Resource optimization and power allocation in in-band full duplex-enabled non-orthogonal multiple access networks

Elbamby, Mohammed S.; Bennis, Mehdi; Saad, Walid; Debbah, Mérouane; Latva-aho, Matti

doi:10.1109/jsac.2017.2726218

Cited by 70 publications

(42 citation statements)

References 33 publications

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“…The use of Matching Theory [27] -a mathematical framework from labor economics that attempts to describe the formation of mutually beneficial relationships over time-, has recently garnered a considerable interest in the context of resource allocation for wireless networks [28] with applications as varied as V2V communications [29], [30], FD-NOMA/OMA [31] or Fog computing [32]. However, for the sake of completeness we will first provide several definitions to properly address the fundamentals of this framework adapted to the problem at hand.…”

Section: Schedulingmentioning

confidence: 99%

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Taming the Latency in Multi-User VR 360°: A QoE-Aware Deep Learning-Aided Multicast Framework

Perfecto

Elbamby

Ser

et al. 2020

IEEE Trans. Commun.

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106

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Immersive virtual reality (VR) applications are known to require ultra-high data rate and low-latency for smooth operation. In this paper, we propose a proactive deep-learning aided joint scheduling and content quality adaptation scheme for multi-user VR field of view (FoV) wireless video streaming. Using a real VR head-tracking dataset, a deep recurrent neural network (DRNN) based on gated recurrent units (GRUs) is leveraged to obtain users' upcoming tiled FoV predictions. Subsequently, to exploit a physical layer FoV-centric millimeter wave (mmWave) multicast transmission, users are hierarchically clustered according to their predicted FoV similarity and location. We pose the problem as a quality admission maximization problem under tight latency constraints, and adopt the Lyapunov framework to model the problem of dynamically admitting and scheduling proactive and real-time high definition (HD) video chunk requests corresponding to a tile in the FoV of a cluster user for a given video frame while maintaining the system stability. After decoupling the problem into three subproblems, a matching theory game is proposed to solve the scheduling subproblem by associating chunk requests from clusters of users to mmWave small cell base stations (SBSs) for multicast transmission. Simulation results demonstrate the streaming quality gain and latency reduction brought by using the proposed scheme. It is shown that the prediction of FoV significantly improves the VR streaming experience using proactive scheduling of the video tiles in the users' future FoV. Moreover, multicasting significantly reduces the VR frame delay in a multi-user setting by applying contentreuse in clusters of users with highly overlapping FoVs.

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Section: Schedulingmentioning

confidence: 99%

“…Phase I -Interference learning and candidate chunk selection • Each u ∈ U, updatesÎ u (t) as per (31) and reports channel in the UL. • In the edge controller, queues in {χ(t)} u∈U are updated by solving (22), (24).…”

Section: Algorithm 1: Hd Chunk Scheduling Between Sbss and User-clustersmentioning

confidence: 99%

Taming the Latency in Multi-User VR 360°: A QoE-Aware Deep Learning-Aided Multicast Framework

Perfecto

Elbamby

Ser

et al. 2020

IEEE Trans. Commun.

Self Cite

106

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“…The problem in (8) actually belongs to the class of the General Linear Fractional Programming (GLFP) problem. Due to the characteristics of functions f n (x), ξ n (x) and ψ(x), this problem is a non-concave optimization problem.…”

Section: B Physical Layer Model For Noma Systemmentioning

confidence: 99%

“…Many studies have been carried out to analyze and improve performance of NOMA systems [2], [3], [5], [6], [7], [8]. The authors in [2] showed that NOMA can outperform OMA in terms of spectral efficiency.…”

