Abstract
Currently, there is a growing demand for the use of communication network bandwidth for the Internet of Things (IoT) within the cyber-physical-social system (CPSS), while needing progressively more powerful technologies for using scarce spectrum resources. Then, cognitive radio networks (CRNs) as one of those important solutions mentioned above, are used to achieve IoT effectively. Generally, dynamic resource allocation plays a crucial role in the design of CRN-aided IoT systems. Aiming at this issue, orthogonal frequency division multiplexing (OFDM) has been identified as one of the successful technologies, which works with a multi-carrier parallel radio transmission strategy. In this article, through the use of swarm intelligence paradigm, a solution approach is accordingly proposed by employing an efficient Jaya algorithm, called PA-Jaya, to deal with the power allocation problem in cognitive OFDM radio networks for IoT. Because of the algorithm-specific parameter-free feature in the proposed PA-Jaya algorithm, a satisfactory computational performance could be achieved in the handling of this problem. For this optimization problem with some constraints, the simulation results show that compared with some popular algorithms, the efficiency of spectrum utilization could be further improved by using PA-Jaya algorithm with faster convergence speed, while maximizing the total transmission rate.
Highlights
With the rapid development of the Internet of Things (IoT) within the cyber-physical-social system (CPSS), there is an ever-increasing demand for communication network bandwidth for achieving high-performance applications which enrich and broaden the interactions and connections in the cyber-physical-social world
In this article, motivated by our previous work in ref. [34], the power resource allocation in the downlink of a cognitive radio networks (CRNs)-aided IoT system is modeled as a constrained optimization problem, and a solution method is presented by incorporating the proposed Jaya algorithm into the cognitive orthogonal frequency division multiplexing (OFDM) radio network model to achieve a satisfactory power allocation result
Based on the practical scenario discussed above for the basic OFDM power allocation model in CRNs, instead of considering the primary interference constraints, we considered the fairness of channel resource allocation among secondary users
Summary
With the rapid development of the Internet of Things (IoT) within the cyber-physical-social system (CPSS), there is an ever-increasing demand for communication network bandwidth for achieving high-performance applications which enrich and broaden the interactions and connections in the cyber-physical-social world. In the CRN-aided IoT, the secondary user (i.e., cognitive user) may selectively access the idle frequency band of the primary user (i.e., authorized user) to improve the utilization of the licensed spectrum. [34], the power resource allocation in the downlink of a CRN-aided IoT system is modeled as a constrained optimization problem, and a solution method is presented by incorporating the proposed Jaya algorithm into the cognitive OFDM radio network model to achieve a satisfactory power allocation result. The simulation results show that compared with other popular optimization algorithms, our PA-Jaya algorithm can achieve a better power allocation with faster converge speed, which means that it can improve the efficiency of spectrum utilization more effectively in IoT.
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