342 research outputs found
Average Rate of Downlink Heterogeneous Cellular Networks over Generalized Fading Channels - A Stochastic Geometry Approach
In this paper, we introduce an analytical framework to compute the average
rate of downlink heterogeneous cellular networks. The framework leverages
recent application of stochastic geometry to other-cell interference modeling
and analysis. The heterogeneous cellular network is modeled as the
superposition of many tiers of Base Stations (BSs) having different transmit
power, density, path-loss exponent, fading parameters and distribution, and
unequal biasing for flexible tier association. A long-term averaged maximum
biased-received-power tier association is considered. The positions of the BSs
in each tier are modeled as points of an independent Poisson Point Process
(PPP). Under these assumptions, we introduce a new analytical methodology to
evaluate the average rate, which avoids the computation of the Coverage
Probability (Pcov) and needs only the Moment Generating Function (MGF) of the
aggregate interference at the probe mobile terminal. The distinguishable
characteristic of our analytical methodology consists in providing a tractable
and numerically efficient framework that is applicable to general fading
distributions, including composite fading channels with small- and mid-scale
fluctuations. In addition, our method can efficiently handle correlated
Log-Normal shadowing with little increase of the computational complexity. The
proposed MGF-based approach needs the computation of either a single or a
two-fold numerical integral, thus reducing the complexity of Pcov-based
frameworks, which require, for general fading distributions, the computation of
a four-fold integral.Comment: Accepted for publication in IEEE Transactions on Communications, to
appea
Performance analysis for industrial wireless networks
Industrial wireless networks operate in harsher and noisier environments compared to
traditional wireless networks, while demanding high reliability and low latency. These
requirements, combined with the constant need for better coverage, higher data rates
and overall seamless user experience call for a paradigm shift in communication in regards
to the previous generations of technologies used. Cooperative diversity is one such
approach.
The main focus of this thesis is on the performance analysis of cooperative wireless
networks set in industrial environments – where the network, apart from additive white
Gaussian noise, is subject to multipath fading and shadowing, and/or temporary random
blockage effects. In these scenarios, in order to achieve specific performance metrics
such as error rates or outage probabilities, existing cooperative strategies are aided by
protocols in the channel between the cooperating nodes. Moreover, pair-wise analysis
investigates the correlation of multiple data flows.
Building upon existing repetition protocols, outage performance of a network subject
to fading and shadowing is observed, and the effects of fading and shadowing severity,
network dimension, average signal-to-noise ratio values and packet length are discussed.
Special cases are also observed, in which the composite fading channel is reduced to
several familiar propagation environments, unifying the analysis.
Afterwards, the analysis of more complex protocols is presented, taking into account
random blockage in the channels between cooperating nodes. A novel, threshold-based
internode protocol is introduced, which improves performance by listening to the transmissions
and choosing whether to send a packet immediately or after a waiting period.
As these two periods are close, the effect of temporal correlation is also investigated.
Apart from the exact outage probability expressions, simpler asymptotic expressions,
with and without blockage, are derived as well, giving a better insight on the network
behaviour at high average signal-to-noise ratio regimes.
Both outage probability and packet error rate can be also improved by adding automatic
repeat request schemes in the channel between cooperating nodes, which again
utilize the internode channels by re-sending data until it can be successfully decoded.
Error-free communication can be achieved, but at a delay cost. Nevertheless, a trade-off
between performance gains and delays remains, and can therefore be used for designing
wireless networks with different requirements – error-free or low-latency.
