COOPERATIVE NETWORK Wireless network

CHAPTER I: WIRELESS CHANNEL MODEL 1.1 Path Loss 1.1.1 Theory The decline in power density (attenuation) of an electromagnetic wave as it propagates over space is known as path loss or path attenuation. Path loss is an important factor to consider while analyzing and designing a telecommunication systems link budget. In wireless communications and signal propagation, this word is frequently used. Freespace loss, refraction, diffraction, reflection, aperturemedium coupling loss, and absorption are all possible causes of path loss. Terrain contours, environment (urban or rural, flora and foliage), propagation medium (dry or wet air), distance between transmitter and receiver, and antenna height and position are all factors that affect path loss. 1.1.2 Cause Path loss typically includes propagation losses due to the natural expansion of the radio wave front in free space (which usually takes the shape of an everincreasing sphere), absorption losses (also known as penetration losses) when the signal passes through media that are not transparent to electromagnetic waves, diffraction losses when part of the radiowave front is obstructed by an opaque obstacle, and losses due to other phenomena. Path loss typically includes propagation losses due to the natural expansion of the radio wave front in free space (which usually takes the shape of an everincreasing sphere), absorption losses (also known as penetration losses) when the signal passes through media that are not transparent to electromagnetic waves, diffraction losses when part of the radio wave front is obstructed by an opaque obstacle, and losses due to other phenomena. 1.2 Shadowing The route loss model discussed in the preceding section seeks to calculate the path loss in a deterministic manner for a given transmitter and receiver position. In actuality, the position of a receiver includes the topography as well as the objects that surround the transmission line. Measurements were taken under a variety of situations, with statistical variances noted. Different levels of the received signal power were measured at a certain frequency and distance. As a result, the received signal power is not predictable for a given fixed distance, frequency, and transmission power, but fluctuates according to objects in and surrounding the signal path. Shadowing is the name for these stochastic, locationdependent changes. Its worth noting that these stochastic fluctuations are constant in time as long as the receiver and his surroundings remain stationary. The term shadowing refers to the disparity between the observed received signal strength and the theoretical value estimated using route loss calculations. However, averaging numerous received signal power levels for the same distance produces the precise route loss value. The fluctuations of the recorded signal level compared to the average anticipated route loss were determined using path loss measurements for a variety of settings and distances. It has a normal distribution with a 0 mean in decibels, implying a lognormal distribution of received power around the path loss mean value. The KolmogrovSmirnov test was used to verify this hypothesis, and it was confirmed to be valid with large confidence intervals. The theoretical underpinning for the lognormal distribution is that in an environment with surrounding objects, different signals travel across the propagation medium with random re ections and diractions. The additional loss in each path, expressed in decibels, is equal to subtracting a random loss from the path loss value. The total of all the dB losses for a large number of propagation pathways converges to a normally distributed random variable (central limit theorem) since the different propagation paths are independent. This becomes a lognormal distribution in natural units. The path loss shadowing fluctuations may thus be computed from the distribution. p(a_SH )=1(σ_SH √2π) exp(a_SH2)(2σ_SH2 ) where σ_SH is the signals variability and all variables are measured in decibels. To obtain the variations, the value of the variation due to shadowing is added to the path loss value. adB= 10∙ log P0Pt= a_PL dB + A_SH dB

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REPORT cooperative network

COOPERATIVE NETWORK

CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION

COOPERATIVE NETWORK

Ho Chi Minh City, 12th, December, 2021

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Two-wave with diffused power (TWDP)

Orthogonal frequency-division multiplexing (OFDM)

single frequency networks (SFNs)

Diversity DF (DDF)

adaptive relaying protocol (ARP)

fractional incremental relaying (FIR)

negative acknowledgment (NACK)

acknowledgment (ACK)

Maximal Ratio Combining (MRC)

carrier-to-noise ratio (CNR)

Equal-gain Combining (EGC)

wireless ad hoc network (WANET)

