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system performance through combating channel impairments.
2.2. Cooperative Diversity
Some early works on cooperation communications [14,15] introduced a basic commu-
nication structure among nodes to exploit cooperative diversity. The results suggested that
even in a noisy environment, the diversity created through cooperation between in-cluster
nodes can not only increase the overall channel capacity, but also provide a more robust
system to combat channel fading.
Laneman and Wornell developed cooperative diversity protocols given consideration
of cooperating radio implementing constraint. In this work, the spatial diversity achieved
through coordinated transmission was exploit on a distributed antenna system to combat
multipath fading [16-18]. Their previous work assumes the node in the cluster can transmit
and receive simultaneously (full-duplex). Since the full-duplex assumption is not applicable in
practice, a constraint of half-duplex was employed to the cluster node [3]. Also, for a sensor
network built in nonergodic scenarios like discrete-time channel models, it is more applicable
to use outage probability for the system performance evaluation [19].
In addition to cooperative diversity, multiuser diversity can also increase channel capac-
ity. Multiuser diversity focuses on the uplink in a single cell [20]. A multiuser diversity system
can improve channel capacity by exploiting fading. In this model, multiple users communicate
to the base station on time-varying fading channels, and the receiver will track the channel
state information and feed back to the transmitters. An efficiency strategy to maximize the
total information-theoretic capacity is to schedule at any one time only the user with the
best channel to transmit to the base station. Diversity gain is obtained by finding one among
all the independent user channels that is near its peak. It can also be considered as another
form of selection diversity.
Multiuser diversity is combined with transmit beamforming in [21] to achieve coherent
beamforming capacity. In this model, the transmitter only requires received signal-to-noise11
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Li, Li. Source and Channel Coding Strategies for Wireless Sensor Networks, dissertation, December 2012; Denton, Texas. (https://digital.library.unt.edu/ark:/67531/metadc177226/m1/21/: accessed March 28, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; .