@Article{cmc.2020.09908,
AUTHOR = {Xiaoli He, Hong Jiang, Yu Song, Muhammad Owais},
TITLE = {Power Control and Routing Selection for Throughput  Maximization in Energy Harvesting Cognitive Radio Networks},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {63},
YEAR = {2020},
NUMBER = {3},
PAGES = {1273--1296},
URL = {http://www.techscience.com/cmc/v63n3/38875},
ISSN = {1546-2226},
ABSTRACT = {This paper investigates the power control and routing problem in the
communication process of an energy harvesting (EH) multi-hop cognitive radio network 
(CRN). The secondary user (SU) nodes (i.e., source node and relay nodes) harvest energy 
from the environment and use the energy exclusively for transmitting data. The SU nodes 
(i.e., relay nodes) on the path, store and forward the received data to the destination node. 
We consider a real world scenario where the EH-SU node has only local causal 
knowledge, i.e., at any time, each EH-SU node only has knowledge of its own EH 
process, channel state and currently received data. In order to study the power and routing 
issues, an optimization problem that maximizes path throughput considering quality of 
service (QoS) and available energy constraints is proposed. To solve this optimization 
problem, we propose a hybrid game theory routing and power control algorithm 
(HGRPC). The EH-SU nodes on the same path cooperate with each other, but EH-SU 
nodes on the different paths compete with each other. By selecting the best next hop node, 
we find the best strategy that can maximize throughput. In addition, we have established 
four steps to achieve routing, i.e., route discovery, route selection, route reply, and route 
maintenance. Compared with the direct transmission, HGRPC has advantages in longer 
distances and higher hop counts. The algorithm generates more energy, reduces energy 
consumption and increases predictable residual energy. In particular, the time complexity 
of HGRPC is analyzed and its convergence is proved. In simulation experiments, the 
performance (i.e., throughput and bit error rate (BER)) of HGRPC is evaluated. Finally, 
experimental results show that HGRPC has higher throughput, longer network life, less 
latency, and lower energy consumption.},
DOI = {10.32604/cmc.2020.09908}
}