Wireless sensor networks (WSNs)

Multi-hop Amplify-and-Forward (MAF)

Switched Combining (SWC)

Selection Combining (SC)

Very high frequency (VHF)

Ultra high frequency (UHF)

INTRODUCTION

Data communication over wireless networks is a field that is gradually advancing

in both directions magic and applicability This is the spearhead in the information

and communication industry now and in the future However, the transmission ofinformation through radio channels is not guaranteed for many reasons such asweather and terrain In practice, the signal is transmitted from the transmitter to thereceiver along many different paths, causing random fluctuations in the amplitude,phase, and angle of incidence of the received signal, a phenomenon known asmultipath fading The influence of multipath fading on signal transmission quality isvery large This problem has received a lot of research attention and various methodshave been proposed to limit the effect of this fading such as using diversitytechniques MIMO However, with each method there are disadvantages This reportwill present another method to reduce the effects of fading, which is Multi-hopCommunication, which is a relatively new technique The main idea of this technique

is to split the transmission path between the source node and the destination node byusing intermediate nodes in the middle (relay) to relay the signal Node relay inaddition to signal transmission is also responsible for amplifying and transmitting,decoding, and transmitting to expand the coverage area improve the quality of thesystem This is also an issue worthy of attention and research

CHAPTER I: WIRELESS CHANNEL MODEL

1.1 Path Loss

or rural, flora and foliage), propagation medium (dry or wet air), distance between transmitter and receiver, and antenna height and position are all factors that affect pathloss.

1.1.2 Cause

Path loss typically includes propagation losses due to the natural expansion of theradio wave front in free space (which usually takes the shape of an ever-increasing sphere), absorption losses (also known as penetration losses) when the signal passes through media that are not transparent to electromagnetic waves, diffraction losses when part of the radiowave front is obstructed by an opaque obstacle, and losses due

to other phenomena

Path loss typically includes propagation losses due to the natural expansion of theradio wave front in free space (which usually takes the shape of an ever-increasing sphere), absorption losses (also known as penetration losses) when the signal passes through media that are not transparent to electromagnetic waves, diffraction losses when part of the radio wave front is obstructed by an opaque obstacle, and losses due

to other phenomena

1.2 Shadowing

The route loss model discussed in the preceding section seeks to calculate the path loss in a deterministic manner for a given transmitter and receiver position In actuality, the position of a receiver includes the topography as well as the objects that surround the transmission line Measurements were taken under a variety of

situations, with statistical variances noted Different levels of the received signal power were measured at a certain frequency and distance As a result, the received

signal power is not predictable for a given fixed distance, frequency, and transmissionpower, but fluctuates according to objects in and surrounding the signal path

Shadowing is the name for these stochastic, location-dependent changes It's worth noting that these stochastic fluctuations are constant in time as long as the receiver and his surroundings remain stationary The term "shadowing" refers to the disparity between the observed received signal strength and the theoretical value estimated using route loss calculations However, averaging numerous received signal power levels for the same distance produces the precise route loss value

The fluctuations of the recorded signal level compared to the average anticipated route loss were determined using path loss measurements for a variety of settings and distances It has a normal distribution with a 0 mean in decibels, implying a log-normal distribution of received power around the path loss mean value

The Kolmogrov-Smirnov test was used to verify this hypothesis, and it was confirmed to be valid with large confidence intervals The theoretical underpinning for the log-normal distribution is that in an environment with surrounding objects, different signals travel across the propagation medium with random re ections and diractions The additional loss in each path, expressed in decibels, is equal to

subtracting a random loss from the path loss value The total of all the dB losses for a large number of propagation pathways converges to a normally distributed random variable (central limit theorem) since the different propagation paths are independent This becomes a log-normal distribution in natural units

The path loss shadowing fluctuations may thus be computed from the distribution

where is the signal's variability and all variables are measured in decibels To obtain the variations, the value of the variation due to shadowing is added to the path loss value

