Premium
Throughput optimization using simultaneous sensing and transmission in energy harvesting cognitive radio networks
Author(s) -
Moradi Alieh,
Farrokhi Hamid,
Ghazizade Reza
Publication year - 2019
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.3850
Subject(s) - cognitive radio , computer science , throughput , energy harvesting , underlay , network packet , transmission (telecommunications) , transmitter , energy consumption , energy (signal processing) , interference (communication) , computer network , data transmission , optimization problem , real time computing , wireless , telecommunications , algorithm , signal to noise ratio (imaging) , electrical engineering , channel (broadcasting) , statistics , mathematics , engineering
Summary A three‐dimensional continuous‐time Markov model is proposed for an energy harvesting cognitive radio system, where each secondary user (SU) harvests energy from the ambient environment and attempts to transmit data packets on spectrum holes in an infinite queuing buffer. Unlike most previous works, the SU can perform spectrum sensing, data transmission, and energy harvesting simultaneously. We determine active probability of the SU transmitter, where the average energy consumption for both spectrum sensing and data transmission should not exceed the amount of harvested energy. Then, we formulate achievable throughput of secondary network as a convex optimization problem under average transmit and interference energy constraints. The optimal pair of controlled energy harvesting rate and data packet rate is derived for proposed model. Results indicate that no trade‐off is available among harvesting, sensing/receiving, and transmitting. The SU capability for self‐interference cancelation affects the maximum throughput. We develop this work under hybrid channels including overlay and underlay cases and propose a hybrid solution to achieve the maximum throughput. Simulation results verify that our proposed strategy outperforms the efficiency of the secondary network compared to the previous works.