is the number of signal levels on each axis.

M = K^2 for some K then the costellation is symmetric.

Signal levels on each axis are the same as for PAM
E.g. 4-QAM -> +/-1
16-QAM -> +/-1, +/-3

Using the same pulse g(t), the bandwidth efficiency is the same as M_PAM BUT QAM has larger energy efficiency than PAM.

Question 16

M-QAM Modulator and Demodulator

Answer 16

• Your symbol is a point 𝑠_𝑚=(𝐴𝑥, 𝐴𝑦) in the I-Q constellation plane.
• You convert that 2D value into a bandpass waveform by multiplying:
  Icomponent(𝐴𝑥)×cos(2𝜋𝑓𝑐𝑡)
  Qcomponent(𝐴𝑦)×sin⁡(2𝜋𝑓𝑐𝑡)
• Cosine and sine are orthogonal (independent) sinusoids at carrier frequency 𝑓𝑐
• They form a basis for the bandpass signal, just like
  𝑥 and 𝑦 axes form the basis for 2D geometry.

If your symbol is the 𝑚-th one from the constellation, with components 𝐴𝑥,𝑚 and 𝐴𝑦,𝑚, and your pulse shape is 𝑔(𝑡), then:
𝑠𝑚(𝑡) = 𝐴𝑥,𝑚⋅𝑔(𝑡)⋅cos⁡(2𝜋𝑓𝑐𝑡)−𝐴𝑦,𝑚⋅𝑔(𝑡)⋅sin⁡(2𝜋𝑓𝑐𝑡)
This is the bandpass QAM signal for the m-th symbol.
- The minus sign ensures the Q component is in quadrature (90° out of phase) with the I component.
- It also aligns with standard signal processing conventions and makes demodulation simpler at the receiver.

Over one full symbol duration 𝑇, sine and cosine at frequency 𝑓𝑐 are orthogonal: this means they don’t interfere with each other when used as basis functions. The symbol duration 𝑇 must match an integer number of carrier cycles: f c = n/T, forsomeintegern. This ensures clean separation of I and Q during demodulation.

At the receiver, to recover 𝐴𝑥 and 𝐴𝑦, we do:
1. Recover I (Aₓ):
Multiply 𝑈(𝑡) by cos(2𝜋𝑓𝑐𝑡)
Low-pass filter (to remove high-frequency terms)
Why it works: cos⋅cos term survives while sin⋅cos term averages to zero (because of orthogonality)

2. Recover Q (Aᵧ):
   Multiply 𝑈(𝑡) by sin(2𝜋𝑓𝑐𝑡)
   Low-pass filter again
   Why it works: sin⋅sin term survives while cos⋅sin term cancels out

Question 17

PSK

Answer 17

PSK is a form of digital modulation where the phase of a carrier wave is changed to represent digital data.
- The amplitude remains constant
- Only the phase of the carrier changes
This means:
- All symbols have the same energy.
- The signal points lie on the circumference of a circle in the I-Q (In-phase and Quadrature) plane.

PSK symbols are placed evenly around a circle with radius radice(E_s) (symbol energy).
This helps keep symbol spacing equal and minimizes bit errors.

Example: M-PSK (e.g., 8-PSK, 16-PSK)
𝑀 symbols are spaced evenly around a circle
Each symbol represents: log2(𝑀)bits
Example:
8-PSK: 3 bits/symbol
16-PSK: 4 bits/symbol
Essentially, it is the same modulator and demodulator of M-QAM (schema).

Question 18

challenges of the wireless medium

Answer 18

the communication channel is the major source of error. Errors come for example from
- Thermal Noise
- Inter Symbol Interference (ISI).

