MIMO Systems: Principles, Iterative Techniques, and Advanced Polarization - Adaptive Signal Processing in Wireless Communications - page 128

form some links that SISO cannot. In the elongated region scenario this trend holds,
though it is less apparent [89].
There is also an increasing need for mobile networks with distributed transmitters and
receivers, typically referred to as mobile ad hoc networks (MANETs). There, transmitters
and receivers do not pool their information together, either due to geographical disper-
siveness, the bandwidth and resource limitation, or due to security/privacy concerns.
Recognizing that multiple antennas at the transceivers provide inherent multiplexing
capability due to their spatial selectivity, it is attractive to study MIMO communication
in ad hoc networks with interference transmission.
Energy-efficient communication techniques typically focus on minimizing the trans-
mission energy only, which is reasonable in long-range applications where the transmis-
sion energy is dominant in the total energy consumption.
In cooperative sensor networks, we allow the cooperation among sensors for infor-
mation transmission or reception, so that energy consumption as well as transmission
delays over some distance ranges can be reduced.
In conclusion, for the same throughput requirement, MIMO systems require less
transmission energy than SISO systems. However, direct application of multiantenna
techniques to sensor networks is impractical due to the limited physical size of a sensor
node, which typically can only support a single antenna. If individual single-antenna
nodes allowed cooperating on information transmission or reception, a cooperative
MIMO system can be constructed such that energy-efficient MIMO schemes can be
deployed [90]. Finally, MIMO can provide significant network performance improve-
ments in power consumption, latency, and network robustness.
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