Lecture 5

MIMO Channel Equalisation MATLAB Programming Conclusions
System Model
v
s
y ˜s
H W H
y = Hs+v (1)
y — noisy N r-dimensional received vector
s — N t-dimensional transmit vector ∈ S N is assumed to be a
spatially-uncorrelated and uniformly distributed complex random vector process
with zero-mean and variance σ 2 s (i.e. R ss = E [ ss H] = σ 2 sI Nt
v — noise vector with dimension N r ×1 drawn from CN ( 0,σ 2 v)
, or
equivalently R vv = E [ vv H] = σ 2 vI Nr
H — N r ×N t flat-fading channel with entries h ij are assumed i.i.d. complex
Gaussian random variables with zero-mean and unit-variance E [ |h ij| 2] = 1, i.e.,
h ij ∈ CN (0,1)
Dr. Waleed Al-Hanafy Digital Signal Processing (ECE407) — Lecture no. 5
Linear Equalisation of MIMO Channels