Simplifying our model, the received signal experience additive noise
r(t) = s_i(t)*h_c(t)+ n(t) where n(t) = AWGN

That’s why we need to build a receiver which tries to:
- miximize the Signal to noise ration (SNR)
- minimize the ISI

Steps in design:
- Model the received signal
- Find separate solutions for each of the goals

How to Maximize SNR?
- Considering a simplified noise model, n(t) is a random process (each “sample” of 𝑛(𝑡) is a random variable) => Its variance is proportional to the noise density 𝑁0
- What is the filter ℎ(𝑡) that yields the maximum SNR at sampling? => SNR is maximized by the matched filter ℎ 𝑡 = 𝑔(𝑇 − 𝑡)

How to minimize ISI?
- Channel impulse response must be reverted
- ISI due to filtering effect of the communications channel (e.g. wireless channels)
- Channels behave like band-limited filters
- A linear distortion can be compensated by an equalizer => ideally, H_e(f) = 1/H_c(f) => An approximation 𝑠𝑖appr(𝑡) of the transmitted symbol is obtained

How to know 𝐻𝑐(𝑓)?
- Channel Estimation is the process that takes place before equalization in the communication system
- The channel transfer function is estimated thanks to known signal characteristics
- Types based on the density of training symbols:
Blind Channel Estimation
Semi-Blind Channel Estimation
Pilot Assisted Channel Estimation

Question 19

Channel’s fading

Answer 19

• slow fading: channel impulse response variations are slow => symbols transmitted less frequently
• fast fading: channel impulse response variations are fast => symbols transmitted more frequently

Question 20

multiplexing and multiple access, types

Answer 20

multiplexing: method by which multiple analog or digital signal are combined into one signal over a shared medium => the capacity of the communication channel is divided into LOGICAL channels
-> deals with combining signals

multiple access: enables multiple users or devices to share a communication channel simultaneously
-> deals with allowing multiple users to access and share a signle medium

Types of M/MA:
- Frequency division
- Code division
- Time division
- time & frequency division

Question 21

FDM/FDMA

Answer 21

• Each signal, which has its specific central frequency, is modulated to a different carrier frequency.
• Useful bandwidth of medium exceeds required bandwidth of channel
• Carrier frequencies separated so signals do not
  overlap (guard bands)
• Channel gets band of the spectrum for the whole
  time
• Channel allocated even if no data

Advantages:
- no dynamic coordination needed
- works also for analog signals
Disadvantages:
- waste of bandwidth (fixed allocation) if traffic
distributed unevenly
- guard spaces

Applications:
- All wireless systems basically!
- Radio and tv broadcasting, telephone,
communication satellites (uplink and
downlink), DSL,…

FDM Scheme
- Different signals can be frequency-modulated in different portions of the spectrum.
- Once they are received they can be de-multiplexed withouth distortions.

Question 22

Thermal Noise characteristics

Answer 22

Thermal Noise (AWGN)
- disturbs the signal in an additive fashion (Additive)
- has flat spectral density for all frequencies of interest (White)
- is modeled by Gaussian random process (Gaussian Noise)

Question 23

What are the receiver tasks?

Answer 23

Receiver Tasks
1. Demodulation and sampling
2. Waveform recovery and preparing the received signal for detection
- Improving the signal-to-noise ratio (SNR)
- Reducing ISI
- Sampling the recovered waveform
3. Detection: Estimate the transmitted symbol based on the received sample

Question 24

Symbols Detection

Answer 24

After matched filtering we get 𝑟 = 𝑆𝑚 + 𝑛 with 𝑆𝑚 ∈ {𝑆1, … , SM} - How do we determine from 𝑟 which of the 𝑀 possible symbols was sent? - Without the noise we would receive what sent, but the noise can transform one symbol into another **Hypothesis testing** - Objective: minimize the probability of a decision error - Decision rule: Choose 𝑆𝑚 such that 𝑃(𝑆𝑚 sent | 𝑟 received) is maximized This is known as **Maximum a posteriori probability (MAP) rule** - MAP Rule: Maximize the conditional probability that 𝑆𝑚 was sent given that 𝑟 was received - Turns out to be equivalent (under certain conditions) to minimum distance decoding E.g. 2-PAM - If 𝑆1 was sent then the received signal is 𝑟 = 𝑆1 + 𝑛 - If 𝑆2 was sent then the received signal is 𝑟 = 𝑆2 + 𝑛 - Then if 𝑟 > 0 decide 𝑆1, if 𝑟 < 0 decide 𝑆2

