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Spectral Efficiency Scaling Laws in Dense Random Wireless Networks with Multiple Receive Antennas
This paper considers large random wireless networks where
transmit-and-receive node pairs communicate within a certain range while
sharing a common spectrum. By modeling the spatial locations of nodes based on
stochastic geometry, analytical expressions for the ergodic spectral efficiency
of a typical node pair are derived as a function of the channel state
information available at a receiver (CSIR) in terms of relevant system
parameters: the density of communication links, the number of receive antennas,
the path loss exponent, and the operating signal-to-noise ratio. One key
finding is that when the receiver only exploits CSIR for the direct link, the
sum of spectral efficiencies linearly improves as the density increases, when
the number of receive antennas increases as a certain super-linear function of
the density. When each receiver exploits CSIR for a set of dominant interfering
links in addition to the direct link, the sum of spectral efficiencies linearly
increases with both the density and the path loss exponent if the number of
antennas is a linear function of the density. This observation demonstrates
that having CSIR for dominant interfering links provides a multiplicative gain
in the scaling law. It is also shown that this linear scaling holds for direct
CSIR when incorporating the effect of the receive antenna correlation, provided
that the rank of the spatial correlation matrix scales super-linearly with the
density. Simulation results back scaling laws derived from stochastic geometry.Comment: Submitte
Aggregation Latency-Energy Tradeoff in Wireless Sensor Networks with Successive Inter- ference Cancellation
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