30,362 research outputs found
A New Phase Transition for Local Delays in MANETs
We consider Mobile Ad-hoc Network (MANET) with transmitters located according
to a Poisson point in the Euclidean plane, slotted Aloha Medium Access (MAC)
protocol and the so-called outage scenario, where a successful transmission
requires a Signal-to-Interference-and-Noise (SINR) larger than some threshold.
We analyze the local delays in such a network, namely the number of times slots
required for nodes to transmit a packet to their prescribed next-hop receivers.
The analysis depends very much on the receiver scenario and on the variability
of the fading. In most cases, each node has finite-mean geometric random delay
and thus a positive next hop throughput. However, the spatial (or large
population) averaging of these individual finite mean-delays leads to infinite
values in several practical cases, including the Rayleigh fading and positive
thermal noise case. In some cases it exhibits an interesting phase transition
phenomenon where the spatial average is finite when certain model parameters
are below a threshold and infinite above. We call this phenomenon, contention
phase transition. We argue that the spatial average of the mean local delays is
infinite primarily because of the outage logic, where one transmits full
packets at time slots when the receiver is covered at the required SINR and
where one wastes all the other time slots. This results in the "RESTART"
mechanism, which in turn explains why we have infinite spatial average.
Adaptive coding offers a nice way of breaking the outage/RESTART logic. We show
examples where the average delays are finite in the adaptive coding case,
whereas they are infinite in the outage case.Comment: accepted for IEEE Infocom 201
On Modeling Heterogeneous Wireless Networks Using Non-Poisson Point Processes
Future wireless networks are required to support 1000 times higher data rate,
than the current LTE standard. In order to meet the ever increasing demand, it
is inevitable that, future wireless networks will have to develop seamless
interconnection between multiple technologies. A manifestation of this idea is
the collaboration among different types of network tiers such as macro and
small cells, leading to the so-called heterogeneous networks (HetNets).
Researchers have used stochastic geometry to analyze such networks and
understand their real potential. Unsurprisingly, it has been revealed that
interference has a detrimental effect on performance, especially if not modeled
properly. Interference can be correlated in space and/or time, which has been
overlooked in the past. For instance, it is normally assumed that the nodes are
located completely independent of each other and follow a homogeneous Poisson
point process (PPP), which is not necessarily true in real networks since the
node locations are spatially dependent. In addition, the interference
correlation created by correlated stochastic processes has mostly been ignored.
To this end, we take a different approach in modeling the interference where we
use non-PPP, as well as we study the impact of spatial and temporal correlation
on the performance of HetNets. To illustrate the impact of correlation on
performance, we consider three case studies from real-life scenarios.
Specifically, we use massive multiple-input multiple-output (MIMO) to
understand the impact of spatial correlation; we use the random medium access
protocol to examine the temporal correlation; and we use cooperative relay
networks to illustrate the spatial-temporal correlation. We present several
numerical examples through which we demonstrate the impact of various
correlation types on the performance of HetNets.Comment: Submitted to IEEE Communications Magazin
Optimal Paths on the Space-Time SINR Random Graph
We analyze a class of Signal-to-Interference-and-Noise-Ratio (SINR) random
graphs. These random graphs arise in the modeling packet transmissions in
wireless networks. In contrast to previous studies on the SINR graphs, we
consider both a space and a time dimension. The spatial aspect originates from
the random locations of the network nodes in the Euclidean plane. The time
aspect stems from the random transmission policy followed by each network node
and from the time variations of the wireless channel characteristics. The
combination of these random space and time aspects leads to fluctuations of the
SINR experienced by the wireless channels, which in turn determine the
progression of packets in space and time in such a network. This paper studies
optimal paths in such wireless networks in terms of first passage percolation
on this random graph. We establish both "positive" and "negative" results on
the associated time constant. The latter determines the asymptotics of the
minimum delay required by a packet to progress from a source node to a
destination node when the Euclidean distance between the two tends to infinity.
The main negative result states that this time constant is infinite on the
random graph associated with a Poisson point process under natural assumptions
on the wireless channels. The main positive result states that when adding a
periodic node infrastructure of arbitrarily small intensity to the Poisson
point process, the time constant is positive and finite
Analysis and Optimization of Cellular Network with Burst Traffic
In this paper, we analyze the performance of cellular networks and study the
optimal base station (BS) density to reduce the network power consumption. In
contrast to previous works with similar purpose, we consider Poisson traffic
for users' traffic model. In such situation, each BS can be viewed as M/G/1
queuing model. Based on theory of stochastic geometry, we analyze users'
signal-to-interference-plus-noise-ratio (SINR) and obtain the average
transmission time of each packet. While most of the previous works on SINR
analysis in academia considered full buffer traffic, our analysis provides a
basic framework to estimate the performance of cellular networks with burst
traffic. We find that the users' SINR depends on the average transmission
probability of BSs, which is defined by a nonlinear equation. As it is
difficult to obtain the closed-form solution, we solve this nonlinear equation
by bisection method. Besides, we formulate the optimization problem to minimize
the area power consumption. An iteration algorithm is proposed to derive the
local optimal BS density, and the numerical result shows that the proposed
algorithm can converge to the global optimal BS density. At the end, the impact
of BS density on users' SINR and average packet delay will be discussed.Comment: This paper has been withdrawn by the author due to missuse of queue
model in Section Fou
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