2,744 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
A Pricing-Based Cooperative Spectrum Sharing Stackelberg Game
We consider the problem of cooperative spectrum sharing among a primary user
(PU) and multiple secondary users (SUs) under quality of service (QoS)
constraints. The SUs network is controlled by the PU through a relay which gets
a revenue for amplifying and forwarding the SUs signals to their respective
destinations. The relay charges each SU a different price depending on its
received signal-to-interference and-noise ratio (SINR). The relay can control
the SUs network and maximize any desired PU utility function. The PU utility
function represents its rate, which is affected by the SUs access, and its
gained revenue to allow the access of the SUs. The SU network can be formulated
as a game in which each SU wants to maximize its utility function; the problem
is formulated as a Stackelberg game. Finally, the problem of maximizing the
primary utility function is solved through three different approaches, namely,
the optimal, the heuristic and the suboptimal algorithms.Comment: 7 pages. IEEE, WiOpt 201
Spectrum Sharing in RF-Powered Cognitive Radio Networks using Game Theory
We investigate the spectrum sharing problem of a radio frequency (RF)-powered
cognitive radio network, where a multi-antenna secondary user (SU) harvests
energy from RF signals radiated by a primary user (PU) to boost its available
energy before information transmission. In this paper, we consider that both
the PU and SU are rational and self-interested. Based on whether the SU helps
forward the PU's information, we develop two different operation modes for the
considered network, termed as non-cooperative and cooperative modes. In the
non-cooperative mode, the SU harvests energy from the PU and then use its
available energy to transmit its own information without generating any
interference to the primary link. In the cooperative mode, the PU employs the
SU to relay its information by providing monetary incentives and the SU splits
its energy for forwarding the PU's information as well as transmitting its own
information. Optimization problems are respectively formulated for both
operation modes, which constitute a Stackelberg game with the PU as a leader
and the SU as a follower. We analyze the Stackelberg game by deriving solutions
to the optimization problems and the Stackelberg Equilibrium (SE) is
subsequently obtained. Simulation results show that the performance of the
Stackelberg game can approach that of the centralized optimization scheme when
the distance between the SU and its receiver is large enough.Comment: Presented at PIMRC'1
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