Performance of Video Streaming in Infrastructure-to-Vehicle Telematic Platforms With 60-GHz Radiation and IEEE 802.11ad Baseband

Kim, Joongheon; Kwon, Seok-Chul; Choi, Giwan

doi:10.1109/tvt.2016.2547943

Cited by 25 publications

(15 citation statements)

References 12 publications

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“…Second, the tradeoff between the classification error rate p l→m and the SINR degradation term of η l→m is observed in (22). According to (25), the classification error rate decreases with d min (M l , M m ). However, if the modulation classification error occurs, then SINR would be increasingly degraded as d min (M l , M m ) increases.…”

Section: Capacity Of Noma Ut With Signal Classification Errorsmentioning

confidence: 97%

“…In (24), s m (k) is the closest one among the constellation points of M k to s l (i), so the case where s l (i) is confused with s m (k) is dominant for incorrect classification. Equation (25) is approximated one step further by only considering the symbol pairs from different modes, giving the minimum distance d min (M l , M m ). N min is the number of these pairs, and N min = 4 in Fig.…”

Section: Capacity Of Noma Ut With Signal Classification Errorsmentioning

confidence: 99%

See 1 more Smart Citation

Blind Signal Classification for Non-Orthogonal Multiple Access in Vehicular Networks

Choi

Yoon

Kim

2019

IEEE Trans. Veh. Technol.

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For downlink multiple-user (MU) transmission based on non-orthogonal multiple access (NOMA), the advanced receiver strategy is required to cancel the inter-user interference, e.g., successive interference cancellation (SIC). The SIC process can be applicable only when information about the co-scheduled signal is known at the user terminal (UT) side. In particular, the UT should know whether the received signal is OMA or NOMA, whether SIC is required or not, and which modulation orders and power ratios have been used for the superposed UTs, before decoding the signal. An efficient network, e.g., vehicular network, requires that the UTs blindly classify the received signal and apply a matching receiver strategy to reduce the high-layer signaling overhead which is essential for high-mobility vehicular networks. In this paper, we first analyze the performance impact of errors in NOMA signal classification and address ensuing receiver challenges in practical MU usage cases. In order to reduce the blind signal classification error rate, we propose transmission schemes that rotate data symbols or pilots to a specific phase according to the transmitted signal format. In the case of pilot rotation, a new signal classification algorithm is also proposed. The performance improvements by the proposed methods are verified by intensive simulation results.Index Terms-Non-orthogonal multiple access (NOMA), blind signal classification, signaling overhead, spectrum efficiency, 5Genabled vehicular networks J. Kim is with the

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Section: Capacity Of Noma Ut With Signal Classification Errorsmentioning

confidence: 97%

Section: Capacity Of Noma Ut With Signal Classification Errorsmentioning

confidence: 99%

Blind Signal Classification for Non-Orthogonal Multiple Access in Vehicular Networks

Choi

Yoon

Kim

2019

IEEE Trans. Veh. Technol.

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“…In (5), is a noise power spectral density which is −174 dBm/Hz [20], is one subchannel bandwidth in 60 GHz mmWave which is defined as 2.16 GHz in IEEE 802.11ad [5], and is a noise figure which is assumed to be 5 dB [12]. in (4) is a set of the wireless transmissions from VRS to VRD (those are not our main considering VR wireless communications) excluding the aforementioned main video streaming, that is, a set of interference transmissions.…”

Section: Calculation Of the Received Signal Strength At Vrdmentioning

confidence: 99%

“…For massive high-volume and high-definition multimedia contents delivery, millimeter-wave (mmWave) wireless communication technologies are widely discussed nowadays [5][6][7]. In mmWave wireless communication research, 60 GHz wireless technologies are generally and widely considered [8][9][10][11] because it is only one standardized millimeter-wave wireless technology so called IEEE 802.11ad [12].…”

Section: Introductionmentioning

confidence: 99%

Strategic Control of 60 GHz Millimeter-Wave High-Speed Wireless Links for Distributed Virtual Reality Platforms

Kim

Lee

2017

Mobile Information Systems

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This paper discusses the stochastic and strategic control of 60 GHz millimeter-wave (mmWave) wireless transmission for distributed and mobile virtual reality (VR) applications. In VR scenarios, establishing wireless connection between VR data-center (called VR server (VRS)) and head-mounted VR device (called VRD) allows various mobile services. Consequently, utilizing wireless technologies is obviously beneficial in VR applications. In order to transmit massive VR data, the 60 GHz mmWave wireless technology is considered in this research. However, transmitting the maximum amount of data introduces maximum power consumption in transceivers. Therefore, this paper proposes a dynamic/adaptive algorithm that can control the power allocation in the 60 GHz mmWave transceivers. The proposed algorithm dynamically controls the power allocation in order to achieve time-average energy-efficiency for VR data transmission over 60 GHz mmWave channels while preserving queue stabilization. The simulation results show that the proposed algorithm presents desired performance.

