Low-complexity timer-based multi-relay selection and sequential power allocation of cooperative cognitive radio networks for future Internet of things

Md Arifur Rahman,Insoo Koo,Youngdoo Lee

doi:10.1177/1550147716671254

Md Arifur Rahman, Insoo Koo + Show 1 more

Open Access

https://doi.org/10.1177/1550147716671254

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Abstract

Cooperative cognitive radio networks use cooperative relays to forward signal from the source to the destination. In cooperative cognitive radio networks, the transmission power of each relay is limited by the interference constraint of the primary user receiver. Thus, it is essential to optimize power allocation and multi-relay selection jointly to maximize the secondary system throughput. Optimizing multi-relay selection and power allocation requires an exhaustive search for all possible relay combinations, since this approach uses a large amount of valuable resources and entails high computational complexity. A suboptimal solution for power allocation may reduce the computational complexity but still involves high implementation complexity. Thus, for an efficient utilization of resources to support the applicability of cognitive radio for the Internet of things, we propose a low-complexity timer-based multi-relay selection that determines a forwarding relay set before the source begins to transmit its data. This allows the source to know the instantaneous channel state information of the relays, which helps the source to assign appropriate transmission power to the relays. By simulation, we show that the proposed scheme achieves near-optimal secondary system throughput performance to the optimal multi-relay selection as well as provides a significant secondary system throughput gain when compared to conventional and random relay selection scheme with equal power allocation.

Highlights

Cognitive radio (CR) is a wireless technology with promise to resolve the growing scarcity problem of crucial electromagnetic spectrum resources by adaptively changing its transmitter parameters based on the interaction with the environment
In order to support the applicability of CR for future Internet of things (IoT), cooperative cognitive radio networks (CCRNs) is a promising approach which can reduce the interference of the primary users (PUs) receiver and energy consumption in transmission
To prevent unnecessary wastage of valuable spectrum resources, joint relay selection and power allocation in CCRNs were presented in Yu et al.,[8] where the secondary users (SUs) relays are operated on amplify-and-forward (AF) mode, and optimal power allocation (OPA) and suboptimal power allocation schemes were derived for secondary system throughput maximization under a PU receiver interference threshold

Summary

Introduction

Cognitive radio (CR) is a wireless technology with promise to resolve the growing scarcity problem of crucial electromagnetic spectrum resources by adaptively changing its transmitter parameters based on the interaction with the environment. In order to support the applicability of CR for future IoT, cooperative cognitive radio networks (CCRNs) is a promising approach which can reduce the interference of the PU receiver and energy consumption in transmission. To prevent unnecessary wastage of valuable spectrum resources, joint relay selection and power allocation in CCRNs were presented in Yu et al.,[8] where the SU relays are operated on amplify-and-forward (AF) mode, and optimal power allocation (OPA) and suboptimal power allocation schemes were derived for secondary system throughput maximization under a PU receiver interference threshold. We propose a scheme that jointly uses a lower complexity timer-based MRS with sequential power allocation to achieve efficient utilization of resource in underlay CCRNs. In this article, we propose a scheme to maximize the secondary system throughput using a timer-based MRS with low IC, which determines a forwarding relay set by the SU source via handshaking mechanism between the SU source and the surrounding SU relays. The system model and description are introduced in sections ‘‘System model’’ and ‘‘System description.’’ The proposed timer-based MRS and the sequential power assignment algorithm and the energy consumption analysis are analyzed in sections ‘‘The proposed timerbased MRS,’’‘‘The proposed sequential power assignment,’’ and ‘‘Energy consumption analysis.’’ The simulation results are given in section ‘‘Simulation results,’’ and the article’s conclusions are provided in section ‘‘Conclusion.’’

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Conclusion