Question 25

Probability of Error between two symbols

Answer 25

In general, the probability of error 𝑃 𝑒 between two symbols separated by a distance d is given by: P_e(d) = Q(square_root(d^2 / (2N_0))) where 𝑁0 is the noise density. Based on that, it is possible to compute a bit error rate (BER) for each modulation - Under certain conditions (e.g. gray coding) 𝐵𝐸𝑅 = 𝑃 𝑒 / log2 𝑀 Note: - the performance decreases for increasing m - SNR is proportional to the received power

Question 26

Signal attenuation in the channel and Antenna beamwidth

Answer 26

The signal suffers an attenuation loss L - Received power: 𝑃_𝑅 = 𝑃_𝑇/𝐿 - Received SNR: 𝑆𝑁𝑅 = 𝐸𝑏 /𝑁0 , 𝐸𝑏 = 𝑃_𝑅/𝑅_𝑏 - Antennas are used to compensate for attenuation loss => Capture as much of the signal as possible Antenna Beamwidth - The beamwidth 𝜃𝐵 is a measure of the directivity of the antenna - A smaller beamwidth concentrates power along a smaller area - Free space loss assumes that power is radiated in all directions - An antenna with a smaller beamwidth concentrates the power, hence yields a gain - For parabolic antenna, 𝜃𝐵 ~ 70𝜆/𝐷 - Gain (𝐺𝑇 ) is proportional to 1/(𝜃𝐵)^2 - Hence a doubling of the diameter 𝐷 increases gain by a factor of 4

Question 27

TDM/TDMA

Answer 27

**Synchronous TDM/TDMA** - Multiple digital signals interleaved in time - Time slots preassigned to sources and fixed - Time slots allocated even if no data - Data rate of medium exceeds data rate of digital signal to be transmitted - Channel gets the whole spectrum for a certain amount of time Advantages: - only one carrier in the medium at any time - throughput high even for many users Disadvantages: - precise synchronization necessary Applications: - Optical networks (SONET), GSM, ISDN,…. PRO: **Statistical Time Division Multiplexing** - In Synchronous TDM many slots are wasted - Statistical TDM allocates time slots dynamically based on demand - Multiplexer scans input lines and collects data until frame full - Data rate on line lower than aggregate rates of input lines - More advanced technique - It requires scheduling algorithms

Question 28

CDM/CDMA

Answer 28

- Each channel has unique code - All channels use **same spectrum at same time** - Implemented using spread spectrum technology - Each sender is assigned a unique binary code 𝑐𝑖(𝑡) - Binary codes are orthogonal vectors => This means that they can be summed together and separated without interference - **MUX**: sum signals after code modulation -> s_mux(t) = s_1(t)*c_1(t) + s_2(t)*c_2(t) - **DEMUX**: perform the scalar product **over a code period** to get the desired signal: < s_mux, c_1(t) > = s_1(t) Advantages - Bandwidth efficient - No coordination and synchronization - Good protection against interference Disadvantages - lower user data rates - more complex signal regeneration Applications: - UMTS (3G), Global Navigation Satellite Systems (**GPS**),…

Question 29

TDM/A + FDM/A

Answer 29

- A channel gets a certain frequency band for a certain amount of time (e.g. GSM) Advantages: - better protection against tapping - protection against frequency selective interference - higher data rates compared to code multiplex - Precise coordination required

Question 30

Encoder/Decoder

Answer 30

**Encoder** - Implements source encoding to limit the amount of transmitted data - Implements channel encoding to limit the effects of channel disturbances => It aims to generate a compressed representation 𝑌, starting from the input data 𝑋. **Decoder** - Implements channel decoding to limit the effect of channel errors and extract the information data - Implements source decoding to expand the compressed data back to their original form => It aims to reconstruct the input data, generating a version 𝑋_tilde starting from the compressed sequence 𝑌

Question 31

Source coding

Answer 31

**Source coding**, a.k.a. **data compression**, aims to represent information or data in a more compact form to reduce redundancy and save storage space or transmission bandwidth - The primary goal is to eliminate or minimize redundancy in the data - This can be done since many real-world datasets exhibit patterns or repetitions that can be efficiently encoded - E.g. **Variable-length coding** assigns shorter codes to more frequent symbols and longer codes to less frequent symbols => This reduces the average number of bits needed to represent the data.

