Wireless and Mobile Communications

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Link Budget It is the accounting of all of the gains and losses from the Transmitter, through the medium (free space, cable, waveguide, fiber, etc.) to the Receiver in a telecommunication system. Simple link budget equation Received Power = Transmitted Power + Gains Losses

Accounts for the attenuation of the transmitted signal due to Propagation Antenna gains Feedline and miscellaneous losses.

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Link Budget Randomly varying channel gains such as fading are taken into account by adding some margin (depending on the anticipated severity of its effects ). The amount of margin required can be reduced by the use of mitigating techniques such as antenna diversity or frequency hopping. Link budgets are required for different terrains

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Link Budgets

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Link Budgets

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Maximum Allowable Path Loss

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Maximum Allowable Path Loss

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Link Budgets Forward and Reverse

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Link Budgets Forward and Reverse

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Link Budgets Forward and Reverse

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Reverse Link Budget Example

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Reverse Link Budgets Example

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Link Budget

RF Link Budget CalculatorFree Space Loss Path Frequency ERP ERP in dBm Transmission Line Loss Tx Antenna Gain Path Length Free Space Path Loss Rx Antenna Gain Rx Transmission Line Loss Rx Signal Strength Rx Threshhold Fade Margin 0.9000 50.0000 46.9897 0.0000 0.0000 0.1500 75.0484 0.0000 0.0000 -28.0587 -85.0000 56.9413 GHz Watts dBm dB dBi Km dB dBi dB dBm dBm dB

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Propagation Models

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Types Of Propagation Models And Their Uses

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Propagation Models

Practical Link Budget Design using Path Loss Models Log-distance Path Loss Model Log-normal Shadowing

Outdoor Propagation Models Longley-RIce Model Okumura Model Hata Model

Indoor Propagation Models17

Path Loss Models Models to estimate the received signal level as a function of distance Prediction of the Signal to Noise Ratio

Path Loss Models Log-distance Path loss model Log-normal shadowing

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Log-distance Path loss model

Uses the idea that both theoretical and empirical evidence suggests that average received signal strength decreases logarithmically with distance , whether in outdoor or indoor radio channels

To measure received signal strength near to transmitter and approximate to different distances based on above reference observation

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Log-distance Path Loss Model

A radio propagation model that predicts the path loss that a signal encounters inside a building or densely populated areas over distance.

The average large-scale path loss for an arbitrary T-R separation is expressed as a function of distance by using a path loss exponent n.

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Log-distance Path Loss ModelThe Mean loss in dB follows the power law .Average power (in dB) decreases proportional to log of distance

n = Path Loss Exponent Indicates the rate at which the path loss increases with distance The value of n depends on the specific propagation environment. In free space, n = 2 When obstructions are present, n > 221

Log-distance Path Loss Model

d0 = the close-in reference distance In large coverage cellular systems 1 km reference distances are commonly used The reference path loss is calculated using the Free space path loss formula" or through field measurements at distance d0.

d = T-R separation distance bar means the average of many PL values at a given value of d (T-R separation.)22

Log-distance Path Loss Model

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Log-Normal Shadowing Limitations of Log-distance path loss normal Model Gives only the average value of path loss. Does not consider the fact that the surrounding environmental clutter may be vastly different at two different locations having the same T-R separation. Thus measured signals average value predicted are different than the

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Log-normal shadowing The long-term variation in the mean level is known as shadowing or log-normal fading. This fading caused by shadowing. Observes that the environment can be vastly different at two points with the same distance of separation. Shadowing occurs when objects block LOS between transmitter and receiver

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Log-normal shadowing Measurements have shown that at any value of d, the path loss PL(d) at a particular location is random and distributed lognormally A simple statistical model can account for unpredictable shadowing Add a Zero -mean Gaussian RV to Log-Distance PL The measured loss in dB varies about this mean according to a zero-mean Gaussian RV, X, with standard deviation

X : zero mean Gaussian random variable, a bell curve26

Log-Normal Shadowing

is the standard deviation that takes into account received signal strength variations due to shadowing n & are computed from measured data for different area types

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Log-Normal Model This distribution is applicable where the propagation environment has high rising structures like tall buildings and trees. The signal does not adopt different propagation immediately after it is transmitted from the antenna. paths

Rather, it undergoes through multiple reflections or scattering through tall structures prior to adopting multiple paths to the receiver. Therefore, the signal reaching the receiver will not be the result of single scattering effect but will be the result of multiple scattering.

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Log-Normal Model Multiple scattering introduces further fluctuation in the received signal. The long-term variation in the mean level is known as shadowing or log-normal fading. This fading is caused by shadowing.

Accounts for random variations in received power observed over distances comparable to the widths of buildings Extra transmit power (a fading margin) must be provided to compensate for these fades. Log normal distribution typical model for random attenuation Random due to random number and type of obstructions29

Log-Normal Model The probability density function and cumulative distribution functions are given by

log10 ( r) 1 P(r) = exp r 2 2 where and are

(

)

2

, r >0

the standard deviation and mean

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Log-normal Distribution

2 p(M)

M The pdf of the received signal level

M

where M is the true received signal level m in decibels, i.e., 10log10 m, M is the area average signal level, i.e., the mean of M, 31 is the standard deviation in decibels

Longley Rice model To calculate large-scale median transmission loss relative to free space loss Available as a computer program to calculate large-scale median transmission loss relative to free space loss over irregular terrain for frequencies between 20 MHz and 10 GHz Geometric Optics Techniques (primarily the 2-ray ground reflection model) are used to predict signal strengths within the radio horizon. Diffraction losses over isolated obstacles are estimated using the FresnelKirchoff knife-edge models

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Longley Rice model Inputs of the program the transmission frequency Path length Polarization Antenna heights Surface refractivity Effective radius of earth Ground conductivity Ground dielectric constant Climate33

Longley Rice modelTwo modes of operation Point-to-point mode prediction When a detailed terrain path profile is available

Area mode prediction When a detailed terrain path profile not available Provides techniques specific parameter to estimate the path-

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Longley Rice model Modifications and corrections Radio propagation in urban areas for mobile Introduction of an excess term as an allowance for the additional attenuation due to urban clutter near the receiving antenna. Urban factor (UF)

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Longley Rice model Shortcoming Does not provide a way of determining corrections due to environmental factors in the immediate vicinity of the mobile receiver Multipath not considered. Does not consider correction factors to account for the effects of buildings and foliage

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Okumura Model Used for signal prediction in urban areas Applicable for frequencies in the range 150 MHz to 1920 MHz (Extrapolated up to 3000 MHz) Applicable for distances of 1 km to 100 km.

Totally based on measured data and does not provide any analytical explanation.

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Okumura Model Median Attenuation Curve Okumura developed a set of curves giving the median attenuation (Amu ) relative to free space (Amu), in an urban area over a quasi-smooth terrain with a base station effective antenna height (hte) of 200 m and a mobile antenna height (hre) of 3m

These curves were developed from extensive measurements using vertical omni-directional antennas at both the base and mobile, Plotted as a function of frequency in the range 100 MHz to 1920 MHz and distance from the base station in the range 1 km to 100 km.

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Structure of the Okumura Model

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Okumura Model

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Okumura Model Advantages Simplest best in terms of accuracy in path loss prediction for mature cellular and land mobile radio systems in cluttered environments. It is very practical and has become a standard for system planning in modern land mobile radio systems in Japan

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Okumura Model Disadvantages Model is slow in response to rapid changes in terrain, Model is fairly good in urban and suburban areas, but not as good in rural areas.

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Hata Model

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Hata Model Empirical formulation of the graphical path loss data provided by Okumura, and is