27,599 research outputs found
Throughput Analysis of Primary and Secondary Networks in a Shared IEEE 802.11 System
In this paper, we analyze the coexistence of a primary and a secondary
(cognitive) network when both networks use the IEEE 802.11 based distributed
coordination function for medium access control. Specifically, we consider the
problem of channel capture by a secondary network that uses spectrum sensing to
determine the availability of the channel, and its impact on the primary
throughput. We integrate the notion of transmission slots in Bianchi's Markov
model with the physical time slots, to derive the transmission probability of
the secondary network as a function of its scan duration. This is used to
obtain analytical expressions for the throughput achievable by the primary and
secondary networks. Our analysis considers both saturated and unsaturated
networks. By performing a numerical search, the secondary network parameters
are selected to maximize its throughput for a given level of protection of the
primary network throughput. The theoretical expressions are validated using
extensive simulations carried out in the Network Simulator 2. Our results
provide critical insights into the performance and robustness of different
schemes for medium access by the secondary network. In particular, we find that
the channel captures by the secondary network does not significantly impact the
primary throughput, and that simply increasing the secondary contention window
size is only marginally inferior to silent-period based methods in terms of its
throughput performance.Comment: To appear in IEEE Transactions on Wireless Communication
Surrogate modeling based cognitive decision engine for optimization of WLAN performance
Due to the rapid growth of wireless networks and the dearth of the electromagnetic spectrum, more interference is imposed to the wireless terminals which constrains their performance. In order to mitigate such performance degradation, this paper proposes a novel experimentally verified surrogate model based cognitive decision engine which aims at performance optimization of IEEE 802.11 links. The surrogate model takes the current state and configuration of the network as input and makes a prediction of the QoS parameter that would assist the decision engine to steer the network towards the optimal configuration. The decision engine was applied in two realistic interference scenarios where in both cases, utilization of the cognitive decision engine significantly outperformed the case where the decision engine was not deployed
On Modeling Coverage and Rate of Random Cellular Networks under Generic Channel Fading
In this paper we provide an analytic framework for computing the expected
downlink coverage probability, and the associated data rate of cellular
networks, where base stations are distributed in a random manner. The provided
expressions are in computable integral forms that accommodate generic channel
fading conditions. We develop these expressions by modelling the cellular
interference using stochastic geometry analysis, then we employ them for
comparing the coverage resulting from various channel fading conditions namely
Rayleigh and Rician fading, in addition to the fading-less channel.
Furthermore, we expand the work to accommodate the effects of random frequency
reuse on the cellular coverage and rate. Monte-Carlo simulations are conducted
to validate the theoretical analysis, where the results show a very close
match
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