**2.3. Stanford University Interim (SUI) channel models**

SUI channel models are an extension of the earlier work by AT&T Wireless and Erceg. In this model a set of six channels was selected to address three different terrain types that are typical of the continental US [11]. This model can be used for simulations, design, development and testing of technologies suitable for fixed broadband wireless applications [12]. The parameters for the model were selected based upon some statistical models. The tables below depict the parametric view of the six SUI channels.

**3. Equalization in wireless channel**

**Table 2.** SUI Channels Parameter.

**Model Delay L(numberoftape)=3**

**Tap1 Tap2 Tap3 Kfactor**

0 µs 0.4 µs 0.9 µs

4 0 0

0 µs 0.4 µs 1.1 µs

2 0 0

0 µs 0.4 µs 0.9 µs

1 0 0

0 µs 1.5 µs 4 µs

0 0 0

0 µs 4 µs 10 µs

0 0 0

0 µs 14 µs 20 µs

0 0 0

0 dB -15 dB -20 dB 0.111 µs

0 dB -12 dB -15 dB 0.202 µs

0 dB -5 dB -10 dB 0.264 µs

0 dB -4 dB -8 dB 1.257 µs

0 dB -5 dB -10 dB 2.842 µs

0 dB -10 dB -14 dB 5.240 µs

**Gain**

SUI 1

SUI 2

SUI 3

SUI 4

SUI 5

SUI 6

**RMS Delay spread** 41

PAPR Reduction in WiMAX System http://dx.doi.org/10.5772/55380

wireless data systems.

Equalization defines any signal processing technique used at the receiver to alleviate the ISI problem caused by delay spread. Signal processing can also be used at the transmitter to make the signal less susceptible to delay spread: spread spectrum and multicarrier modulation fall in this category of transmitter signal processing techniques. ISI mitigation is required when the modulation symbol time *Ts* is on the order of the channel's rms delay spread *σTm*. Higher data rate applications are more sensitive to delay spread, and generally require high-perform‐ ance equalizers or other ISI mitigation techniques. In fact, mitigating the applications are more sensitive to delay spread, and generally require high-performance equalizers or other ISI mitigation techniques. In fact, mitigating the applications are more sensitive to delay spread, and generally require high-performance equalizers or other ISI mitigation techniques. In fact, mitigating the impact of delay spread is one of the most challenging hurdles for high-speed

Equalizer design must typically balance ISI mitigation with noise enhancement, since both the signal and the noise pass through the equalizer, which can increase the noise power. Nonlinear


**Table 1.** Terrain type for SUI channel.

The parametric view of the SUI channels is summarized in the Table 2. For simplicity, SUI 1 from train type C(Flat/Light tree density), SUI 3 from train type B(Hilly/Light tree density or Flat/moderate tree density),and SUI 5 from train type A(Hilly/moderate to heavy tree density) are considered in the following.


**Table 2.** SUI Channels Parameter.

cially true of fixed wireless systems, which do not experience fast fading and often are

The parametric statistical channel models discussed therefore in this chapter do not take into account specific wireless propagation environments. Although exactly modeling a wireless channel requires complete knowledge of the surrounding scatterers, such as buildings and plants, the time and computational demands of such a methodology are unrealistic, owing to the near-infinite number of possible transmit/receive locations and the fact that objects are subject to movement. Therefore, empirical and semiempirical wireless channel models have been developed to accurately estimate the path loss, shadowing, and small-scale fast fading. Although these models are generally not analytically tractable, they are very useful for simulations and to fairly compare competing designs. Empirical models are based on extensive measurement of various propagation environments, and they specify the parameters and

methods for modeling the typical propagation scenarios in various wireless systems.

SUI channel models are an extension of the earlier work by AT&T Wireless and Erceg. In this model a set of six channels was selected to address three different terrain types that are typical of the continental US [11]. This model can be used for simulations, design, development and testing of technologies suitable for fixed broadband wireless applications [12]. The parameters for the model were selected based upon some statistical models. The tables below depict the

C (Mostly flat terrain with light tree densities) SUI1, SUI2

A (Hilly terrain with moderate to heavy tree density) SUI5, SUI6

The parametric view of the SUI channels is summarized in the Table 2. For simplicity, SUI 1 from train type C(Flat/Light tree density), SUI 3 from train type B(Hilly/Light tree density or Flat/moderate tree density),and SUI 5 from train type A(Hilly/moderate to heavy tree density)

**TerrainType SUIChannels**

density) SUI3, SUI4

**2.3. Stanford University Interim (SUI) channel models**

B (Hilly terrain with light tree density or flat terrain with moderate to heavy tree

parametric view of the six SUI channels.

**Table 1.** Terrain type for SUI channel.

are considered in the following.

deployed to maximize LOS propagation.

**2.2. Empirical channel models**

40 Selected Topics in WiMAX
