OFDM Modulated PNC in V2X Communications: An ICI-Aware Approach Against CFOs and Time-Frequency-Selective Channels

Situ, Zhenhui; Ho, Ivan Wang‐Hei; Wang, Taotao; Liew, Soung Chang; Chau, Chi-Kin

doi:10.1109/access.2018.2889219

Cited by 9 publications

(5 citation statements)

References 30 publications

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“…where 𝑈 𝑡𝑜𝑡 is the resultant electric-field envelope, 𝑅 𝑎 is the reflection coefficient of the 𝑎-th path, 𝐷 𝑒 is the diffraction coefficient of the 𝑒-th path, and 𝑃 𝑟 is the received power. We implement the network simulation accordingly, the location is the intersection of Fong Shu Chuen Hall on PolyU campus, which the simulation result is consistent with the empirically collected dataset in our previous work [22]. As shown in Fig.…”

Section: B City-model-aware Channel Modelingsupporting

confidence: 75%

“…As shown in Fig. 3(b), on-road V2I experiments based on universal software radio peripheral (USRP) were conducted on PolyU campus to collect experimental vehicular channel data [22]. One set of the data is used in the training dataset for the CMA channel modeling approach, and another set is used as testing data to verify the performance of the proposed models.…”

Section: B City-model-aware Channel Modelingmentioning

confidence: 99%

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Digital-Twin-Enabled City-Model-Aware Deep Learning for Dynamic Channel Estimation in Urban Vehicular Environments

Ding

2022

IEEE Trans. on Green Commun. Netw.

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Most of the existing works on vehicle-to-everything (V2X) communications assume some deterministic or stochastic channel models, which is unrealistic for highly-dynamic vehicular channels in urban environments under the influence of high-speed vehicle motion, intermittent connectivity, and signal attenuation in urban canyon. Enabled by the concept of digital twin, the digital replica of a real-world physical system, this paper proposes a city-model-aware deep learning algorithm for dynamic channel estimation in urban vehicular environments. Specifically, the digital twin simulation allows us to accurately model radio ray reflection and attenuation in urban canyon, and the data can be supplemented and validated with empirical measurements. Our results indicates that the city-model-aware deep neural network (CMA DNN) estimator performs much better than conventional methods and has more than 32% improvement in BER when compared with generic DNN approaches that do not take the 3D city model into account. Since some geometry-based models like ray-tracing techniques used in the digital twin simulation for dynamic channel modeling could be computational expensive, we also propose a basis expansion model (BEM) approach to simplify the computation load of the overall methodology to gain a good balance between accuracy and timeliness.

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Section: B City-model-aware Channel Modelingsupporting

confidence: 75%

Section: B City-model-aware Channel Modelingmentioning

confidence: 99%

Digital-Twin-Enabled City-Model-Aware Deep Learning for Dynamic Channel Estimation in Urban Vehicular Environments

Ding

2022

IEEE Trans. on Green Commun. Netw.

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“…Meanwhile, protected data exchange and vehicle identity privacy are used to overcome security problems by using the ElGamal encryption technique with a tweaked Schnorr signature technique. In addition, incorporating physical layer network (PNC) coding in vehicle-to-all communications to handle time-critical properties will minimize short touch time issues created by high-speed vehicle travel [41]. General conceptualizations that can be extended to the communication domain of an Intelligent Transportation System (ITS) enable the exchanging of information between applications and services running on the equipment that makes up a VANET, particularly moving vehicles, fixed road infrastructure systems, and mobile personal devices [42].…”

Section: Discussionmentioning

confidence: 99%

Performance analysis of communication model on position based routing protocol : review analysis

Himawan¹,

Hassan

Bahaman

2022

IJCAI

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Research on the Vanet system always has its own challenges and obstacles. The communication system between nodes is certainly the main problem that is always faced. The communication model and concept in the routing protocol process is a very decisive choice to get good communication quality. Four categories in vanet system topology, namely position based routing protocols, broadcast based routing protocols, cluster based routing protocols and multicast/geocast routing protocols, have fundamental differences, especially in the concept of sending data and information between nodes. For this reason, in this study, the selection of standardization and integration of data delivery between nodes is of particular concern and is certainly an interesting thing to study more deeply. The ability to send data properly in busy and fast traffic conditions has its own challenges. For this, there are many variables that must be considered, so that communication between nodes will be better Povzetek: .

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“…Therefore, JD provides better performance than SIC at the cost of higher complexity. Network-Coded Multiple Access (NCMA) is an example of JD-based NOMA scheme that employs Physical-layer Network Coding (PNC) to boost the throughput [8] [9]. Focusing on message exchange among multiple vehicles, our previous work showed that NCMA provided higher throughput performance as compared with SIC and the complexity can be reduced by exploiting the side information [10][11].…”

Section: Introductionmentioning

confidence: 99%

Stochastic analysis of urban V2X communications: Orthogonality versus non-orthogonality

Situ¹,

Ho²,

Xu³

et al. 2022

ITU J-FET

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In this paper, we study the broadcasting performance of urban Vehicle-to-everything (V2X) communications at road intersections. In such environments, dense buildings obstruct the radio channel between vehicles in adjacent road segments and Non-Line-Of-Sight (NLOS) signal propagation reduces the received power level. Therefore, messages that originate from adjacent roads traveling in a non-parallel directions usually have weaker signals than those from the road segment traveling in parallel opposite direction. Besides, the high vehicular density leads to insuficient orthogonal channel resources and high level of interference. We propose to apply Non-Orthogonal Multiple Access (NOMA) to V2X communications at urban road intersections to enhance the spectrum efficiency and improve the Package Delivery Ratio (PDR) performance. With NOMA, signals from multiple transmitters are decoded together and the interference from undesired users can be canceled if these messages are retrieved. Specifically, we study two NOMA-based V2X communication schemes, namely, NOMA-V2X decoded by Successive Interference Cancellation (SIC-V2X) and NOMA-V2X decoded by Joint Decoding (JD-V2X). Based on the tools developed in stochastic geometry, we derive and compare the PDR expressions for both NOMA schemes and the Orthogonal Multiple Access (OMA) scheme. Our results indicate that 1) both NOMA schemes outperform the conventional OMA scheme and the PDR of LOS/NLOS communications with two-user access increases by 51%/369%; 2) for four-user access, the proposed NOMA scheme shows 375% goodput enhancement as compared with the OMA scheme; and 3) JD-V2X provides significant PDR enhancement compared with SIC-V2X in the high data rate regime. Finally, we also demonstrate that the random access based NOMA schemes can achieve lower transmission latency than collision-free scheduling schemes when the road is over 56% jammed.

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OFDM Modulated PNC in V2X Communications: An ICI-Aware Approach Against CFOs and Time-Frequency-Selective Channels

Cited by 9 publications

References 30 publications

Digital-Twin-Enabled City-Model-Aware Deep Learning for Dynamic Channel Estimation in Urban Vehicular Environments

Digital-Twin-Enabled City-Model-Aware Deep Learning for Dynamic Channel Estimation in Urban Vehicular Environments

Performance analysis of communication model on position based routing protocol : review analysis

Stochastic analysis of urban V2X communications: Orthogonality versus non-orthogonality

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