Context-aware and priority-based user association and resource allocation in heterogeneous wireless networks

Zalghout, Mohamad; Khalil, Ayman; Crussière, Matthieu; Abdul-Nabi, Samih; Hélard, Jean-François

doi:10.1016/j.comnet.2018.11.001

Cited by 6 publications

(2 citation statements)

References 33 publications

(70 reference statements)

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“…Considering that users' mobility affects the performance of heterogeneous networks, Cheng et al [21] introduced the users' mobility and proposed a multiagent RL approach to maximize the system capacity. Based on users' preferences information, Zalghout et al [22] proposed a priority-based user association approach to maximize user's QoS in heterogeneous wireless networks.…”

Section: Related Workmentioning

confidence: 99%

Deep Reinforcement Learning-Based Joint Satellite Scheduling and Resource Allocation in Satellite-Terrestrial Integrated Networks

Yin

Huang

et al. 2022

Wireless Communications and Mobile Computing

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Satellite-terrestrial integrated networks (STINs) are considered to be a new paradigm for the next generation of global communication because of its distinctive merits, such as wide coverage, high reliability, and flexibility. When the satellite associates with different base stations (BSs) and adopts different channels for communication, the utility of offloading data to BSs is different. In our work, we study how to jointly associate satellites with appropriate BSs and allocate channels to satellites. Our purpose is to maximize the utility of the data offloaded from satellites to BSs while considering the load balance of BSs. However, some satellites are often unable to connect to BSs because of their periodic flight characteristic, which makes the joint satellite-BS association and channel allocation more challenging. To solve the problem that satellites sometimes cannot connect to BSs, we abstract the communication model between satellites and BSs into a bipartite graph and add a virtual BS to ensure that all satellites can connect to at least one BS. Then, in the constructed joint optimization problem, we solve the assignment of satellites and channels simultaneously. Considering that the joint optimization problem is nonconvex, we use double deep Q-Network (DDQN) for achieving the optimal strategy of satellite association and channel allocation. Furthermore, the reward value in most state transition information generated by satellites is 0, which leads to the low learning efficiency of DDQN. Aiming at enhancing the learning efficiency of DDQN, the priority sampling-based DDQN (PSDDQN) algorithm is proposed. Experimental results demonstrate that PSDDQN gets better utility and achieves the load balance of BSs compared with other algorithms.

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Section: Related Workmentioning

confidence: 99%

Deep Reinforcement Learning-Based Joint Satellite Scheduling and Resource Allocation in Satellite-Terrestrial Integrated Networks

Yin

Huang

et al. 2022

Wireless Communications and Mobile Computing

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“…The available literature on DL analysis of HCNs considering various load balancing and/or interference management schemes is solely based on SS-PLM and to the best of our knowledge here has been no work reported on analysis of multi-tier cellular networks which explicitly incorporates multi-slope PLM [6]- [9], [12], [14], [19], [21], [31]- [33]. Furthermore, the SS-PLM analysis cannot be trivially extended to multi-slope PLM primarily because of two reasons.…”

Section: B Major Contributionsmentioning

confidence: 99%

Impact of Frequency Reuse and Flexible Cell Association on the Performance of Dense Heterogeneous Cellular Networks Using Dual-Slope Path Loss Model

2019

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Densifying low-power/small base stations (SBSs) in support of overlaid macro BSs (MBS) is getting significant consideration as a viable solution for meeting the rapidly increasing capacity demands of emerging wireless networks. Given the disparity in transmit power of BS tiers, load balancing strategies have achieved paramount importance as they ensure balance of user access load amongst BS tiers and assist in availing maximum potential of multi-tier networks. Moreover, it is also essential to utilize efficient interference management schemes to account for the excessively increasing interference in the deployed networks. There is a plethora of literature available on the analysis of dense multi-tier networks that undertake various load balancing and interference management mechanisms but they are strictly limited to single slope (SS) path loss model (PLM). Furthermore, it is also well-known in literature that SS-PLM leads to inaccuracies in estimating the performance of dense networks owing to the simplistic approach of estimating the path loss. To overcome the limitations of SS-PLM, in our work, we have employed DS-PLM to study and analyze the performance of a two-tier dense cellular network that permits flexible user association using SBS biasing in conjunction with a simple frequency reuse mechanism. A comparison of SS-PLM with DS-PLM is performed for tier association probability and coverage probability, which shows that there is significant difference in the estimated overall network performance of our proposed scheme, as compared to SS-PLM. The results clearly signify the benefits of utilizing both load balancing and interference management mechanisms under DS-PLM, and give critical design insights for finding optimal parametric values in cellular planning. INDEX TERMS Coverage probability, dual-slope path loss model, frequency reuse, heterogeneous cellular networks, load balancing, stochastic geometry.

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Performance analysis of coverage-centric heterogeneous cellular networks using dual-slope path loss model

2021

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Context-aware and priority-based user association and resource allocation in heterogeneous wireless networks

Cited by 6 publications

References 33 publications

Deep Reinforcement Learning-Based Joint Satellite Scheduling and Resource Allocation in Satellite-Terrestrial Integrated Networks

Deep Reinforcement Learning-Based Joint Satellite Scheduling and Resource Allocation in Satellite-Terrestrial Integrated Networks

Impact of Frequency Reuse and Flexible Cell Association on the Performance of Dense Heterogeneous Cellular Networks Using Dual-Slope Path Loss Model

Performance analysis of coverage-centric heterogeneous cellular networks using dual-slope path loss model

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