Interference Hypergraph-Based 3D Matching Resource Allocation Protocol for NOMA-V2X Networks

Wang, Baoji; Zhang, Rongqing; Chen, Chen; Cheng, Xiang; Yang, Liuqing

doi:10.1109/icc.2019.8761579

Cited by 23 publications

(32 citation statements)

References 17 publications

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“…The authors' system model was composed of a single BS and multiple vehicle clusters, and the objective was to enhance the minimum achievable rate of the vehicles. To mitigate interference and increase the sum rate, the authors of [11] investigated a resource allocation problem in deviceto-device (D2D)-enhance V2X NOMA networks. Moreover, they proposed a greedy algorithm based on a hyper-graph three-dimension (3D) matching algorithm to solve the interference mitigation resource management problem.…”

Section: A Recent Workmentioning

confidence: 99%

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Multiobjective Optimization of Uplink NOMA-Enabled Vehicle-to-Infrastructure Communication

et al. 2020

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Vehicular communication is gradually evolving from the rudimentary data exchange techniques to innovative, efficient, and large-scale communication platform. The future vehicular networks aim to offer new services and achieve massive connectivity with the aid of advanced wireless communication techniques. In this regard, one of the emerging paradigms is non-orthogonal multiple access (NOMA) which holds the promise to meet the resource-intensive demands of future networks. Due to this reason, the applications of NOMA are being investigated by the researcher of academia and industry alike. This article aims to build on the state-of-the-art by providing a novel multiobjective optimization framework for vehicle-to-infrastructure (V2I) communications. Specifically, this work aims to improve upon the sum-rate and energy efficiency of uplink NOMA-enabled V2I communications. The formulated problem is based on the tradeoff between sum-rate and total transmit power while maintaining the quality of service (QoS) requirements of the network. To provide a reliable solution, a multiobjective optimization framework has been proposed by applying the weighted-sum method and handle joint metrics of sum-rate maximization and total transmit power minimization. Extensive simulations have been performed to validate the superiority of the proposed framework against conventional benchmark techniques. The results clearly indicate that the proposed framework is feasible for NOMA-enabled V2I communication and can be scaled up for practical implementation. INDEX TERMS Non-orthogonal multiple access, multiobjective optimization, QoS, vehicular communication.

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Section: A Recent Workmentioning

confidence: 99%

“…where itr is the iteration index, and ω is the step size. In each iteration, λ j , µ j and η j are updated using p * j obtained from (11). In the subsequent iterations, the optimal values of λ j , µ j and η j are used to calculate the optimal p * j .…”

Section: A Proposed Multiobjective Solutionmentioning

confidence: 99%

Multiobjective Optimization of Uplink NOMA-Enabled Vehicle-to-Infrastructure Communication

et al. 2020

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“…The objective here is to optimise

η_{m^{'}}

, that is, to determine which of the RBs used by V2X links can be reused by the U2V links. To solve this problem, we apply the resource allocation scheme proposed in [11] with the iterative 3DM algorithm, where graph theory is applied to model the interference environment [24–26].…”

Section: Density‐aware Deployment Schemementioning

confidence: 99%

Density‐aware deployment with multi‐layer UAV‐V2X communication networks

et al. 2020

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Unmanned aerial vehicle (UAV)-assisted communications have been regarded as a promising technology, which can be used in dynamic heterogeneous networks, since the UAVs can be applied as mobile base stations (MBSs). It is more efficient to set the UAVs as MBSs in different layers according to their functions. Due to the ability in communicating with other vehicles or facilities, vehicle-to-everything (V2X) makes the information required by the vehicles be efficiently transmitted and processed, so as to increase the safety of driving. However, because of the rapid change of topology and the huge demand of data transmission, it is hard to guarantee the efficient coverage of all the vehicles only by the support of terrestrial wireless communication networks. Considering this, this study combines UAV and V2X communications together, and proposes a multilayer aerial-road vehicular (MLARV) architecture. The UAVs in the higher layer are in charge of overall monitoring, while the UAVs in the lower layer are responsible for hot-spot area coverage. To solve the throughput maximisation problem, the authors further propose a density-aware deployment (DAD) scheme with an iterative three-dimensional matching resource allocation algorithm. Simulation results show that the proposed DAD scheme with the MLARV architecture outperforms the traditional UAV-assisted V2X communications with single layer architecture.

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“…Some prior research endeavor has been put into the application of NOMA to V2X communications [7]- [9]. In [7], the authors proposed efficient centralized and decentralized schemes for NOMA based V2X broadcasting systems.…”

mentioning

confidence: 99%

“…Further, in [8], the authors investigated the application of NOMA to relay-aided broadcasting/multicasting scenarios, where optimal power allocation is studied. In [9], the authors studied the resource allocation problem for NOMA aided V2X network by applying weighted 3-partite interference hypergraph.…”

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confidence: 99%

Performance of Downlink NOMA in Vehicular Communication Networks: An Analysis Based on Poisson Line Cox Point Process

Sun

Ding

Dai

et al. 2020

IEEE Trans. Veh. Technol.

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In this paper we investigate downlink performance in a non-orthogonal multiple access (NOMA) based vehicular communication network. In contrast to the previous works wherein the vehicles are simply assumed to be located anywhere in the coverage area, we consider practical cases where vehicles are located on a system of roads. We then adopt a system model based on Poisson Line Cox Point (PLC) processes, where the road system is represented through a Poisson Line (PL) Process. Vehicles ordered according to their distances to their corresponding roadside units (RSUs) are then served by using power domain NOMA. Adopting analytical tools from the stochastic geometry, we then analyse the outage performance of the system. Numerical results corroborate our analysis and demonstrate how the system settings influence the considered NOMA based V2X network. Index Terms-Poisson line Cox point (PLC) process , vehicular communications, non-orthogonal multiple access (NOMA) I. INTRODUCTION T He proliferation of intelligent transport systems (ITSs) encourages research on design and performance evaluation of vehicle-to-everything (V2X) communications both in academia and industry [1]. According to [2], V2X communications can be implemented either as a sidelink for direct communications over the PC5 interface, such as vehicle-tovehicle (V2V), vehicle-to-pedestrian (V2P) and vehicle-toinfrastructure (V2I), or as a traditional cellular link over the Uu interface, such as vehicle-to-network (V2N). It is worth pointing out that this paper will only focus on a downlink V2N scenario, where each roadside unit (RSU) needs to transmit different messages to different vehicle users. Existing V2X communications are based on orthogonal multiple access (OMA), where one channel resource block can only be occupied by one user. However, due to the ever increasing number of vehicular users and the scarce bandwidth available for vehicular communications, a dilemma may occur when the number of users is much larger than the number of available resource blocks. As a result, some users have to wait for a period of time before getting service. In this case, the

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Interference Hypergraph-Based 3D Matching Resource Allocation Protocol for NOMA-V2X Networks

Cited by 23 publications

References 17 publications

Multiobjective Optimization of Uplink NOMA-Enabled Vehicle-to-Infrastructure Communication

Multiobjective Optimization of Uplink NOMA-Enabled Vehicle-to-Infrastructure Communication

Density‐aware deployment with multi‐layer UAV‐V2X communication networks

Performance of Downlink NOMA in Vehicular Communication Networks: An Analysis Based on Poisson Line Cox Point Process

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