This document discusses smart co-channel interference mitigation techniques in MIMO communication networks. It examines the problem of interference when there are many transmitter-receiver pairs operating in a small area using MIMO. Simply increasing transmit power is not optimal, and capacity per unit area is a better metric. The document analyzes the channel capacity for an uninformed transmitter with no channel state information and an informed transmitter with feedback. It finds that an informed transmitter using techniques like water-filling of transmit power across antenna modes can improve resistance to interference. Further improvements may come from combining methods such as power control, channel sensing, link adaptation, and transmit/receive beamforming to significantly increase network capacity density.

1. Smart co-channel Interference
Mitigation in MIMO
Communication Networks
Niranjan Thontadarya
School of Electrical, Computer,
and Energy Engineering
Arizona State University
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2. IEEE BSN- 2
Bliss 5/9/13
Introduction to the Problem
 Many pairs of nodes in a small area, all of
which are MIMO systems
 High power is not always the right answer. If
there was only one link, it would be.
 Capacity per unit area is a possible metric to
consider.
 Interference here is ‘spacially coloured’ and
also, users have different data rate.
System Model Changes:
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3. IEEE BSN- 3
Bliss 5/9/13
Uninformed Transmitter Capacity 2
The received matrix is:
Hence the interference plus noise
covariance matrix is given by:
The transmit covariance matrix is:
Hence, the Covariance matrix of the
received signal will be:
The knowledge of the channel estimate and the
interference could help a lot but in an
absolutely dumb system, the best we can do is
to transmit equally through all the antennas.
Such is the case in an Uninformed Transmitter
(No CSIT). The transmit covariance hence
becomes just
In this simple case, the channel capacity is :
The transmitter has no information about the
channel or the interference here.

4. IEEE BSN- 4
Bliss 5/9/13
Uninformed Transmitter Capacity 3
Merely increasing the number of antennas does not seem to be the answer. As few as ten
interferers can completely cripple the established link.

5. IEEE BSN- 5
Bliss 5/9/13
Informed Transmitter Capacity 4
When there exists some feedback from the receiver about the channel and the interference, we
know what to expect while transmitting and having a set of Tx antennae affords us modes that
help us ‘maneuver’ the signal better.
The whitened channel matrix estimate is decomposed as
And the new capacity is found to be
Where the weights p are chosen such that
Under the power constraint:
And the transmit covariance
matrix is hence,
Simply put, we are pushing the maximum power into
the most significant singularities of the channel, and
this method is called ‘Water Filling Example’

6. IEEE BSN- 6
Bliss 5/9/13
Informed Transmitter Capacity 5
Some improvement in the channel’s resistance to interferers is seen right away, even when
transmitting in just the strongest mode, as seen above.

7. IEEE BSN- 7
Bliss 5/9/13
More Improvements Possible 6
 Water filling in all the nodes
 Power Control
 Channel Sensing – MAC
 Link Adaptation
 A MIMO ‘Network’ rather than independent
Tx-Rx pairs
 Tx/Rx beamforming
 More than one or all of the above at the same
time!
The ultimate goal is to increase the Capacity density (bps/Hz/km2) by many folds.

8. IEEE BSN- 8
Bliss 5/9/13