Finally, joint outage performance is investigated. Using a generic approach, which
can be applied to any sort of data where multiple sources are communicating over wireless
networks, pair-wise behaviour is investigated. As a result, any multi-route diversity
type of scheme will have this sort of behaviour, since particular point-to-point relay links
are being shared by source nodes. This in turn means that the performance of those
flows will be correlated. For higher layers, there is a difference in the behaviour, meaning
that when errors are correlated, data flows start behaving correlated as well. As a
result, negative acknowledgements may start to correlate as well. All of this contributes
to the network behaving in a correlated way, i.e., when something happens, it tends to
happen to more than one data flow
Applications of Stochastic Ordering to Wireless Communications
Stochastic orders are binary relations defined on probability distributions
which capture intuitive notions like being larger or being more variable. This
paper introduces stochastic ordering of instantaneous SNRs of fading channels
as a tool to compare the performance of communication systems over different
channels. Stochastic orders unify existing performance metrics such as ergodic
capacity, and metrics based on error rate functions for commonly used
modulation schemes through their relation with convex, and completely monotonic
(c.m.) functions. Toward this goal, performance metrics such as instantaneous
error rates of M-QAM and M-PSK modulations are shown to be c.m. functions of
the instantaneous SNR, while metrics such as the instantaneous capacity are
seen to have a completely monotonic derivative (c.m.d.). It is shown that the
commonly used parametric fading distributions for modeling line of sight (LoS),
exhibit a monotonicity in the LoS parameter with respect to the stochastic
Laplace transform order. Using stochastic orders, average performance of
systems involving multiple random variables are compared over different
channels, even when closed form expressions for such averages are not
tractable. These include diversity combining schemes, relay networks, and
signal detection over fading channels with non-Gaussian additive noise, which
are investigated herein. Simulations are also provided to corroborate our
results.Comment: 25 pages, 10 figures, Submitted to the IEEE transactions on wireless
communication
A Comprehensive Framework for Performance Analysis of Cooperative Multi-Hop Wireless Systems over Log-Normal Fading Channels
International audienceIn this paper, we propose a comprehensive framework for performance analysis of multi–hop multi–branch wireless communication systems over Log–Normal fading channels. The framework allows to estimate the performance of Amplify and Forward (AF) relay methods for both Channel State Information (CSI–) assisted relays, and fixed–gain relays. In particular, the contribution of this paper is twofold: i) first of all, by relying on the Gauss Quadrature Rule (GQR) representation of the Moment Generation Function (MGF) for a Log–Normal distribution, we develop accurate formulas for important performance indexes whose accuracy can be estimated a priori and just depends on GQR numerical integration errors; ii) then, in order to simplify the computational burden of the former framework for some system setups, we propose various approximations, which are based on the Improved Schwartz–Yeh (I–SY) method. We show with numerical and simulation results that the proposed approximations provide a good trade–off between accuracy and complexity for both Selection Combining (SC) and Maximal Ratio Combining (MRC) cooperative diversity methods
Entropy and Energy Detection-based Spectrum Sensing over F Composite Fading Channels
In this paper, we investigate the performance of energy detection-based
spectrum sensing over F composite fading channels. To this end, an analytical
expression for the average detection probability is firstly derived. This
expression is then extended to account for collaborative spectrum sensing,
square-law selection diversity reception and noise power uncertainty. The
corresponding receiver operating characteristics (ROC) are analyzed for
different conditions of the average signal-to-noise ratio (SNR), noise power
uncertainty, time-bandwidth product, multipath fading, shadowing, number of
diversity branches and number of collaborating users. It is shown that the
energy detection performance is sensitive to the severity of the multipath
fading and amount of shadowing, whereby even small variations in either of
these physical phenomena can significantly impact the detection probability. As
a figure of merit to evaluate the detection performance, the area under the ROC
curve (AUC) is derived and evaluated for different multipath fading and
shadowing conditions. Closed-form expressions for the Shannon entropy and cross
entropy are also formulated and assessed for different average SNR, multipath
fading and shadowing conditions. Then the relationship between the Shannon
entropy and ROC/AUC is examined where it is found that the average number of
bits required for encoding a signal becomes small (i.e., low Shannon entropy)
when the detection probability is high or when the AUC is large. The difference
between composite and traditional small-scale fading is emphasized by comparing
the cross entropy for Rayleigh and Nakagami-m fading. A validation of the
analytical results is provided through a careful comparison with the results of
some simulations.Comment: 30 pages, 11 figures, 1 table, Submitted to IEEE TCO
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