Open AccessEfficient joint resource allocation for cognitive internet of vehicles networks based on asymmetric relay transmission
Author(s) -
Song Xiaoqin,
Wang Kuiyu,
Xu Lei,
Tan Yazhu,
Miao Juanjuan
Publication year - 2021
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/cmu2.12178
Subject(s) - relay , computer science , computer network , subcarrier , resource allocation , node (physics) , throughput , transmission (telecommunications) , fading , channel (broadcasting) , relay channel , cognitive radio , mathematical optimization , wireless , power (physics) , orthogonal frequency division multiplexing , telecommunications , mathematics , engineering , physics , structural engineering , quantum mechanics
In the internet of vehicles (IoV) networks, a direct connection from the source end to the destination end may not be established due to the fast vehicle speed, long distance between vehicles, variable vehicle density, serious channel fading etc. In this paper, a joint resource allocation (RA) in the relay‐aided IoV networks is modelled as a mixed binary integer non‐linear programming (MBINP), which maximises the throughput of cognitive IoV networks among different subcarriers and relays. To further reduce the computational complexity, a suboptimal scheme is presented. First, the appropriate relay and subcarrier pairs are obtained by averaging the power allocation among the cognitive sources and relays. Second, an alternative optimisation mechanism is proposed to the power allocation. Simulation results show that, different from the symmetric time‐slot relay transmission, the asymmetric one can significantly increase the degree of freedom for transmission. Therefore, it is more robust to the impact of the relay node location on the throughput. Moreover, the proposed suboptimal RA algorithm not only can obtain the system capacity close to the optimal one, but also can reduce the computational complexity. At the same time, unacceptable degradation caused by severe channel fading is avoided.