Power control and mode selection for VBR video streaming in D2D networks

Ye, Chuang; Gursoy, M. Cenk; Velipasalar, Senem

doi:10.1109/wcnc.2018.8377422

Cited by 8 publications

(6 citation statements)

References 7 publications

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“…After selecting the coding scheme for each frame (I, P or B), it is forwarded using one of the possible transmission modes. Similarly, mode selection is jointly considered with power control for variable bit rate (VBR) video streaming in [95] aiming at maximizing the overall data rate while considering buffer utilization (buffer underflow and overflow events). Transmission power in each of the three possible modes is determined then the optimal mode that achieves the best data rate is selected.…”

Section: Mode Selection Schemes In D2d Video Streamingmentioning

confidence: 99%

Video Transmission Using Device-to-Device Communications: A Survey

2019

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In recent years, the growing interest in video-based applications has resulted in a rapid increase in wireless data traffic and meeting the stringent quality-of-experience (QoE) requirements for such type of traffic poses a great challenge given the scarce spectrum. As a consequence, new approaches have been investigated to tackle this problem and one promising solution proposed by researchers is to exploit deviceto-device (D2D) communication in video transmission. D2D communication has been presented as an innovation that can improve the cellular network performance by exploiting the proximity-based service between closely-located devices. It enhances the spectral and energy efficiencies, improves the capacity of the network and reduces the communication delay as well. Despite the above-mentioned advantages, there are some challenges in video transmission over D2D networks that need to be addressed. These issues include proposing methods for improving the quality of video streaming, management of the possible resulting interference between the D2D links and regular cellular links, resource allocation as well as appropriate selection of the mode of operation. Besides, issues related to D2D-based video caching such as clustering, energy consumption and the use of incentive-based schemes have also been discussed. In this paper, we examine the challenges of video streaming over D2D networks and comprehensively review the available solutions proposed in the literature.

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Section: Mode Selection Schemes In D2d Video Streamingmentioning

confidence: 99%

Video Transmission Using Device-to-Device Communications: A Survey

2019

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“…Finally, the transmission mode is assigned to each packet to maximize the quality without exceeding a predefined energy limit. Also, mode selection is considered jointly with power control for variable bit rate (VBR) video streaming in [9] with the goal of maximizing the overall throughput while taking into account buffer underflow and overflow events. Transmission power is determined in each mode and the mode that maximizes the throughput is selected.…”

Section: Introductionmentioning

confidence: 99%

“…In more details, the mode that maximizes the D2D rate is selected for transmission taking into account the minimum rate requirements of both the CUs and D2D pairs, the D2D buffers occupancies and video quality. Different from the assumption of assigning one channel to each user in [9] and [29] or dividing the available resources equally between users in [10], here we estimate the number of Resource Blocks (RBs) to be assigned to CUs and D2D pairs according to the required rate and SNR of each user. In addition, instead of constant bit rate streaming (CBR) as in [9], we adopt SVC where each frame is encoded into one base layer and multiple enhancement layers, and the number of layers to be transmitted is determined by a proposed SVC layer selection algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…Different from the assumption of assigning one channel to each user in [9] and [29] or dividing the available resources equally between users in [10], here we estimate the number of Resource Blocks (RBs) to be assigned to CUs and D2D pairs according to the required rate and SNR of each user. In addition, instead of constant bit rate streaming (CBR) as in [9], we adopt SVC where each frame is encoded into one base layer and multiple enhancement layers, and the number of layers to be transmitted is determined by a proposed SVC layer selection algorithm. Moreover, unlike the works in [23]- [25], which discussed improving QoE of video streaming over the D2D network via only maximizing the video quality, in this paper, we consider both buffer occupancy and quality of the stream in D2D pairs scheduling.…”

Section: Introductionmentioning

confidence: 99%

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A QoE-Aware Mode Selection Framework for Video Streaming in D2D Networks

2020

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Device-to-Device (D2D) communication is a novel approach that has been proposed to enhance the performance of traditional cellular networks. This work focuses on video streaming using D2D communications underlaying a Long Term Evolution (LTE) network where resources are allocated to each D2D pair in three modes of operation; cellular, dedicated and reuse. The objective is to maximize the sumrate of the D2D pairs while maintaining continuous video playback with an acceptable quality level. Unlike previous works, which assign one channel to each user or divide the available resources equally between them or assume constant bit rate streaming (CBR), we estimate the number of Resource Blocks (RBs) needed for all users according to their rate and Signal-to-Noise Ratio (SNR) requirements and consider Scalable Video Coding (SVC). A complete Quality of Experience (QoE)-aware framework for D2D-based video streaming that includes resource allocation, power control, mode selection and SVC layer selection is then proposed while taking into consideration buffer occupancies and the video peak signal-to-noise ratio (PSNR). The efficacy of the proposed scheme is evaluated through extensive simulations and compared to the scenario where only one mode of operation is assigned to all D2D pairs. Furthermore, the effect of the number of D2D users as well as their mobility is also investigated. Simulation results show that the proposed framework improves the throughput of the D2D pairs when compared to a single mode of operation while at the same time providing better video quality and continuity.

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“…In [4], the authors investigated an energy-efficient video downlink transmission by predicting the download rate at the receiver. In [5], we studied power control and mode selection for VBR video streaming in D2D networks in the presence of potential interference, and showed that video delivery with power control and mode selection leads to improved performance. Power control is determined by judiciously considering all possible scenarios and checking the constraints.…”

Section: Introductionmentioning

confidence: 99%

Power Control for Wireless VBR Video Streaming: From Optimization to Reinforcement Learning

Gursoy

Velipasalar

2019

IEEE Trans. Commun.

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In this paper, we investigate the problem of power control for streaming variable bit rate (VBR) videos over wireless links. A system model involving a transmitter (e.g., a base station) that sends VBR video data to a receiver (e.g., a mobile user) equipped with a playout buffer is adopted, as used in dynamic adaptive streaming video applications. In this setting, we analyze power control policies considering the following two objectives: 1) the minimization of the transmit power consumption, and 2) the minimization of the transmission completion time of the communication session. In order to play the video without interruptions, the power control policy should also satisfy the requirement that the VBR video data is delivered to the mobile user without causing playout buffer underflow or overflows. A directional water-filling algorithm, which provides a simple and concise interpretation of the necessary optimality conditions, is identified as the optimal offline policy. Following this, two online policies are proposed for power control based on channel side information (CSI) prediction within a short time window. Dynamic programming is employed to implement the optimal offline and the initial online power control policies that minimize the transmit power consumption in the communication session. Subsequently, reinforcement learning (RL) based approach is employed for the second online power control policy. Via simulation results, we show that the optimal offline power control policy that minimizes the overall power consumption leads to substantial energy savings compared to the strategy of minimizing the time duration of video streaming. We also demonstrate that the RL algorithm performs better than the dynamic programming based online grouped water-filling (GWF) strategy unless the channel is highly correlated.Index Terms-dynamic programming, playout buffer underflow, playout buffer overflow, power control, reinforcement learning, variable bit rate (VBR) video, video streaming.

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Power control and mode selection for VBR video streaming in D2D networks

Cited by 8 publications

References 7 publications

Video Transmission Using Device-to-Device Communications: A Survey

Video Transmission Using Device-to-Device Communications: A Survey

A QoE-Aware Mode Selection Framework for Video Streaming in D2D Networks

Power Control for Wireless VBR Video Streaming: From Optimization to Reinforcement Learning

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