1.3 Fading

Fading is the fluctuation of a signal's attenuation with numerous factors in

wireless communications Time, geographic location, and radio frequency are among

the factors Fading is frequently shown as a chaotic process A communication

channel that fades is known as a fading channel Fading in wireless networks can be caused by multipath propagation (also known as multipath-induced fading), weather (especially rain), or shadowing from barriers impacting wave propagation (also known as shadow fading)

Fading is the fluctuation of a signal's attenuation with numerous factors in

wireless communications Time, geographic location, and radio frequency are among the factors Fading is frequently shown as a chaotic process A communication

channel that fades is known as a fading channel Fading in wireless networks can be caused by multipath propagation (also known as multipath-induced fading), weather (especially rain), or shadowing from barriers impacting wave propagation (also known as shadow fading)

Stopping at a traffic light and hearing an FM broadcast degrade into static is a classic example of deep fade, as the signal is re-acquired if the car drives only a fraction of a meter The truck came to a halt at a spot where the signal was subjected

to strong destructive interference, resulting in the loss of the transmission Similar brief fades can also be seen on cellular phones

In cellular networks and broadcast communication, fading channel models are frequently used to simulate the effects of electromagnetic transmission of information over the air Fading channel models are often used to mimic the distortion induced by the water in underwater audio communications

1.3.1 Models of fading:

1.3.1.1 Nakagami distribution:

The Nakagami distribution, also known as the Nakagami-m distribution, is a gamma-like probability distribution There are two parameters in the Nakagami distribution family: a shape parameter a second parameter that controls spread

The Nakagami distribution is a relatively recent concept, having been suggested for the first time in 1960 It has been used to analyze the influence of fading channels

on wireless communications and to model attenuation of wireless signals travelling numerous pathways

This random variable, R, will have the following probability density function:

A complex number is frequently used to indicate the gain and phase aspects of a channel's distortion The assumption that the tangible and intangible sections of the response are described by independent and identically distributed zero-mean Gaussianprocesses, with the amplitude of the response being the sum of two such processes, results in Rayleigh fading in this situation

Rayleigh fading can be a helpful model in strongly built-up city centers when there is no line of sight between the transmitter and the receiver and numerous

buildings and other things attenuate, reflect, refract, and diffract the signal due to the demand for multiple scatterers Near-Rayleigh fading has been discovered in

Manhattan as a result of experimental study [3] Many particles in the atmospheric layers operate as scatterers in tropospheric and ionospheric signals transmission, and this type of environment may also resemble Rayleigh fading If the environment is such that there is a substantially dominant signal visible at the receiver in addition to the scattering, which is commonly induced by a line of sight, the mean of the random process will no longer be zero, but will instead fluctuate about the power-level of the dominant path Rician fading is a better term for this circumstance

Rayleigh fading is a small-scale phenomenon The fading will be placed on the environment's bulk qualities, such as path loss and shadowing

The speed with which the receiver and/or transmitter move will determine how quickly the channel fades The received signal components undergo a Doppler shift as

a result of motion The figures depict a constant signal's power change over one second after travelling via a single-path Rayleigh fading channel with a maximum Doppler shift of 10 Hz and 100 Hz At 1800 MHz, one of the operational frequencies for GSM mobile phones, these Doppler shifts correspond to velocities of roughly 6 km/h (4 mph) and 60 km/h (40 mph) This is the classic Rayleigh fading form 'Deep fades,' where signal strength might drop by a factor of thousands, or 30–40 dB.

