Utilizing turbo codes for secure 5G V2X

Chaikalis, Costas; Kosmanos, Dimitrios; Samaras, Nicholas

doi:10.1109/mttw51045.2020.9245035

Cited by 10 publications

(12 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Let's give more information on the simulated transmission of the transmitter−receiver pair, where the transmission power is 100 mW and results in a transmission range of less than 500 m. Furthermore, in our simulation model we transmit a total of 1,000,000 bits, which are divided into appropriate data frames. Subsequently, they are turbo encoded and send every TTI, to the mobile channel similarly to [20][21][22]. C-V2X in the direct mode operates in what is known as the intelligent transport systems (ITS) frequency band at 5.9 GHz.…”

Section: Gpp 5g V2x Qos Scenarios and Proposed Dynamic System Modelmentioning

confidence: 99%

“…The choice of most of these parameters is based on the 6 scenarios of Table 1. The two Table 2 frame lengths have been chosen similarly to [21,22], while the data rates are similar to those in [20]. The difference with [20] is that in this work the focus is on larger short frame lengths of 256 and 512 bits, while in [20] mainly a short frame length of 128 bits is considered.…”

Section: Gpp 5g V2x Qos Scenarios and Proposed Dynamic System Modelmentioning

confidence: 99%

“…However, none of these papers considers channel coding parameters (e.g., different decoding algorithms, number of iterations) in the optimization process for the realistic QoS indicators to be satisfied. The idea of focusing on physical layer channel coding process and particularly using turbo coding in 5G V2X systems has been initially discussed in [20][21][22][23] without, however, the channel coding parameters being optimized for realistic QoS indicators. An initial approach has been investigated in [20,21], where only a small frame length of 128 bits is examined without the message size to be investigated in the simulation results and not enough vehicle density values are considered.…”

Section: Comparison Of the Proposed Approach With Published Literaturementioning

confidence: 99%

“…Specifically, some papers focus on RSC methods [17], whereas other papers focus on radio resource management [15] and the last subcategory of papers optimize the QoS papers triggered by dynamic radio conditions [16]. The idea of focusing on physical layer channel coding process and particularly using turbo coding in 5G V2X systems has been initially discussed in [20][21][22][23] without, however, the channel coding parameters being optimized for realistic QoS indicators. Turbo decoding adds significant complexity to the system and the most popular algorithms to be used are log maximum a−posteriori (log-MAP), max-log-MAP and soft output Viterbi algorithm (SOVA).…”

Section: Introduction and Related Workmentioning

confidence: 99%

“…The general idea, according to [21], is to use the specific simulation results in a future system with real-time coding parameters dynamic prediction, which is based on the conditions of the external environment. In this case the specific QoS parameters of the specified scenarios have to be satisfied.…”

Section: Introduction and Related Workmentioning

confidence: 99%

See 4 more Smart Citations

3GPP 5G V2X Scenarios: Performance of QoS Parameters Using Turbo Codes

Kosmanos

Chaikalis

Savvas

2022

Telecom

Self Cite

View full text Add to dashboard Cite

Cellular vehicle-to-everything (C-V2X) communication has recently gained attention in industry and academia. Different implementation scenarios have been derived by the 3rd Generation Partnership Project (3GPP) 5th Generation (5G) Vehicle-to-Everything (V2X) standard, Release 16. Quality of service (QoS) is important to achieve reliable communication and parameters which have to be considered are reliability, end-to-end latency, data rate, communication range, throughput and vehicle density for an urban area. However, it would be desirable to design a dynamic selecting system (with emphasis on channel coding parameters selection) so that all QoS parameters are satisfied. Having this idea in mind, in this work we examine nine V2X implementation scenarios using Long Term Evolution (LTE) turbo coding with a geometry-based efficient propagation model for vehicle-to-vehicle communication (GEMV), where we consider the above QoS parameters for SOVA, log-MAP and max-log-MAP decoding algorithms. Our study is suitable for 3GPP cooperative sensing, for the eight scenarios considering medium and large signal-noise-ratio (SNR) values. The proposed model is sustainable despite a doubled data rate, which results in a minimal bit error rate (BER) performance loss up to 1.85 dB. In this case tripling the data rate results in a further 1 dB loss. Moreover, a small loss up to 0.4 dB is seen for a vehicle speed increase from 60 km/h to 100 km/h. Finally, increasing vehicle density has no effect on the implemented 3GPP scenario considering end-to-end latency, irrespectively from the decoding algorithm.

show abstract

Section: Gpp 5g V2x Qos Scenarios and Proposed Dynamic System Modelmentioning

confidence: 99%

Section: Gpp 5g V2x Qos Scenarios and Proposed Dynamic System Modelmentioning

confidence: 99%

Section: Comparison Of the Proposed Approach With Published Literaturementioning

confidence: 99%

Section: Introduction and Related Workmentioning

confidence: 99%

Section: Introduction and Related Workmentioning

confidence: 99%

See 3 more Smart Citations

3GPP 5G V2X Scenarios: Performance of QoS Parameters Using Turbo Codes

Kosmanos

Chaikalis

Savvas

2022

Telecom

Self Cite

View full text Add to dashboard Cite

show abstract

Data Forwarding System with Error Detection and Leader Selection Features

Obias

Magsino

Abad

et al. 2021

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

The concept of vehicular networks utilizes vehicular nodes and roadside units to exchange data to achieve travel comfort and convenience. However, as the number of vehicles on the road increases exponentially, the data dissemination becomes inefficient and lossy due to communication factors, one of which is the availability of too much sources of information. In this paper, a data forwarding system (DFS) is proposed to address communication failure due to bit error during data transmission and in the presence of data collision. The proposed system enables the receiver to detect errors in the received data using Hamming codes and utilizes a retransmission scheme to correct bit errors. DFS also selects a limited number of vehicles, called leaders, that can communicate with the infrastructure to minimize data collision and flooding. DFS, under various number of vehicles, is tested in additive white gaussian noise (AWGN) and Rayleigh channels. Simulation results show that DFS reduces bit error rate (BER) to approximately 54% in the AWGN and 62% in the Rayleigh channel for the maximum number of retransmissions simulated, respectively. Also, with DFS, data upload to infrastructures is reduced by at most 99.5% depending on the maximum allowable number of clusters and vehicles inside the RSU coverage.

show abstract