24,262 research outputs found
Optimizing cooperative cognitive radio networks with opportunistic access
Optimal resource allocation for cooperative cognitive radio networks with opportunistic access to the licensed spectrum is studied. Resource allocation is based on minimizing the symbol error rate at the receiver. Both the cases of all-participate relaying and selective relaying are considered. The objective function is derived and the constraints are detailed for both scenarios. It is then shown that the objective functions and the constraints are nonlinear and nonconvex functions of the parameters of interest, that is, source and relay powers, symbol time, and sensing time. Therefore, it is difficult to obtain closed-form solutions for the optimal resource allocation. The optimization problem is then solved using numerical techniques. Numerical results show that the all-participate system provides better performance than its selection counterpart, at the cost of greater resources
Distributed Cooperative Sensing in Cognitive Radio Networks: An Overlapping Coalition Formation Approach
Cooperative spectrum sensing has been shown to yield a significant
performance improvement in cognitive radio networks. In this paper, we consider
distributed cooperative sensing (DCS) in which secondary users (SUs) exchange
data with one another instead of reporting to a common fusion center. In most
existing DCS algorithms, the SUs are grouped into disjoint cooperative groups
or coalitions, and within each coalition the local sensing data is exchanged.
However, these schemes do not account for the possibility that an SU can be
involved in multiple cooperative coalitions thus forming overlapping
coalitions. Here, we address this problem using novel techniques from a class
of cooperative games, known as overlapping coalition formation games, and based
on the game model, we propose a distributed DCS algorithm in which the SUs
self-organize into a desirable network structure with overlapping coalitions.
Simulation results show that the proposed overlapping algorithm yields
significant performance improvements, decreasing the total error probability up
to 25% in the Q_m+Q_f criterion, the missed detection probability up to 20% in
the Q_m/Q_f criterion, the overhead up to 80%, and the total report number up
to 10%, compared with the state-of-the-art non-overlapping algorithm
Green Cellular Networks: A Survey, Some Research Issues and Challenges
Energy efficiency in cellular networks is a growing concern for cellular
operators to not only maintain profitability, but also to reduce the overall
environment effects. This emerging trend of achieving energy efficiency in
cellular networks is motivating the standardization authorities and network
operators to continuously explore future technologies in order to bring
improvements in the entire network infrastructure. In this article, we present
a brief survey of methods to improve the power efficiency of cellular networks,
explore some research issues and challenges and suggest some techniques to
enable an energy efficient or "green" cellular network. Since base stations
consume a maximum portion of the total energy used in a cellular system, we
will first provide a comprehensive survey on techniques to obtain energy
savings in base stations. Next, we discuss how heterogeneous network deployment
based on micro, pico and femto-cells can be used to achieve this goal. Since
cognitive radio and cooperative relaying are undisputed future technologies in
this regard, we propose a research vision to make these technologies more
energy efficient. Lastly, we explore some broader perspectives in realizing a
"green" cellular network technologyComment: 16 pages, 5 figures, 2 table
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