Next Article in Journal
A Novel Cross-Layer V2V Architecture for Direction-Aware Cooperative Collision Avoidance
Next Article in Special Issue
An On-Path Caching Scheme Based on the Expected Number of Copies in Information-Centric Networks
Previous Article in Journal
Area-Efficient Differential Fault Tolerance Encoding for Finite State Machines
Previous Article in Special Issue
Neighbor Aware Protocols for IoT Devices in Smart Cities—Overview, Challenges and Solutions
Open AccessArticle

Grant-Free Resource Allocation for NOMA V2X Uplink Systems Using a Genetic Algorithm Approach

Department of Computer Science, Hanyang University, Gyeonggi-do 15588, Korea
*
Author to whom correspondence should be addressed.
Electronics 2020, 9(7), 1111; https://doi.org/10.3390/electronics9071111
Received: 3 June 2020 / Revised: 3 July 2020 / Accepted: 5 July 2020 / Published: 8 July 2020
(This article belongs to the Special Issue Future Networks: New Advances and Challenges)
While NOMA-V2V (non-orthogonal multiple accesscan-vehicle-to-vehicle) effectively achieve massive connectivity requirements in 5G network systems, minimizing communication latency is a very crucial challenge. To address the latency problem, we propose a channel allocation method called hyper-fraction, which divides the road into many zones and allocates a channel to each zone. Then, a vehicle located within the corresponding zone uses the channel allocated to the zone. Hyper-fraction will allow the system to minimize communication latency between a user equipment (UE) and a base station (BS) caused by scheduling processes and consequentially reduce the overall latency of the system. In the simulation, a novel concept of genetic algorithm (GA) is utilized, called GA with continuous pool. It is an approach to enable conventional GA to solve optimization problems for continuous situations within much less computation, especially in situations where the elements in the system keep moving such as vehicular networks. As a result, GA with continuous pool is proven to be an effective heuristic method to improve throughput rate, as well as hyper-fraction improving the latency of NOMA V2V and vehicle-to-infrastructure (V2I) systems. View Full-Text
Keywords: NOMA; V2V; V2I; resource allocation; hyper-fraction; genetic algorithm; continuous pool NOMA; V2V; V2I; resource allocation; hyper-fraction; genetic algorithm; continuous pool
Show Figures

Figure 1

MDPI and ACS Style

Lee, S.; Kim, J.; Park, J.; Cho, S. Grant-Free Resource Allocation for NOMA V2X Uplink Systems Using a Genetic Algorithm Approach. Electronics 2020, 9, 1111.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop