PRACB: A Novel Channel Bonding Algorithm for Cognitive Radio Sensor Networks

Wireless sensor networks (WSNs) can utilize the unlicensed industrial, scientific, and medical (ISM) band to communicate the sensed data. The ISM band has been already saturated due to the overlaid deployment of WSNs. To solve this problem, WSNs have been powered up by cognitive radio (CR) capability. By using CR capability, WSNs can utilize the spectrum holes opportunistically. The sensor nodes, which need large bandwidth to transmit their sensed data from source to destination require some scheme, which should be able to provide them a wide band channel whenever required. Channel bonding (CB) is a technique through which multiple contiguous channels can be combined to form a single wide band channel. By using CB technique, CR-based WSN nodes attempt to find and combine contiguous channels to avail larger bandwidth. In this paper, we show that by increasing the number of channels, the probability of finding contiguous channels decreases. Moreover, we then propose a primary-radio (PR) user-activity-aware CB algorithm and compare it with three state-of-the-art schemes: SWA, KNOWS, and AGILE. It has been demonstrated through extensive NS-2 simulations that intelligent CB decisions can reduce harmful interference to PR nodes. We find that CB in CR sensor networks attempts to provide greater bandwidth and utilizes the spectrum effectively.