Interference-aware User Grouping Strategy in NOMA Systems with QoS Constraints

Guo, Fengqian; Lu, Hancheng; Zhu, Daren; Wu, Hao

doi:10.1109/infocom.2019.8737590

Cited by 20 publications

(18 citation statements)

References 24 publications

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“…In [33], the authors use a directed graph to model the externalities in stable matching model. Inspired by this idea, we construct a directed graph G D (V D , E D ) to model the externalities in our popular matching model, where V D = D denotes the vertex set and E denotes the directed edge set.…”

Section: Popular Matching With Externalitiesmentioning

confidence: 99%

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Popular Matching for Security-Enhanced Resource Allocation in Social Internet of Flying Things

Wang

Sun

Duong

et al. 2020

IEEE Trans. Commun.

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As the Internet of Things (IoT) is maturing and acquires its social flavor, the Social IoT enables smart devices to build inter-thing social networks without human intervention. As a new form of smart devices, unmanned aerial vehicles (UAVs) are finding their way into IoT applications. The integrated Social Internet of Flying Things (SIoFT) can provide the socialaware UAV-assisted services. However, the broadcast nature of air-to-ground (A2G) channels makes them vulnerable to being eavesdropped by terrestrial malicious users due to their strong line-of-sight (LoS) links. In this paper, we investigate to ensure the security of A2G communications when the location information of multiple potential eavesdroppers cannot be perfectly estimated. Following the "no pain no gain" principle, the terrestrial users who reuse the UAV cellular spectrum will act as friendly jammers to realize "win-win" situation. Hence, joint trajectory design, power control, and channel allocation optimization problem is formulated to maximize the average secrecy rate of UAVs in worst case. In the first stage, we utilize the block coordinate descent method and successive convex optimization method to solve the trajectory design and power control problems in an iterative manner. In the second stage, we convert the user pairing problem into a popular matching problem with externalities. Two distributed algorithms are proposed to maintain the popular matching under dynamics. Moreover, we conduct detailed analysis of the popularity, convergence, and computational complexity. Simulation results demonstrate the superiority of our proposed method in terms of different performance metrics.

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Section: Popular Matching With Externalitiesmentioning

confidence: 99%

“…For the third condition, since both endpoints of ρ are matched in Ω, neither endpoint is matched in Ω and contribute -1 to the first term on (33). Through Lemma 3, at most one edge can be labeled (1, 1), and then this contribution is canceled out by the votes of two endpoints.…”

mentioning

confidence: 97%

Popular Matching for Security-Enhanced Resource Allocation in Social Internet of Flying Things

Wang

Sun

Duong

et al. 2020

IEEE Trans. Commun.

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“…The article in [16] investigates load balancing solutions to optimize the QoS of a cloud radio access network. The authors in [17] study user grouping strategies while considering the diverse QoS requirements of users in Non-Orthogonal Multiple Access (NOMA) systems. A game theoretic approach for interference-limited cellular environments is presented in [11].…”

Section: Related Work and Motivationmentioning

confidence: 99%

“…-Focus on QoS provisioning [8], [9], [10], [11] -Examining energy-efficiency aspects [12], [13] -Different network deployment technologies [14], [15], [16], [17] -Implementation of QCI awareness [18], [19].…”

Section: Related Work and Motivationmentioning

confidence: 99%

Performance Comparison of QoS Deployment Strategies for Cellular Network Services

Zeydan¹,

Mangues‐Bafalluy²,

Dedeoglu³

et al. 2020

IEEE Access

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Differentiated quality-of-Service (QoS) techniques are widely used to distinguish between different service classes and prioritize service needs in mobile networks. Mobile Network Operators (MNOs) utilize QoS techniques to develop strategies that are supported by the mobile network infrastructure. However, QoS deployment strategy can ensure that the radio resources provided by the base station are easily consumed if it is not used correctly or when different techniques are used all together. In this paper, we propose a scheduling algorithm and compare two different QoS deployment strategies for prioritized User Equipment (UEs) (with higher scheduling rates and dedicated bandwidth) that MNOs can use in the current infrastructure, using a commercial real-time Long Term Evolution (LTE) network in different test scenarios. Moreover, we expose the real-time user experience in terms of uplink throughput and analyze results of the UE's real-time key performance indicators (KPIs) in detail. Experiment results are evaluated considering the implications of different QoS support types on network coverage and capacity planning optimizations. Our results demonstrate that even though preconfigured resource allocations can be given to prioritize UEs, the experience of all the UEs can be affected unexpectedly in the presence of many UEs who have received different QoS deployment support. Our experimental observations have revealed that location of the UEs with respect to Base Station (BS) and the availability of dedicated bandwidth UEs inside cell may have implications on the apriori defined resource allocation strategies of the other UEs. INDEX TERMS QoS, differentiated services, mobile networks, experiments.

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“…To address aforementioned challenges, in this paper, we study QoS-aware user grouping strategy that minimizes power consumption in multi-cell NOMA systems with inter-cell interference. Our preliminary work was presented in [31]. In [31], we solved the user grouping problem in single-cell NOMA systems with QoS constraints using graph theory.…”

Section: Introductionmentioning

confidence: 99%

QoS-aware User Grouping Strategy for Downlink Multi-Cell NOMA Systems

Guo,

Lu,

Jiang

et al. 2021

Preprint

Self Cite

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In multi-cell non-orthogonal multiple access (NOMA) systems, designing an appropriate user grouping strategy is an open problem due to diverse quality of service (QoS) requirements and inter-cell interference. In this paper, we exploit both game theory and graph theory to study QoS-aware user grouping strategies, aiming at minimizing power consumption in downlink multi-cell NOMA systems. Under different QoS requirements, we derive the optimal successive interference cancellation (SIC) decoding order with inter-cell interference, which is different from existing SIC decoding order of increasing channel gains, and obtain the corresponding power allocation strategy. Based on this, the exact potential game model of the user grouping strategies adopted by multiple cells is formulated. We prove that, in this game, the problem for each player to find a grouping strategy can be converted into the problem of searching for specific negative loops in the graph composed of users. Bellman-Ford algorithm is expanded to find these negative loops. Furthermore, we design a greedy based suboptimal strategy to approach the optimal solution with polynomial time. Extensive simulations confirm the effectiveness of grouping users with consideration of QoS and inter-cell interference, and show that the proposed strategies can considerably reduce total power consumption comparing with reference strategies.

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Interference-aware User Grouping Strategy in NOMA Systems with QoS Constraints

Cited by 20 publications

References 24 publications

Popular Matching for Security-Enhanced Resource Allocation in Social Internet of Flying Things

Popular Matching for Security-Enhanced Resource Allocation in Social Internet of Flying Things

Performance Comparison of QoS Deployment Strategies for Cellular Network Services

QoS-aware User Grouping Strategy for Downlink Multi-Cell NOMA Systems

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