Question 32

Compression Types for source encoding

Answer 32

Compression **classes** for source encoding - **Loseless class**: Ensures that the original data can be perfectly reconstructed from the compressed version. Examples include ZIP and PNG. - **Lossy class**: Sacrifices some data accuracy for higher compression ratios. Commonly used in multimedia compression, as in JPEG and MP3 Notes: - There are no universal compression formats. - The fidelity requirements (𝑋tilde ≈ 𝑋) of the application and the nature of the data define the specifications - Trade-off: compression efficiency vs. computational complexity => Advanced algorithms may provide higher compression but require more processing power

Question 33

Error Detection and Correction

Answer 33

After source coding, bits should be received unaltered => **Goal: reliable delivery of digital data over unreliable communication channels** **Error detection** techniques allow detecting such errors, while **error correction** enables reconstruction of the original data. All error-detection and correction schemes add some redundancy (i.e., some extra data) to a message, which receivers can use to check consistency of the delivered message and to recover corrupted data. There are two main approaches: **ARQ** and **FEC** **Automatic repeat request (ARQ)** - It uses acknowledgements (messages sent by the receiver indicating that it has correctly received a message) and timeouts (specified periods of time allowed to elapse before an acknowledgment is to be received) to achieve reliable data transmission - Protocol perspective, needs a backward channel - Examples: Stop-and-wait ARQ, Go-Back-N ARQ, and Selective Repeat ARQ **Forward error correction (FEC) / Channel coding** - It is a process of adding redundant data to a message so that it can be recovered by a receiver even when some errors (up to the capability of the code being used) are introduced - No need for a backward channel, unidirectional communication - Examples: Block codes, convolutional codes **Channel Coding** - aims to detect and correct errors that may occur during transmission - It adds redundant bits to the original message, creating a coded message that contains extra information for error detection and correction - Used in various communication systems, including wireless communication, satellite communication, digital television, and data storage - The effectiveness of a channel code is often measured by its error correction capability, indicating the maximum number of errors that can be corrected within a codeword. - There is a trade-off between the amount of redundancy added (which affects bandwidth efficiency) and the level of error correction provided. - **Block Codes**: Divide the data into fixed-size blocks, and error correction is performed independently on each block. A block code acts on block of 𝑘 bits of input data to produce 𝑛 bits of output data (𝑛,𝑘) - **Convolutional Codes**: Process the data as a continuous stream, on a bit-by-bit basis, and error correction is based on the convolution of the input data with a code. Optimally decoded through Viterbi Algorithm.

Question 34

Security Threat related to the wireless channel

Answer 34

When signals are transmitted over the wireless channel, security is more of a concern, because: - there is no inherent physical protection => physical connections between devices are replaced by logical associations - sending and receiving messages do not need physical access to the network infrastructure (cables, hubs, routers, etc.) - the communication is broadcast: - wireless usually means radio, which has a broadcast nature - transmissions can be overheard by anyone in range - anyone can generate transmissions that will be received by other devices in range and that can interfere with other nearby transmissions and may prevent their correct reception (jamming) As a result: - eavesdropping is easy - injecting bogus messages into the network is easy - replaying previously recorded messages is easy (e.g. meaconing) - illegitimate access to the network and its services is easy - denial of service is easily achieved by jamming

