Radio Resource Allocation for Multicast Services Based on Multiple Video Layers

Fuente, Alejandro de la; Escudero-Garzás, J. Joaquín; García‐Armada, Ana

doi:10.1109/tbc.2017.2781121

Cited by 10 publications

(7 citation statements)

References 21 publications

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“…where |A| is the complexity due to the "while" cycle over all |A| users in the worst case of the unicast transmission (lines [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. This means that each beam j covers only a single user.…”

Section: Complexity Analysismentioning

confidence: 99%

“…Meanwhile, multicast transmission can provide effective system bandwidth usage and energy efficiency improvement, thus playing a crucial role in emerging applications [11], [12]. In multicast transmissions, a device, which acts as a personal basic service set (PBSS) central point (PCP) or access point (AP), may transmit the same packet to a group of receivers simultaneously by utilizing the same frequency and the same modulation and coding scheme (MCS) [13]. Further, multicasting can improve the total network throughput [14], which is a critical feature for ultra-high-speed data transmissions.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Management of Multicast Traffic in Directional mmWave Networks

Chukhno

Pizzi

et al. 2021

IEEE Trans. on Broadcast.

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Multicasting is becoming more and more important in the Internet of Things (IoT) and wearable applications (e.g., high definition video streaming, virtual reality gaming, public safety, among others) that require high bandwidth efficiency and low energy consumption. In this regard, millimeter wave (mmWave) communications can play a crucial role to efficiently disseminate large volumes of data as well as to enhance the throughput gain in fifth-generation (5G) and beyond networks. There are, however, challenges to face in view of providing multicast services with high data rates under the conditions of short propagation range caused by high path loss at mmWave frequencies. Indeed, the strong directionality required at extremely high frequency bands excludes the possibility of serving all multicast users via a single transmission. Therefore, multicasting in directional systems consists of a sequence of beamformed transmissions to serve all multicast group members, subgroup by subgroup. This paper focuses on multicast data transmission optimization in terms of throughput and, hence, of the energy efficiency of resource-constrained devices such as wearables, running their resource-hungry applications. In particular, we provide a means to perform the beam switching and propose a radio resource management (RRM) policy that can determine the number and width of the beams required to deliver the multicast content to all interested users. Achieved simulation results show that the proposed RRM policy significantly improves network throughput with respect to benchmark approaches. It also achieves a high gain in energy efficiency over unicast and multicast with fixed predefined beams.

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Section: Complexity Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Efficient Management of Multicast Traffic in Directional mmWave Networks

Chukhno

Pizzi

et al. 2021

IEEE Trans. on Broadcast.

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“…Specifically, a threshold-based solution was proposed in [20] that dynamically selected a subset of subscribers to be served within each scheduling slot. The authors of [21] have made a step forward by striking a trade-off between error resilience and transmission rate. In [22], rate selection was optimized by maximizing the minimum throughput in a multicast group, even when the channel qualities were nonidentically distributed.…”

Section: Related Workmentioning

confidence: 99%

“…Then, after substituting (18), (20) and (21) into (19), we can derive a "loose" upper bound of the drift-plus-penalty as follows…”

Section: B Coarse-grained Assignment For Each Groupmentioning

confidence: 99%

Dynamic Resource Allocation for Scalable Video Multirate Multicast Over Wireless Networks

Chen

Yang

et al. 2020

IEEE Trans. Veh. Technol.

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Aided by scalable video coding, multirate multicast has become a promising technique of providing differentiated quality of experience (QoE) for massive numbers of video subscribers operating in heterogeneous channel conditions. Nevertheless, due to the time-varying nature of wireless channels and the subscribers' diverse requirements, it is challenging to dynamically control the video rate in the light of the available radio resource to achieve the best QoE. To elaborate a little further, the time scale of resource scheduling is of short-term nature, which determines the short-term video quality variation, but from a service provider's perspective the design objective is to optimize the long-term QoE for all subscribers. Despite its importance, this problem has not been considered before. Explicitly, we formulated this problem as a time-averaged stochastic optimization problem which avoids the impact of both the shortterm channel quality fluctuation and that of the video bitrates, whilst maintaining both inter-and intra-group fairness. The stratified structure of the problem inspires us to decompose it into a two-phase optimization: coarse grained assignment for each user group and fine grained assignment for each subgroup. We propose an adaptive multicast algorithm based on Lyapunov's optimization theory for solving this problem, by striking a compelling trade-off between the system's utility and its queue stability. We quantify the achievable performance of our proposed solution based on realistic video traces.

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“…Transmission for layered video has also been studied. Layered video, encoded by H.264/AVC and SHVC, can dynamically adjust the transmission rate to adapt to the channel state [4][5][6]13]. However, it has a high computational complexity.…”

Section: Introductionmentioning

confidence: 99%

Joint rate adaptation and resource allocation for real-time H.265/HEVC video transmission over uplink OFDMA systems

Wang

Cosman

2019

Multimed Tools Appl

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We consider multiuser video communication over uplink orthogonal frequency-division multiple access (OFDMA) systems. A cross-layer algorithm of joint bit allocation, packet scheduling and wireless resource assignment are proposed to minimize the end-to-end expected video distortion. Video rate adaptation is performed under the wireless resource constraints. The target number of encoding bits for each video packet is obtained to minimize the estimated distortion based on the online content-based rate-distortion function. Due to the inaccuracy of the rate control algorithm in H.265/HEVC encoding, the actual number of bits may differ from the target. Accordingly, the actual encoder distortion may deviate from the estimated distortion. Then, we propose an iterative algorithm to re-assign wireless resources based on the actual number of encoded bits to obtain the final resource allocation policy and packet scheduling decision. Numerical simulation results show that our proposed approach significantly outperforms the baseline algorithms in terms of received video quality.

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Radio Resource Allocation for Multicast Services Based on Multiple Video Layers

Cited by 10 publications

References 21 publications

Efficient Management of Multicast Traffic in Directional mmWave Networks

Efficient Management of Multicast Traffic in Directional mmWave Networks

Dynamic Resource Allocation for Scalable Video Multirate Multicast Over Wireless Networks

Joint rate adaptation and resource allocation for real-time H.265/HEVC video transmission over uplink OFDMA systems

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