2,766 research outputs found
When Channel Bonding is Beneficial for Opportunistic Spectrum Access Networks
Transmission over multiple frequency bands combined into one logical channel
speeds up data transfer for wireless networks. On the other hand, the
allocation of multiple channels to a single user decreases the probability of
finding a free logical channel for new connections, which may result in a
network-wide throughput loss. While this relationship has been studied
experimentally, especially in the WLAN configuration, little is known on how to
analytically model such phenomena. With the advent of Opportunistic Spectrum
Access (OSA) networks, it is even more important to understand the
circumstances in which it is beneficial to bond channels occupied by primary
users with dynamic duty cycle patterns. In this paper we propose an analytical
framework which allows the investigation of the average channel throughput at
the medium access control layer for OSA networks with channel bonding enabled.
We show that channel bonding is generally beneficial, though the extent of the
benefits depend on the features of the OSA network, including OSA network size
and the total number of channels available for bonding. In addition, we show
that performance benefits can be realized by adaptively changing the number of
bonded channels depending on network conditions. Finally, we evaluate channel
bonding considering physical layer constraints, i.e. throughput reduction
compared to the theoretical throughput of a single virtual channel due to a
transmission power limit for any bonding size.Comment: accepted to IEEE Transactions on Wireless Communication
Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining
The deployment of underlay small base stations (SBSs) is expected to
significantly boost the spectrum efficiency and the coverage of next-generation
cellular networks. However, the coexistence of SBSs underlaid to an existing
macro-cellular network faces important challenges, notably in terms of spectrum
sharing and interference management. In this paper, we propose a novel
game-theoretic model that enables the SBSs to optimize their transmission rates
by making decisions on the resource occupation jointly in the frequency and
spatial domains. This procedure, known as interference draining, is performed
among cooperative SBSs and allows to drastically reduce the interference
experienced by both macro- and small cell users. At the macrocell side, we
consider a modified water-filling policy for the power allocation that allows
each macrocell user (MUE) to focus the transmissions on the degrees of freedom
over which the MUE experiences the best channel and interference conditions.
This approach not only represents an effective way to decrease the received
interference at the MUEs but also grants the SBSs tier additional transmission
opportunities and allows for a more agile interference management. Simulation
results show that the proposed approach yields significant gains at both
macrocell and small cell tiers, in terms of average achievable rate per user,
reaching up to 37%, relative to the non-cooperative case, for a network with
150 MUEs and 200 SBSs
Listen-and-Talk: Full-duplex Cognitive Radio Networks
In traditional cognitive radio networks, secondary users (SUs) typically
access the spectrum of primary users (PUs) by a two-stage "listen-before-talk"
(LBT) protocol, i.e., SUs sense the spectrum holes in the first stage before
transmit in the second stage. In this paper, we propose a novel
"listen-and-talk" (LAT) protocol with the help of the full-duplex (FD)
technique that allows SUs to simultaneously sense and access the vacant
spectrum. Analysis of sensing performance and SU's throughput are given for the
proposed LAT protocol. And we find that due to self-interference caused by FD,
increasing transmitting power of SUs does not always benefit to SU's
throughput, which implies the existence of a power-throughput tradeoff.
Besides, though the LAT protocol suffers from self-interference, it allows
longer transmission time, while the performance of the traditional LBT protocol
is limited by channel spatial correction and relatively shorter transmission
period. To this end, we also present an adaptive scheme to improve SUs'
throughput by switching between the LAT and LBT protocols. Numerical results
are provided to verify the proposed methods and the theoretical results.Comment: in proceeding of IEEE Globecom 201
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
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