Performance Comparison of Cognitive Radio Sensor Networks for Industrial IoT With Different Deployment Patterns

Abstract

Square lattice (SL), triangle lattice (TL), and hexagon lattice (HL) are widely used regular deployment patterns for industrial Internet of Things (IoT). However, the performance of cognitive-radio-based access with these three deployment patterns has not been explored yet. This paper first designs a transmission scheduling method named cognitive access for regular topology (CART) in cognitive radio sensor networks (CRSNs) with minimal occupation of channels and high transmission efficiency. CART consists of a timeslot-and-channel allocation scheme, a cooperative spectrum-sensing scheme, and a scheme for reporting spectrum-sensing results (SSRs) in SL, TL, and HL. This paper also analyzes CART’s cooperative spectrum-sensing performance, reception bandwidth, and transmission delay for different transmission interference range and coverage patterns. Based on numerical analysis and simulation, this paper makes comparison between CART and optimal transmission scheduling method for single channel, and that among these three deployment patterns. Results show the following insights for efficient deployment of CRSN: 1) TL yields the optimal cooperative spectrum-sensing performance among three patterns by data fusion rule of 3-out-of-7; 2) under the same conditions and area for deployment, SL provides the optimal reception bandwidth; 3) SL and TL lead to low transmission delay for critical complete coverage; 4) SL leads to the lowest transmission delay for critical multiple coverage; 5) the false alarm (FA) probability of individual node has little influence on transmission delay, while the probability of primary user’s (PU) occurrence has noticeably influence on it; and 6) increasing the ratio of transmission timeslot to spectrum-sensing timeslot may decrease transmission delay