In vehicle-to-vehicle (V2V) communication, link reliability has been regarded as an important performance metric, especially for safety-critical broadcast services. In this paper, we analyze the link reliability of the centralized mode (Mode 3) for long-term evolution (LTE)-based V2V (LTE-V2V) from the PHY/MAC perspectives. Moreover, we derive the statistical distribution of the interference distance and interference to noise ratio (INR) for LTE-V2V. Based on this analytical framework, we propose a resource size control (RSC) method for improving link reliability. The proposed RSC adapts the resource size according to the macroscopic network parameters such as vehicle density, communication range, and message size. Numerical results show that the proposed method improves link reliability compared with the fixed resource size setting in a highway scenario. Moreover, it is observed that larger-sized resources are preferred when the vehicle density decreases, the message size increases, or the communication range decreases.
Bibliographical noteFunding Information:
Manuscript received February 19, 2018; revised June 29, 2018 and September 5, 2018; accepted October 12, 2018. Date of publication November 6, 2018; date of current version January 15, 2019. This work was supported in part by the National Research Foundation of Korea Grant funded by the Korea government Grant NRF-2018R1A2A1A05021029 and in part by the Institute for Information and communications Technology Promotion Grant funded by the Korea government (2016-0-00181, Development on the core technologies of transmission, modulation and coding with low-power and low-complexity for massive connectivity in the IoT environment). The review of this paper was coordinated by D. Matolak. (Corresponding author: Daesik Hong.) Y. Park is with the Autonomous Machine Laboratory, AI Center, Sam-sung Research, Samsung Electronics Co., Seoul 06765, South Korea (e-mail:, firstname.lastname@example.org).
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All Science Journal Classification (ASJC) codes
- Automotive Engineering
- Aerospace Engineering
- Electrical and Electronic Engineering
- Applied Mathematics