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Published in Lal Chand Godara, Handbook of Antennas in Wireless Communications, 2018
When the received signal is made up of multiple reflective rays plus a significant LOS (nonfaded) component, the received envelope amplitude has a Rician pdf, shown as follows, and the fading is referred to as Rician fading [2]. () p(r0)={r0σ2exp[−(r02+A2)2σ2]I0(r0Aσ2)forr0≥0,A≥00otherwise
Force-System Resultants and Equilibrium
Published in Richard C. Dorf, The Engineering Handbook, 2018
Figure 1.139 illustrates the phenomenon of multi-path propagation experienced by signals traveling from a transmitter to a receiver via several reflecting and scattering objects. Each of the multiple paths experiences a different attenuation and time delay (and resulting phase offset). What is seen at the receiver is the superposition of these multiple waves. This superposition can cause constructive or destructive interference depending on the phase relationship among the different waves. Therefore the amplitude of the resultant received signal will depend on the particular multipath structure seen at the receiver. As the mobile receiver moves in space, the radio paths between the transmitter and receiver will change giving rise to a different multipath structure. This change in multipath structure changes the relative phase and amplitude of the received waves, and thereby changes the amplitude of the resultant signal Therefore, as the receiver moves in space, the amplitude of the received signal varies depending on variation in the multipath structure. Thus, spatial variation in multipath structure is manifested as temporal variation in the received signal strength of a mobile receiver. This variation in received signal strength caused by multipath propagation is called multipath fading. Depending on the absence or presence of a dominant path (e.g., direct line of sight), the amplitude variation in the received signal caused by multi-path fading is often found to follow either a Rayleigh or Rician probability distribution, and therefore referred to as Rayleigh fading or Rician fading, respectively.
Power Control for Reliable M2M Communication
Published in Hongjian Sun, Chao Wang, Bashar I. Ahmad, From Internet of Things to Smart Cities, 2017
There are statistical models to represent shadowing and fading. Although statistical models cannot accurately represent actual systems, thanks to these models we have the opportunities to obtain a clearer perspective and understanding of wireless communication systems. In the channel statistical models, we take each link’s fading at any time t as an independent and identically distributed (i. i. d.) random variable. Shadowing is usually modeled as a random variable with log-normal distribution. Typical fading distributions are Rician fading, Rayleigh fading, and Nakagami fading [29]. When there is a line-of-sight path between transmitter and receiver, or there is a specular path between transmitter and receiver, the channel is represented by a Rician fading model. When there is not a main path component, we can think of the channel consisting of many small paths. Rayleigh fading model is the most widely used model. The Nakagami model is known to provide a closer match to some measurement data than either Rayleigh or Rician distributions [4]. The Nakagami model can be used to model the channel which is more or less severe than Rayleigh fading. The Nakagami model defines a Nakagami shape factor m. When m =1, the Nakagami distribution becomes the Rayleigh distribution, and when m œ the distribution approaches an impulse (no fading). The Nakagami model has been recently used in vehicular networks.
Distributed polar-coded OFDM based on Plotkin’s construction for half duplex wireless communication
Published in International Journal of Electronics, 2018
Rahim Umar, Fengfan Yang, Shoaib Mughal, HongJun Xu
where is the Dirac delta function, is the delay of the l-th resolvable path such that , is the complex channel gain of l-th resolvable paths. The with different l are uncorrelated zero-mean complex random variables with variance. The power of L paths is normalised such that. In the case of AWGN channel, is taken as unity. However, in the case of Rician fading channel, the channel model with Rician distribution is defined as a sum of non-line of sight (NLOS) component and line of sight (LOS) component (n) that can be modelled as follows:
Performance evaluation of distributed CSS with clustering of secondary users over fading channels
Published in International Journal of Electronics Letters, 2018
Figure 6 illustrates complimentary ROC curves for OR–OR fusion over Nakagami, Rician and Rayleigh fading channels. Rician k = 0 and Nakagami m = 1 curves coincide with Rayleigh curve and therefore are not shown here. Clearly performance improvement is observed for m = 2–4 and k = 1–2. The Rician fading constant k is the ratio of power in direct path and scattered paths. Larger values of k give better performance as we can see in Figure 6, performance improves as Rician fading constant increases.