2,585 research outputs found
Coalition Formation Game for Cooperative Cognitive Radio Using Gibbs Sampling
This paper considers a cognitive radio network in which each secondary user
selects a primary user to assist in order to get a chance of accessing the
primary user channel. Thus, each group of secondary users assisting the same
primary user forms a coaltion. Within each coalition, sequential relaying is
employed, and a relay ordering algorithm is used to make use of the relays in
an efficient manner. It is required then to find the optimal sets of secondary
users assisting each primary user such that the sum of their rates is
maximized. The problem is formulated as a coalition formation game, and a Gibbs
Sampling based algorithm is used to find the optimal coalition structure.Comment: 7 pages, 2 figure
Directional Relays for Multi-Hop Cooperative Cognitive Radio Networks
In this paper, we investigate power allocation and beamforming in a relay assisted cognitive radio (CR) network. Our objective is to maximize the performance of the CR network while limiting interference in the direction of the primary users (PUs). In order to achieve these goals, we first consider joint power allocation and beamforming for cognitive nodes in direct links. Then, we propose an optimal power allocation strategy for relay nodes in indirect transmissions. Unlike the conventional cooperative relaying networks, the applied relays are equipped with directional antennas to further reduce the interference to PUs and meet the CR network requirements. The proposed approach employs genetic algorithm (GA) to solve the optimization problems. Numerical simulation results illustrate the quality of service (QoS) satisfaction in both primary and secondary networks. These results also show that notable improvements are achieved in the system performance if the conventional omni-directional relays are replaced with directional ones
Joint Spectrum Sensing and Resource Allocation for OFDM-based Transmission with a Cognitive Relay
In this paper, we investigate the joint spectrum sensing and resource
allocation problem to maximize throughput capacity of an OFDM-based cognitive
radio link with a cognitive relay. By applying a cognitive relay that uses
decode and forward (D&F), we achieve more reliable communications, generating
less interference (by needing less transmit power) and more diversity gain. In
order to account for imperfections in spectrum sensing, the proposed schemes
jointly modify energy detector thresholds and allocates transmit powers to all
cognitive radio (CR) subcarriers, while simultaneously assigning subcarrier
pairs for secondary users (SU) and the cognitive relay. This problem is cast as
a constrained optimization problem with constraints on (1) interference
introduced by the SU and the cognitive relay to the PUs; (2) miss-detection and
false alarm probabilities and (3) subcarrier pairing for transmission on the SU
transmitter and the cognitive relay and (4) minimum Quality of Service (QoS)
for each CR subcarrier. We propose one optimal and two sub-optimal schemes all
of which are compared to other schemes in the literature. Simulation results
show that the proposed schemes achieve significantly higher throughput than
other schemes in the literature for different relay situations.Comment: EAI Endorsed Transactions on Wireless Spectrum 14(1): e4 Published
13th Apr 201
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
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