1.3.1.3 Rician fading:

Rician fading, also known as Ricean fading, is a stochastic model for radio propagation anomalies induced by partial cancellation of a radio signal by itself – the signal arrives to the receiver through many routes (thus multipath interference), at least one of which is changing (lengthening or shortening) When one of the

pathways, usually a line of sight signal or some powerful reflection signals, is

substantially stronger than the others, Rician fading develops The amplitude gain in Rician fading is defined by a Rician distribution

When there is no line of sight signal, Rayleigh fading is sometimes considered a specific example of Rician fading The Rician distribution, which characterizes the amplitude gain in Rician fading, becomes a Rayleigh distribution in this situation Two-wave with diffuse power (TWDP) fading is a specific instance of Rician fading

1.3.2 Mitigation

Fading can degrade the performance of a communication system by causing a decrease in signal power without lowering the noise power This signal loss might occur throughout a portion or the entirety of the signal bandwidth Communication systems are frequently built to adjust to such deficiencies, although fading can changequicker than improvements can be implemented In such instances, the likelihood of afade (and the associated bit errors as the signal-to-noise ratio lowers) on the channel becomes the link's performance limiting factor

Fading can be mitigated by transmitting the signal across numerous channels, each of which experiences separate fading, and then coherently merging them at the receiver The likelihood of seeing a fade in this composite channel is thus proportional

to the probability of seeing a fade in all of the component channels at the same time, which is a far more rare scenario

1.3.2.1 MIMO

Multiple-input, multiple-output, or MIMO, is a method for doubling the capacity

of a radio connection by using multipath propagation by using multiple transmitting and receiving antennas MIMO has become a key component of wireless

communication technologies such as IEEE 802.11n (Wi-Fi 4), IEEE 802.11ac (Wi-Fi 5), HSPA+ (3G), WiMAX, and LTE (LTE) As part of the ITU G.hn standard and the HomePlug AV2 specification, MIMO has recently been used to power-line

communication for three-wire setups

The term "MIMO" used to refer to the usage of multiple antennas at the

transmitter and receiver in wireless communications In current usage, "MIMO" refers

to a viable technology for sending and receiving multiple data signals over the same radio channel at the same time by taking advantage of multipath propagation

Although the "multipath" phenomena is intriguing, the increase in data capacity is due

to the use of orthogonal frequency division multiplexing to encode the channels MIMO is fundamentally distinct from smart antenna methods like beamforming and diversity, which were designed to improve the performance of a single data

transmission

Figure 1 1: MIMO system

1.3.2.2 OFDM

Orthogonal frequency-division multiplexing (OFDM) is a sort of digital

transmission and a way of encoding digital data on multiple carrier frequencies that is used in telecommunications OFDM is a widely used wideband digital

communication technique, with applications including digital television and audio

broadcasting, DSL internet access, wireless networks, power line networks, and 4G/5G telecommunications equipment.

OFDM is a frequency-division multiplexing (FDM) method developed by Bell Labs' Robert W Chang in 1966 In OFDM, data is carried in parallel by many closelyspaced orthogonal subcarrier signals with overlapping spectra Fast Fourier transform methods are used in demodulation Weinstein and Ebert enhanced OFDM in 1971 by introducing a guard interval, which increased orthogonality in multipath propagation-affected transmission channels At a low symbol rate, each subcarrier (signal) is modulated using a traditional modulation strategy (such as quadrature amplitude modulation or phase-shift keying) In the same bandwidth, this keeps overall data speeds comparable to standard single-carrier modulation techniques

The capacity of OFDM to cope with harsh channel circumstances without the use

of sophisticated equalization filters is its major benefit over single-carrier systems Because OFDM uses numerous slowly modulated narrowband signals rather than a single rapidly modulated wideband signal, channel equalization is simpler The low symbol rate allows for the use of a guard interval between symbols, allowing for the elimination of due to interference (ISI) and the use of reverberations and time-

spreading (visible as ghosting and blurring in digital audio television, respectively) to achieve diversity order, or a transmission ratio improved performance This

mechanism also makes it easier to create single frequency networks (SFNs), in which two or more adjacent transmissions send the same signal at the same frequency at the same time, because the signals from multiple faraway transmitters can be

cooperatively recombined, avoiding the interference that a traditional single-carrier system would cause