Transmission capacity of ad hoc networks with spatial diversity

By Andrew M. Hunter, Jeffrey G. Andrews, Steven Weber. IEEE Transactions on Wireless Communications, 2007

376 citations recorded by the source corpus.

This paper derives the outage probability and transmission capacity of ad hoc wireless networks with nodes employing multiple antenna diversity techniques, for a general class of signal distributions. This analysis allows system performance to be quantified for fading or non-fading environments. The transmission capacity is given for interference-limited uniformly random networks on the entire plane with path loss exponent alpha > 2 in which nodes use: (1) static beamforming through M sectorized antennas, for which the increase in transmission capacity is shown to be thetas(M2) if the antennas are without sidelobes, but less in the event of a nonzero sidelobe level; (2) dynamic eigenbeamforming (maximal ratio transmission/combining), in which the increase is shown to be thetas(M 2/alpha ); (3) various transmit antenna selection and receive antenna selection combining schemes, which give appreciable but rapidly diminishing gains; and (4) orthogonal space-time block coding, for which there is only a small gain due to channel hardening, equivalent to Nakagami-m fading for increasing m. It is concluded that in ad hoc networks, static and dynamic beamforming perform best, selection combining performs well but with rapidly diminishing returns with added antennas, and that space-time block coding offers only marginal gains.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/993d1ac1fadaabca7cf93189e1d79171de66cba0

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Citations in the corpus

Millimeter Wave Cellular Networks: A MAC Layer Perspective (2015, methodology): “At the MAC layer, the beamforming is represented by using an ideal sector antenna pattern [27]–[29], where the directivity gain is a constant for all angles in the main lobe and equal to a smaller constant in the side lobe.”
Coverage and Rate Analysis for Millimeter-Wave Cellular Networks (2014, methodology): “For tractability of the a nalysis, the actual array patterns are approximated by a sector ed antenna model, which was used in prior ad hoc network analysis [25].”
Stochastic Geometry for Modeling, Analysis, and Design of Multi-Tier and Cognitive Cellular Wireless Networks: A Survey (2013, methodology): “Since the interference characterization technique used in [24], [73], [74] is limited to channel power gains that can be represented in the form of (9), in [75], the authors proposed the gamma distribution (i.”
Stochastic geometry and random graphs for the analysis and design of wireless networks (2009, background): “Multiple antennas can obviously increase the transmission capacity [60], [91]–[93].”
Spectrum Sharing for Device-to-Device Communication in Cellular Networks (2013, background): “case with ak = 1 and for ℓ 6= k, aℓ = 0: In this case, fW(x) = 1 Γ(k)θk k xk−1e−x/θk models Gamma distributed received power with mean kθk, which is useful for multiple antenna techniques (see, e.g., [27]). When k = 1, fW(x) = 1 θ1 e−x/θ1 models exponentially distributed received power with mean θ1,”