Abstract
With the significant advantages of 5G technique such as higher transmission rate and lower transmission delay, it is more in line with the requirements of the connected vehicle scenario. In addition, the serial interference cancellation (SIC) technology in 5G technology can further improve the communication quality compared to a single one-to-one multiplexing method. Taking the dynamic communication characteristics of Internet of Vehicles into consideration, the robust optimization problem is formulated, which attempts to maximization the total throughput of vehicle users under the changing channel gains. The channel uncertainty is formulated as probability constraints, and they are transformed to the deterministic form to achieve a convex optimization problem. And the Hungarian algorithm is introduced to allocate the available channels to the V2V pairs. With the proposed joint resource allocation algorithm, the maximum throughput can be obtained with the lower algorithm complexity. Also, the robustness against the changing channel gains is guaranteed and the outage probability of users is kept below the pre-given outage threshold.
Highlights
Three available communication modes are suggested for Internet of Vehicles (IoV), including traditional cellular network mode, Ad-hoc mode and device-to-device (D2D) mode [2]–[4]
Considering the the short channel state information (CSI) feedback interval included in channel model (1), the signal-to-interference-plus-noise ratio (SINR) of ith cellular users equipment (CUE) in the uplink is expressed as follows
By increasing the number of CUEs and vehicle pairs, the scalability of the algorithm is validated, and the proposed algorithm is compared with two existing power allocation strategies, one is the multiple objective optimization algorithm proposed in [30], which is named as MOPA, the other is energy-efficiency maximization algorithm proposed in [26], which is named as EEMA
Summary
Three available communication modes are suggested for IoV, including traditional cellular network mode, Ad-hoc mode and device-to-device (D2D) mode [2]–[4]. In [22], with the assumption that the channel gain is only related to slow fading, the energy efficiency resource allocation problem is studied based on matching and interference management. While maximizing the objective function, the communication quality of the V2V communication links are guaranteed, which is included in the constraints of formulated optimization problem Both the CUE performance and the quality of V2V users are considered. The effects of vehicle mobility and the information delay transmission time on the channel gains are considered, that are included in the description of the channel model of the vehicle communication link. Simulation results validate the advantages in aspect of sum rate improvement and robustness against the uncertain channel gains
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