Evaluating the Performance Maximization of Multichannel Allocation Mechanism under Interference Constraint for Hybrid Overlay/Underlay Cognitive Radio Networks with Energy Harvesting

Energy requirement is an important issue in wireless communications. The service life of wireless
sensors dramatically affects the reliability and performance of wireless networks. By harvesting
energy from ambient radio frequency (RF) signals, significant progress has been achieved in wireless
networks self-maintaining their lifecycles. Motivated by this and improved spectrum reuse by
combined use of overlay/underlay modes of cognitive radio networks (CRNs), this paper proposes a
novel multi-channel (m-channel) allocation performance maximization algorithm for low-power
mobiles. CRNs, called secondary transmitters (STs), can harvest energy from RF signals by nearby
active primary transmitters (PTs). In the proposed scheme, PTs and STs are distributed as
independent homogeneous Poisson point processes and contact their receivers at fixed distances.
Each PT contains a guard zone to protect its intended receiver from ST interference, and provides RF
energy to STs located in its harvesting zone. Spectrum demand has increased with the rapid increase
in usage of both wireless devices and wireless services. Prioritization of STs during opportunistic
allocation of channels is critical as properties like energy level and harvesting capability improve
channel distribution performance. A novel metric is proposed that prioritizes STs based on initial
energy levels, harvesting capability, and number of channels through which they can transmit. For
comparison, three algorithms were considered: a greedy mechanism for m-channel allocation of
hybrid CRNs without harvesting, the proposed m-channel allocation schemes based on maximum
independent sets (MIS), and the proposed metric of hybrid CRNs with harvesting capability. The
simulations show that the proposed m-channel allocation method based on MIS outperforms the
greedy algorithm. The proposed m-channel allocation using the proposed metric on hybrid CRNs with
energy harvesting ability produced the best performance of the three methods, proving the superiority
of the proposed algorithm. The results prove the superiority of the proposed mechanism with the
proposed metric.