Question 35

Passive and Active Attacks in Wireless Networks

Answer 35

**Passive attacks**: - do not disrupt network operation, and the adversary’s objective is to steal transmitted information - example: traffic analysis, eavesdropping **Active attacks** - active attacks can significantly interfere with normal network operations because an adversary often tries to alter the network data - Radio Frequency Jamming is also widely used to launch DoS attacks at the physical layer. It can be employed to invade the transmitted signal band. - An adversary can utilize jamming signals (thereby disrupting the communications) to make the attacked nodes suffer from DoS in a specific region - example: DoS, resource consumption, masqerade attack, replay attack, information disclosure, message modification

Question 36

Jamming (DoS)

Answer 36

- it is a simple strategy to disrupt wireless communications is to interfere with communications directly by jamming the communication channel - A jammer may broadcast an interference signal on a broad spectral band to disrupt legitimate signal reception They can be classified into two types: - **Active** (constant) jammers send out a radio signal continuously into the channel and therefore block the communications of users, making the prevention of such interference a big challenge. - A **reactive** jammer is idle until it senses transmission activities occurring in the channel; then it transmits jamming signals to interrupt the ongoing transmission. Since the jammer must detect transmission activities before issuing its jamming signal, the transceiver may improve its own low probability of detection to avoid jamming attacks A persistent and powerful adversary can always jam all data transmissions by transmitting high-power white noise over the entire frequency spectrum. Although such availability threats are powerful, they can be addressed through many physical layer security schemes.

Question 37

Eavesdropping

Answer 37

- The broadcast nature of the wireless medium makes it hard to eliminate unauthorized access to wireless networks - The most common way to maintain confidentiality is to use **encryption** - Another widely used approach is to force the transmitter and receiver to adopt some **information hiding measures**. Information hiding is a method to embed private messages into a background signal or noise process Also eavesdropping can be addressed through Physical Layer Security approaches

Question 38

Physical Layer Security

Answer 38

In traditional systems, reliability is guaranteed by channel coding at the physical layer, while security is ensured by encryption protocols at the upper layers. Physical layer security aims at exploiting the randomness inherent in noisy channels to provide an additional level of protection at the physical layer. **Perfect secrecy** is achievable if the channel is unknown to unauthorized users, or the channel of the unauthorized users is more noisy than that of the authorized users [2] Security at physical layer is not intended to replace cryptographic security, but rather, it affords an additional protection layer - Nowadays, many results from information theory, signal processing, and cryptography suggest that there is much security to be gained by accounting for the imperfections of the physical layer when designing secure systems - PLS is an evolving field of research that continuously explores new techniques and methodologies against emerging threats and vulnerabilities **Cryptography VS Physical Layer Security** - Cryptography permits demodulation, but the message cannot be understood - Physical Layer Security does not even allow demodulation - Physical Layer Security does not rely on the assumption of limited computational power of the attacker - Physical Layer Security can be measured

Question 39

Physical Layer Security Methods

Answer 39

Major categories of physical layer security methods: Channel Approaches, Coding Approaches, Power Approaches, and Signal Design Approaches. **Channel Approaches**: - RF Fingerprinting: Dynamic fingerprinting for intrusion detection - ACDM Precoding: Use of singular value decomposition for generating transmitted code vectors - Randomization of MIMO Transmission Coefficients: Achieving perfect secrecy by randomizing MIMO coefficients **Code Approaches**: - Error Correction Coding: Advanced channel coding and AES cryptosystem for secure communication - Spread Spectrum Coding: Direct-sequence CDMA and Frequency Hopping Spread Spectrum (FHSS) **Power Approaches**: - Directional Antennas: Improved spatial reuse and data availability using beamforming - Artificial Noise Scheme: Generation of artificial noise to impair intruder's channel while maintaining secrecy for the legitimate receiver **Signal Design Approaches**: - Discriminatory Channel Estimation: Use of artificial noise to degrade eavesdropper's channel estimation - Multistage Training-Based Channel Estimation: Minimization of mean squared error subject to constraints using channel feedback Each method addresses specific aspects of physical layer security, ranging from utilizing channel characteristics to employing artificial noise and directional antennas Each method is effective against various attacks. They are using a combination of information theory, coding techniques, and signal processing approaches. Vedere tabella blocco 3 ultima slide