20 research outputs found
Random Matrix Theory applied to the Estimation of Collision Multiplicities
This paper presents two techniques in order to estimate the collision multiplicity, i.e., the number of users involved in a collision [1]. This estimation step is a key task in multi-packet reception approaches and in collision resolution techniques. The two techniques are proposed for IEEE 802.11 networks but they can be used in any OFDM-based system. The techniques are based on recent advances in random matrix theory and rely on eigenvalue statistics. Provided that the eigenvalues of the covariance matrix of the observations are above a given threshold, signal eigenvalues can be separated from noise eigenvalues since their respective probability density functions are converging toward two different laws: a Gaussian law for the signal eigenvalues and a Tracy-Widom law for the
noise eigenvalues. The first technique has been designed for the white noise case, and the second technique has been designed for the colored noise case. The proposed techniques outperform current estimation techniques in terms of mean square error. Moreover, this paper reveals that, contrary to what is generally assumed in current multi-packet reception techniques, a single observation of the colliding signals is far from being sufficient to
perform a reliable estimation of the collision multiplicities
Optimal Tradeoff Between Exposed and Hidden Nodes in Large Wireless Networks
Wireless networks equipped with the CSMA protocol are subject to collisions
due to interference. For a given interference range we investigate the tradeoff
between collisions (hidden nodes) and unused capacity (exposed nodes). We show
that the sensing range that maximizes throughput critically depends on the
activation rate of nodes. For infinite line networks, we prove the existence of
a threshold: When the activation rate is below this threshold the optimal
sensing range is small (to maximize spatial reuse). When the activation rate is
above the threshold the optimal sensing range is just large enough to preclude
all collisions. Simulations suggest that this threshold policy extends to more
complex linear and non-linear topologies
Towards a System Theoretic Approach to Wireless Network Capacity in Finite Time and Space
In asymptotic regimes, both in time and space (network size), the derivation
of network capacity results is grossly simplified by brushing aside queueing
behavior in non-Jackson networks. This simplifying double-limit model, however,
lends itself to conservative numerical results in finite regimes. To properly
account for queueing behavior beyond a simple calculus based on average rates,
we advocate a system theoretic methodology for the capacity problem in finite
time and space regimes. This methodology also accounts for spatial correlations
arising in networks with CSMA/CA scheduling and it delivers rigorous
closed-form capacity results in terms of probability distributions. Unlike
numerous existing asymptotic results, subject to anecdotal practical concerns,
our transient one can be used in practical settings: for example, to compute
the time scales at which multi-hop routing is more advantageous than single-hop
routing
Stability conditions for a discrete-time decentralised medium access algorithm
We consider a stochastic queueing system modelling the behaviour of a
wireless network with nodes employing a discrete-time version of the standard
decentralised medium access algorithm. The system is {\em unsaturated} -- each
node receives an exogenous flow of packets at the rate packets per
time slot. Each packet takes one slot to transmit, but neighboring nodes cannot
transmit simultaneously. The algorithm we study is {\em standard} in that: a
node with empty queue does {\em not} compete for medium access; the access
procedure by a node does {\em not} depend on its queue length, as long as it is
non-zero. Two system topologies are considered, with nodes arranged in a circle
and in a line. We prove that, for either topology, the system is stochastically
stable under condition . This result is intuitive for the circle
topology as the throughput each node receives in a saturated system (with
infinite queues) is equal to the so called {\em parking constant}, which is
larger than . (The latter fact, however, does not help to prove our
result.) The result is not intuitive at all for the line topology as in a
saturated system some nodes receive a throughput lower than .Comment: 22 page
High-SIR Transmission Capacity of Wireless Networks with General Fading and Node Distribution
In many wireless systems, interference is the main performance-limiting
factor, and is primarily dictated by the locations of concurrent transmitters.
In many earlier works, the locations of the transmitters is often modeled as a
Poisson point process for analytical tractability. While analytically
convenient, the PPP only accurately models networks whose nodes are placed
independently and use ALOHA as the channel access protocol, which preserves the
independence. Correlations between transmitter locations in non-Poisson
networks, which model intelligent access protocols, makes the outage analysis
extremely difficult. In this paper, we take an alternative approach and focus
on an asymptotic regime where the density of interferers goes to 0. We
prove for general node distributions and fading statistics that the success
probability \p \sim 1-\gamma \eta^{\kappa} for , and
provide values of and for a number of important special
cases. We show that is lower bounded by 1 and upper bounded by a value
that depends on the path loss exponent and the fading. This new analytical
framework is then used to characterize the transmission capacity of a very
general class of networks, defined as the maximum spatial density of active
links given an outage constraint.Comment: Submitted to IEEE Trans. Info Theory special issu