Section: Introductionmentioning

confidence: 99%

Enabling Quality-Driven Scalable Video Transmission over Multi-User NOMA System

Jiang

Chen

2018

IEEE INFOCOM 2018 - IEEE Conference on Computer Communications

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Recently, non-orthogonal multiple access (NOMA) has been proposed to achieve higher spectral efficiency over conventional orthogonal multiple access. Although it has the potential to meet increasing demands of video services, it is still challenging to provide high performance video streaming. In this research, we investigate, for the first time, a multi-user NOMA system design for video transmission. Various NOMA systems have been proposed for data transmission in terms of throughput or reliability. However, the perceived quality, or the qualityof-experience of users, is more critical for video transmission. Based on this observation, we design a quality-driven scalable video transmission framework with cross-layer support for multiuser NOMA. To enable low complexity multi-user NOMA operations, a novel user grouping strategy is proposed. The key features in the proposed framework include the integration of the quality model for encoded video with the physical layer model for NOMA transmission, and the formulation of multiuser NOMA-based video transmission as a quality-driven power allocation problem. As the problem is non-concave, a global optimal algorithm based on the hidden monotonic property and a suboptimal algorithm with polynomial time complexity are developed. Simulation results show that the proposed multi-user NOMA system outperforms existing schemes in various video delivery scenarios.

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“…Following the initialization of the cluster bandwidths, which are independently executed by each BS in the order of OpU c log U c q, bandwidth and power allowances of clusters are updated by outer and inner while loops, respectively. The inner loop is processed by BSs in a parallel fashion, where optimal powers and Lagrange multipliers are first calculated by (11)- (13) and (15)-(17), respectively. Notice that calculations of (11) and (13) is the most time consuming part of the while loops and it can be given for BS c as O`2 ř r pK r c´1 q˘.…”

mentioning

confidence: 99%

Distributed Cluster Formation and Power-Bandwidth Allocation for Imperfect NOMA in DL-HetNets

Çelik

Tsai

Radaydeh

et al. 2019

IEEE Trans. Commun.

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In this paper, we consider an non-ideal successive interference cancellation (SIC) receiver based imperfect nonorthogonal multiple access (NOMA) schemes whose performance is limited by three factors: 1) Power disparity & sensitivity constraints (PDSCs), 2) Intra-cluster interference (ICRI), and 3) Intercell-interference (ICI). By quantifying the residual interference with a fractional error factor (FEF), we show that NOMA cannot always perform better than orthogonal multiple access (OMA) especially under certain receiver sensitivity and FEF levels. Assuming the existence of an offline/online ICI management scheme, the proposed solution accounts for the ICI which is shown to deteriorate the NOMA performance particularly when it becomes significant compared to the ICRI. Then, a distributed cluster formation (CF) and power-bandwidth allocation (PBA) approach are proposed for downlink (DL) heterogeneous networks (HetNets) operating on the imperfect NOMA. We develop a hierarchically distributed solution methodology where BSs independently form clusters and distributively determine the power-bandwidth allowance of each cluster. A generic CF scheme is obtained by creating a multi-partite graph (MPG) via partitioning user equipments (UEs) with respect to their channel gains since NOMA performance is primarily determined by the channel gain disparity of cluster members. A sequential weighted bi-partite matching method is proposed for solving the resulted weighted multi-partite matching problem. Thereafter, we present a hierarchically distributed PBA approach which consists of the primary master, secondary masters, and slave problems. For a given cluster power and bandwidth pair, optimal power allocations and Lagrange multipliers of slave problems are derived in closed-form. While power allowance of clusters is updated by the secondary masters based on dual variables of slave problems, bandwidth proportions of clusters are iteratively allocated by the primary master as per the utility achieved by the secondary masters at the previous iteration. Finally, the proposed CF and PBA approaches under the operation of imperfect NOMA are investigated and compared to the OMA scheme by extensive simulations results in DL-HetNets.Index Terms-Imperfect SIC, residual interference, intra-cell interference, inter-cell interference, hierarchical decomposition, distributed resource allocation. multi-partite matching.

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Resource optimization and power allocation in in-band full duplex-enabled non-orthogonal multiple access networks

Cited by 70 publications

References 33 publications

Taming the Latency in Multi-User VR 360°: A QoE-Aware Deep Learning-Aided Multicast Framework

Taming the Latency in Multi-User VR 360°: A QoE-Aware Deep Learning-Aided Multicast Framework

Enabling Quality-Driven Scalable Video Transmission over Multi-User NOMA System

Distributed Cluster Formation and Power-Bandwidth Allocation for Imperfect NOMA in DL-HetNets

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