Wireless Network Design: Optimization Models and Solution ...

3 Channel Models for Wireless Communication Systems 61
3.5.2.6 Indoor Models Based on Measurement Data
The clustering model is applied to the indoor environment and validated with measurements
[37, 41]. The channel response is given by
h(t) =
∞ ∞
∑ ∑
k=0 l=0
αkl δ(t − τkl − Tk) (3.27)
where k denotes the cluster, l denotes the ray within a cluster, and αkl is a Rayleigh
distributed random variable. An extension to this model was proposed in [37].
Here, h(t, θ) = h(t)h(θ) with the assumption that temporal and angular impulse
responses are independent. The angular impulse response is given by
h(θ) =
∞ ∞
∑ ∑
k=0 l=0
αkl δ(t − ωkl −Θk) (3.28)
with ωkl is the ray angle and Θk is the mean angle of the kth cluster. The probability
density function of ωkl is given by f (ω) = (1/2 √ σ exp(−| √ 2ω/σ|)) The Time-
Angle FIR filter model [20] defines the channel impulse response as
h(t,τ,θ) =
Q
∑
q=1
αqδ(t − τq)δ(θ − θq) (3.29)
where the FIR structure has Q taps. This is a simple extension of the temporal FIR
model presented before.
3.6 Conclusion
The wireless channel models presented in previous sections are used for designing
highly efficient communication systems which can provide huge data rates. The
statistical nature of these models provides a means to cover most of the possible
scenarios in the real-world through an exhaustive numerical simulation study. The
choice of models is varied and an appropriate choice of the model can be made based
on the specifications of the wireless system to be designed. This chapter provides a
brief introduction to this topic of wireless channel models which have been used to
design the present digital wireless communication systems.
References
1. Digital Land Mobile Radio Communications - COST 207”, Commission of the European
Communities, Final Report. Commission of the European Communities, Final Report, 14