Radio resource allocation improvements in cognitive radio sensor network for smart grid: Investigative study and solutions

Abstract

Background: A cognitive radio sensor network (CRSN)-based Smart Grid (SG) is a new paradigm for a modern SG. It is totally different from the traditional power grid and conventional SG. Currently, an SG uses a static resource allocation technique to allocate resources to sensor nodes in the SG network. Static resource allocation is not efficient due to the heterogeneous nature of CRSN-based SGs. Hence, an appropriate mechanism such as dynamic radio resource allocation (RRA) is required for efficient resource allocation in CRSNs for SGs. Objective: The objective of this paper is to investigate and propose suitable dynamic RRA for efficient resource allocation in CRSNs-based SGs. This involves a proposal for appropriate strategy that will address poor throughput and excessive errors in resource allocation. Methods: In this paper, the dynamic RRA approach is used to allocate resources such as frequency, energy, channels and spectrum to the sensor nodes. This is because of the heterogeneity in a CRSN which differs for SG applications. The dynamic RRA approach is based on optimization of resource allocation criteria such as energy efficiency, throughput maximization, QoS guarantee, etc. The methods include an introduced model called “guaranteed network connectivity channel allocation for throughput maximization” (GNC-TM). Also used, is an optimal spectrum-band determination in RRA for improved throughput. Results: The results show that the model outperforms the existing protocol of channel allocation in terms of throughput and error probability. Conclusion: This study explores RRA schemes for CRSNs for SGs. The paper proposed a GNC-TM model, including demonstration of suitable spectrum band operation in CRSNs for SGs.