CHANNEL MODELLING Archana K B Sr Asst professor

CHANNEL MODELLING Archana K B Sr. Asst. professor ECE Dept. VNR VJIET, HYD.

What U want to know is, what U know – No information conveyed What U want to know is, what U don’t know, but u don’t know what U want to know – Information useless What U want to know is, what U don’t know, but u know what U don’t know – Information conveyed Hence purpose of communication or communication system is: To convey information

Mathematical Modeling of a Communication Channel Contents 1. Types of channels 2. Mathematical Models for Communications Channels 3. Mathematical Models for Wireless Channels 4. 5. 6. 7. 8. Multipath Fading Channels Types of Multipath Fading Channels Fading channel manifestations Fading channel Mitigations Matlab support for channel models

what is a channel or more precisely what is communication channel?

1. Types and Characteristics of channels: • Wire line channels: operates at frequency few k. Hz to several hundreds of k. Hz. • Fiber Optical Channels: provides bandwidth in the magnitude several times higher than that of wire line channel • Wireless Electromagnetic Channels: operates in the range of 10 k. Hz to =~ 100 GHz, this is further categorized as long wave radio, short wave radio, microwave radio as they operates in radio frequency they are also known as ‘radio’ or ‘radio channel’. • Under Water Acoustic Channels: operated at extremely low frequencies. • Storage Channels: like magnetic tapes, magnetic disks etc.

2. Mathematical Models for Communications Channels • Description of the channel models that are frequently used to characterize many of the physical channels that we encounter in practice are: 2. a. The Additive Noise Channel • The simplest mathematical model for a communication channel is the additive noise channel. In this model the transmitted signal s(t) is corrupted by an additive random noise process n(t). Physically, the additive noise process may arise from electronic components and amplifiers at the receiver of the communication system, or from interference encountered in transmission, as in the case of radio signal transmission. • r(t) = as(t)+n(t) where a is the attenuation factor

2. b. The Linear Filter Channel • In some physical channels such as wireline telephone channels, filters are used to ensure that the transmitted signals do not exceed specified bandwidth limitations and, thus, do not interfere with one another. Such channels are generally characterized mathematically as linear filter channels with additive noise. Hence, if the channel input is the signal s(t), the channel output is the signal • where h(t) is the impulse response of the linear filter and denotes convolution.

2. c. The Linear Time-Variant Filter Channel For an input signal s(t), the channel output signal is A good model for multipath signal propagation through physical channels, such as the ionosphere (at frequencies below 30 MHz) and mobile cellular radio channels, is a special case of above Equation in which the time-variant impulse response has the form where the {ak(t)} represent the possibly time-variant attenuation factors for the L multipath propagation paths. Hence, the received signal consists of L multipath components, where each component is attenuated by {ak} and delayed by {tk}.

3. Mathematical Models for Wireless Channels There are three broad classes of channel phenomena of Interest 1. Multipath Fading: constructive and destructive interference caused by multiple TX-RX paths with different lengths arriving from different directions. Signal envelope varies widely over 30 d. B in the span of a few wavelengths in distance Multipath fading is used for physical layer modem design such as coder, modulator, interleaver, etc 2. Shadowing Short-term average variation or large-scale signal variation caused by local changes in terrain features or man-made obstacles (e. g. blockage) Shadowing is used for power control design, 2 nd order interference and TX power Analysis and more detailed link budget and cell coverage analysis • •

Path Loss Model Long-term or large-scale average signal level depends on the distance between TX and RX Path loss model is used for system planning, cell coverage and link budget

4. Multipath Fading Channels Fading channels are useful models of real-world phenomena in wireless communications. These phenomena include multipath scattering effects, time dispersion, and Doppler shifts that arise from relative motion between the transmitter and receiver.

Why Multipath Fading Channels ? • In the study of communication systems the classical (ideal) additive white Gaussian noise (AWGN) channel, is not sufficient to model a practical channel. • If a radio channel’s propagating characteristics are not specified, one usually infers that the signal attenuation versus distance behaves as if propagation takes place over ideal free space. Thus over optimizing the channel. • In a wireless mobile communication system, a signal can travel from transmitter to receiver over multiple reflective paths; this phenomenon is referred to as multipath propagation. The effect can cause fluctuations in the received signal’s amplitude, phase, and angle of arrival, giving rise to the terminology multipath fading which is dynamic, random and relevant to the environment. • By taking these hostile conditions into account, it is a challenge to accurately model the channel mathematically in order to make the model more realistic, leading to higher performance of the communication system.

5. Types of Multipath Fading Channels • Typically, the fading process is characterized by a Rayleigh distribution for a non line-ofsight path and a Rician distribution for a lineof-sight path. • A number of other probability distributions functions are also used to characterize different types of channels. Below is a list of distribution functions and the environment they model.

5. a. Rayleigh fading Channel 5. b. Rician fading Channel

6. Fading channel manifestations Two types of fading effects that characterize mobile communications: large-scale and small-scale fading. Fading channel manifestations

Relationships among the channel correlation functions and power density functions.

Small-scale fading: mechanisms, degradation categories, and effects

7. Fading channel Mitigations

Impact of Fading channels on Wireless communication systems

8. Matlab support for channel models Communication toolbox of Matlab supports these types of channels: • Additive white Gaussian noise (AWGN) channel • Fading channel • Binary symmetric channel, for binary signals • MATLAB support for channel Modelling

Radio Propagation and Propagation Path-Loss Models Refl ection, diffraction and scattering of radio wave.

Propagation Path-Loss Models • Propagation path-loss models play an important role in the design of cellular systems to specify key system parameters such as transmission power, frequency, antenna heights, and so on. • Several models have been proposed for cellular systems operating in different environments (indoor, outdoor, urban, suburban, rural). • Propagation models are used to determine the number of cell sites required to provide coverage for the network. Initial network design typically is based on coverage. Later growth is engineered for capacity. • The propagation model is also used in other system performance aspects including handoff optimization, power level adjustments, and antenna placements.

Widely used empirical models • The Okumura/Hata model has been used extensively both in Europe and NA for cellular systems. • The COST 231 model has been recommended by the European Telecommunication Standard Institute (ETSI) for use in (PCN/PCS). • International Mobile Telecommunication-2000 (IMT 2000) for the indoor office environment, outdoor to indoor pedestrian environment, and vehicular environment.

The Okumura/Hata model • Okumura analyzed path-loss characteristics based on a large amount of experimental data collected around Tokyo, Japan. • Applied several correction factors for other propagation conditions, such as: a. Antenna height and carrier frequency b. Suburban, quasi-open space, or hilly terrain areas c. Diffraction loss due to mountains d. Sea or lake areas e. Road slope • Hata derived empirical formulas for the median path loss (L 50) to fit Okumura curves. Hata’s equations are classified into three models such TYPICAL URBAN, TYPICAL SUBURBAN, RURAL.

COST 231 Model • This model is a combination of empirical and deterministic models for estimating the path loss in an urban area over the frequency range of 800 MHz to 2000 MHz. • The model is used primarily in Europe for the GSM 1800 system.

IMT-2000 Models • The operating environments are identified by appropriate subsets consisting of indoor office environments, outdoor to indoor and pedestrian environments, and vehicular (moving vehicle) environments. • The key parameters of the IMT-2000 propagation models are: a. Delay spread, its structure, and its statistical variation b. Geometrical path loss rule c. Shadow fading margin d. Multipath fading characteristics (e. g. , Doppler spectrum, Rician vs. Rayleigh for envelope of channels) e. Operating radio frequency