Multicast Capacity Scaling of Wireless Networks with Multicast Outage

TL;DR

This paper analyzes the multicast capacity scaling in wireless networks considering outage and retransmissions, revealing how multiple attempts and network parameters influence the maximum achievable multicast rate.

Contribution

It introduces a new capacity metric for multicast networks using a Poisson cluster process and derives the scaling law considering retransmissions and outage effects.

Findings

Multicast capacity scales as Θ(ρ k^x log(k)) with network parameters.

Allowing retransmissions significantly improves multicast capacity.

The model captures key multicast traits like outage and multiple receivers.

Abstract

Multicast transmission has several distinctive traits as opposed to more commonly studied unicast networks. Specially, these include (i) identical packets must be delivered successfully to several nodes, (ii) outage could simultaneously happen at different receivers, and (iii) the multicast rate is dominated by the receiver with the weakest link in order to minimize outage and retransmission. To capture these key traits, we utilize a Poisson cluster process consisting of a distinct Poisson point process (PPP) for the transmitters and receivers, and then define the multicast transmission capacity (MTC) as the maximum achievable multicast rate times the number of multicast clusters per unit volume, accounting for outages and retransmissions. Our main result shows that if $\tau$ transmission attempts are allowed in a multicast cluster, the MTC is $\Theta\left(\rho k^{x}\log(k)\right)$ where $\rho$ and $x$ are functions of $\tau$ depending on the network size and density, and $k$ is the average number of the intended receivers in a cluster. We also show that an appropriate number of retransmissions can significantly enhance the MTC.