1 research outputs found
Coverage and Rate Analysis of Super Wi-Fi Networks Using Stochastic Geometry
Recent regulatory changes proposed by the Federal Communications Commission
(FCC) permitting unlicensed use of television white space (TVWS) channels
present new opportunities for designing wireless networks that make efficient
use of this spectrum. The favorable propagation characteristics of these
channels and their widespread availability, especially in rural areas, make
them well-suited for providing broadband services in sparsely populated regions
where economic factors hinder deployment of such services on licensed spectrum.
In this context, this paper explores the deployment of an outdoor Wi-Fi-like
network operating in TVWS channels, referred to commonly as a Super Wi-Fi
network. Since regulations governing unlicensed use of these channels allow (a)
mounting fixed devices up to a height of 30 m and operation at transmit powers
of up to 4 W EIRP, and (b) operation at transmit powers of up to 100 mW EIRP
for portable devices, such networks can provide extended coverage and higher
rates than traditional Wi-Fi networks. However, these gains are subject to the
viability of the uplink from the portable devices (clients) to the fixed
devices (access points (AP)) because of tighter restrictions on transmit power
of clients compared to APs. This paper leverages concepts from stochastic
geometry to study the performance of such networks with specific focus on the
effect of (a) transmit power asymmetry between APs and clients and its impact
on uplink viability and coverage, and (b) the interplay between height and
transmit power of APs in determining the network throughput. Such an analysis
reveals that (a) maximum coverage of no more than 700 m is obtained even when
APs are deployed at 30 m height, and (b) operating APs at transmit power of
more than 1 W is beneficial only at sparse deployment densities when rate is
prioritized over coverage.Comment: Published in IEEE International Symposium on Dynamic Spectrum Access
Networks (DySPAN), 2017 held at Baltimore, M