Performance Of Cooperative Cognitive Radio Network Research Articles

Performance Analysis of Decision/Data Fusion-Aided Cooperative Cognitive Radio Network Over Generalized Fading Channel

In this paper, the analytical performance evaluation of the cooperative cognitive radio network (CCRN) with hard-decision and soft-data fusions is investigated in the presence of noisy and generalized $\kappa -\mu$ fading channel. The novel expressions to calculate detection probability of CCRN subject to $\kappa -\mu$ fading and fusion are derived. The analysis of various fusions is evaluated and compared. The performance of CCRN, considering an erroneous sensing and reporting channels, is studied. Also, an optimal threshold subject to fusion scheme is computed. The CCRN performance is evaluated through miss detection probability and total error rate, considering the significant impact of channel and network parameters. Finally, Monte Carlo simulation is performed to validate the derived expressions.

Throughput analysis of cooperative cognitive radio network over generalized κ–μ and η–μ fading channels

In this paper, we propose a cooperative cognitive radio network (CCRN) based on energy detection and hard-decision fusion. The performance characteristics are investigated analytically in the presence of noise plus generalized fading channels. In particular, scenarios with $$\kappa$$ – $$\mu$$ and $$\eta$$ – $$\mu$$ fading channels affecting the sensing channels are considered. More precisely, Each cognitive radio user (CRU) relies on an energy detector (ED). The signal from the primary user (PU), received by a CRU, is fed to the ED, and the energy of signal is used to make a local decision. At the fusion center (FC), the decisions received at the FC are fused, using hard-decision fusion, to obtain a final decision on the status of the PU. The performance of CCRN, through total error rate and throughput is evaluated considering the impact of relevant network parameters. Towards that, first we derive the novel mathematical expressions for probability of detection, subject to generalized fading. Also, Monte Carlo simulation is performed to validate the derived expressions. Next, the analytical frame works based on derived expression for evaluating total error rate and throughput performances for any network and channel conditions are developed. Further, the impact of an erroneous sensing (S) and reporting (R) channels on overall performance of CCRN is also investigated. Finally, the impact of the generalized fading parameters, the signal-to-noise ratio, the time-bandwidth product, the number of CRUs, the detection threshold, and the channel error probability on the total error rate and throughput performances is investigated.

Auction-based resource allocation for cooperative cognitive radio networks

Cooperative cognitive radio network (CCRN) is a promising paradigm to increase spectrum utilization and exploit spatial diversity. The allocation of two coupled resources, i.e. spectrum and secondary relay nodes, plays a fundamental role in the performance of CCRNs. However, previous studies either lack of incentives for both primary users (PUs) and relay nodes to participate in or consider spectrum auction and relay auction separately. In this paper, we consider a static cooperative cognitive radio network scenario with several PUs and multiple secondary user coteries, each of which consists of a set of secondary users who are interested in sharing the same secondary relay node. We model the problem of joint spectrum allocation and relay allocation as a hierarchical auction and propose two auction schemes, i.e. TERA and UERA. TERA is the first Truthful auction mechanism for Efficient Resource Allocation in CCRNs which satisfies critical economic properties. UERA is an approximate truthful scheme which adopts a uniform price for fairness in the same secondary user coteries. Furthermore, we theoretically prove TERA and UERA can achieve near-optimal revenue. Finally, extensive simulation results show that TERA and UERA are efficient and able to improve the utility of PUs and relay nodes significantly.