The Effect of Fading, Channel Inversion, and Threshold Scheduling on Ad Hoc Networks

By Steven Weber, Jeffrey G. Andrews, Nihar Jindal. IEEE Transactions on Information Theory, 2007

327 citations recorded by the source corpus.

This paper addresses three issues in the field of ad hoc network capacity: the impact of (i) channel fading, (ii) channel inversion power control, and (iii) threshold-based scheduling on capacity. Channel inversion and threshold scheduling may be viewed as simple ways to exploit channel state information (CSI) without requiring cooperation across transmitters. We use the transmission capacity (TC) as our metric, defined as the maximum spatial intensity of successful simultaneous transmissions subject to a constraint on the outage probability (OP). By assuming the nodes are located on the infinite plane according to a Poisson process, we are able to employ tools from stochastic geometry to obtain asymptotically tight bounds on the distribution of the signal-to-interference (SIR) level, yielding in turn tight bounds on the OP (relative to a given SIR threshold) and the TC. We demonstrate that in the absence of CSI, fading can significantly reduce the TC and somewhat surprisingly, channel inversion only makes matters worse. We develop a threshold-based transmission rule where transmitters are active only if the channel to their receiver is acceptably strong, obtain expressions for the optimal threshold, and show that this simple, fully distributed scheme can significantly reduce the effect of fading.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/56eca07fbc2701011bebed026579b0e2f4f1ce66

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In Electrical and Electronic Engineering

Citations in the corpus

Spectrum allocation in tiered cellular networks (2009, background): “With FALOHA, there should be an optimal fraction of spectrum access for each femtocell in order to maximize the spatial reuse of spectrum, or in effect the net number of simultaneous transmissions per unit area[12], [13].”
Stochastic Geometry for Modeling, Analysis, and Design of Multi-Tier and Cognitive Cellular Wireless Networks: A Survey (2013, background): “5.1], [12]. that, compared to the PPP, the HCPP better captures the spatial distribution of the base stations in a real network deployment.”
Transmission capacity of ad hoc networks with spatial diversity (2007, background): “This approach was also taken in [16] which developed bounds on the transmission capacity for general fading models as well as power control and scheduling schemes with only individual channel state information and single antennas.”
Stochastic geometry and random graphs for the analysis and design of wireless networks (2009, background): “Arbitrary fading distributions can be accommodated at further loss of tractability [90], but agai n there is no change in the first-order effects of the system parameters.”
Interference in Large Wireless Networks (2009, background): “Bounds on the outage probability have been derived in [49, 51] in the context of the so-called transmission capacity, defined to be the maximum transmitter density given an outage constraint for transmissions to a receiver at fixed distance.”
Uplink capacity and interference avoidance for two-tier femtocell networks (2007, background): “This agrees with the observations in [22], [23].”
Cognitive and Energy Harvesting-Based D2D Communication in Cellular Networks: Stochastic Geometry Modeling and Analysis (2014, background): “Relaxing this assumption complicates the derived expressions without adding more insights [23].”