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“…Furthermore, the shift to mm-wave also involves a change to directive communications, rather than broadcasting, which introduces new challenges [8,9]. Within future wireless networks, mm-wave frequencies around 28 GHz and 37 GHz have been proposed for use in cellular 2 International Journal of Antennas and Propagation networks in urban environments (e.g., [10][11][12][13]), with the 25-40 GHz band being considered by the Federal Communications Commission in the US [14], whilst mm-wave frequencies between 55 and 100 GHz have been proposed for indoor environments and short-range outdoor environments, including vehicle-to-vehicle links, as well as other applications that may also rely on 5G networks (e.g., [13,[15][16][17]). …”

Section: Background and Motivationsmentioning

confidence: 99%

Beam-Steering Performance of Flat Luneburg Lens at 60 GHz for Future Wireless Communications

Foster

Nagarkoti

Gao

et al. 2017

International Journal of Antennas and Propagation

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The beam-steering capabilities of a simplified flat Luneburg lens are reported at 60 GHz. The design of the lens is first described, using transformation electromagnetics, before discussion of the fabrication of the lens using casting of ceramic composites. The simulated beam-steering performance is shown, demonstrating that the lens, with only six layers and a highest permittivity of 12, achieves scan angles of ±30 ∘ with gains of at least 18 dBi over a bandwidth from 57 to 66 GHz. To verify the simulations and further demonstrate the broadband nature of the lens, raw high definition video was transmitted over a wireless link at scan angles up to 36 ∘ . Background and MotivationsThe quest for ubiquitous wireless connectivity with everincreasing data rates has been a feature of the last half century. With the advent of the Internet of Things (IoT) adding huge numbers of devices requiring bandwidth to an alreadychallenging push for even greater data rates to be supported on personal wireless terminals, considerable research effort is being invested into future wireless networks. High-data rate applications include the streaming of ultrahigh definition video and virtual and augmented reality (e.g., [1,2]); the use of 60 GHz for these applications is now relatively wellestablished, with IEEE standards (e.g., 802.15.3c, 802.11ad[3]) well-suited for this aspect of 5G services and networks.Other aspects of 5G development are concerned with serving greater numbers of end-terminals and reducing latency, with some applications in the IoT relevant to this (even when data rate requirements are not severe).A large number of technologies are being brought together to achieve the various aims for the next generation of wireless networks [4]. This includes the use of small cells (where the density of base stations is increased), cooperative communications (where interference is reduced via communication between nodes, to improve achievable data rates and reliability), carrier aggregation (where bandwidth from disparate channels is combined to meet requirements), and heterogeneous networks (where multiple networks operating at different frequencies and with different modulations, etc., are used). One key technology is massive multi-input-multioutput (M-MIMO) systems, where the number of antennas is increased by at least an order of magnitude (e.g., [5][6][7]).One key approach to realise the objectives of future wireless networks is to utilise previously unused parts of the electromagnetic spectrum at higher frequency bands, particularly the millimetre-wave (mm-wave) and terahertz (THz) bands. Currently, wireless networks predominantly use the spectrum between 0.1 and 10 GHz, as these have offered key benefits of long propagation ranges, ease of fabrication, and ease of power generation and signal modulation, amongst others. Conversely, the higher bands must overcome increased propagation losses, smaller feature sizes that increase fabrication challenges, and other problems; the demand for bandwidth is such that these challenges...

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Performance of Video Streaming in Infrastructure-to-Vehicle Telematic Platforms With 60-GHz Radiation and IEEE 802.11ad Baseband

Cited by 25 publications

References 12 publications

Blind Signal Classification for Non-Orthogonal Multiple Access in Vehicular Networks

Blind Signal Classification for Non-Orthogonal Multiple Access in Vehicular Networks

Strategic Control of 60 GHz Millimeter-Wave High-Speed Wireless Links for Distributed Virtual Reality Platforms

Beam-Steering Performance of Flat Luneburg Lens at 60 GHz for Future Wireless Communications

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