Self-Organizing Algorithms for Interference Coordination in Small Cell Networks

Ahmed, Furqan; Dowhuszko, Alexis A.; Tirkkonen, Olav

doi:10.1109/tvt.2017.2695400

Cited by 12 publications

(9 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a consequence, any user located in the overlapped area are subject to inter-cell interference, in addition to the inter-user interference caused by the messages of the nearby users within the same cell [12]. Hence, in order to improve the performance of the cell-edge users, various contributions have investigated the variation of time, frequency, or power allocation coordination schemes across the involved attocells [13]- [15]. For instance, multicolor schemes [16], multicarrier-based cell partitioning [17], optimized angle diversity receivers [18], and differential optical detection have been largely investigated in multi-cell VLC networks, showing an improvement on the achievable spectral efficiency compared to the single cell case [19].…”

Section: A Motivation and Contributionmentioning

confidence: 99%

Rate-Splitting Multiple Access: Unifying NOMA and SDMA in MISO VLC Channels

Naser

Sofotasios

Bariah

et al. 2020

IEEE Open J. Veh. Technol.

View full text Add to dashboard Cite

The increased proliferation of connected devices requires a development of innovative technologies for the next generation of wireless systems. One of the key challenges, however, is the spectrum scarcity, owing to the unprecedented broadband penetration rate in recent years. Based on this, visible light communication (VLC) has recently emerged as an effective potential solution for enabling high-speed short-range communications. Yet, despite their undoubted advantageous features, VLC systems suffer from several limitations which constraint their capabilities. As a result, several multiple access (MA) techniques, such as space-division multiple access (SDMA) and non-orthogonal multiple access (NOMA), have been considered in VLC networks as an effective approach, among others, to circumvent these limitations. However, despite their achievable multiplexing gain, their overall performance is still limited compared to the overall potential of this technology. Motivated by this, the presented article offers two contributions: firstly, we provide an overview of the key MA technologies used in VLC systems and then we introduce rate-splitting multiple access (RSMA), and discuss its capabilities and potentials in VLC systems. Secondly, through realistic system modeling and simulations of an RSMA-based two-user scenario, we illustrate the flexibility of RSMA as well as its superiority in terms of the achievable weighted sum rate over NOMA and SDMA in the context of VLC. Finally, we discuss technical challenges, open issues, and research directions, along with the offered results and insights that are expected to be useful towards the effective practical realization of RSMA in VLC configurations.

show abstract

Section: A Motivation and Contributionmentioning

confidence: 99%

Rate-Splitting Multiple Access: Unifying NOMA and SDMA in MISO VLC Channels

Naser

Sofotasios

Bariah

et al. 2020

IEEE Open J. Veh. Technol.

View full text Add to dashboard Cite

show abstract

“…The performance of intra-class user fairness is evaluated in both orthogonal and non-orthogonal 5G radio access technologies [21][22][23][24][25][26]. In non-orthogonal systems [21], different versions of PF scheduling rule are developed to study the impact in terms of user throughput, JFI fairness, and system complexity.…”

Section: Related Workmentioning

confidence: 99%

“…In Reference [23], the GPF parameterization is analyzed for non-orthogonal access systems while taking into account the joint optimization of power allocation and JFI user fairness. For schedulers based on orthogonal access, the JFI fairness performance for PF and Maximum Throughput (MT) scheduling rules is analyzed in Reference [24] for MIMO systems. Since the Quality of Experience (QoE) and, implicitly, the QoS provisioning are becoming the main differentiators between network operators when quantifying the fairness performance in RRM [27], an important aspect is played by the trade-off among other objectives such as system throughput maximization and meeting the QoS requirements.…”

Section: Related Workmentioning

confidence: 99%

A Comparison of Reinforcement Learning Algorithms in Fairness-Oriented OFDMA Schedulers

et al. 2019

View full text Add to dashboard Cite

Due to large-scale control problems in 5G access networks, the complexity of radioresource management is expected to increase significantly. Reinforcement learning is seen as apromising solution that can enable intelligent decision-making and reduce the complexity of differentoptimization problems for radio resource management. The packet scheduler is an importantentity of radio resource management that allocates users’ data packets in the frequency domainaccording to the implemented scheduling rule. In this context, by making use of reinforcementlearning, we could actually determine, in each state, the most suitable scheduling rule to be employedthat could improve the quality of service provisioning. In this paper, we propose a reinforcementlearning-based framework to solve scheduling problems with the main focus on meeting the userfairness requirements. This framework makes use of feed forward neural networks to map momentarystates to proper parameterization decisions for the proportional fair scheduler. The simulation resultsshow that our reinforcement learning framework outperforms the conventional adaptive schedulersoriented on fairness objective. Discussions are also raised to determine the best reinforcement learningalgorithm to be implemented in the proposed framework based on various scheduler settings.

show abstract

“…Thus inter-cell interference coordination (ICIC) is of vital importance for indoor coverage of mobile communication systems. Recent researches aiming at solving the ICIC problem for HetNets mainly focus on the techniques of power allocation and subcarriers scheduling for interference mitigation [7], [8]. While ICIC in HetNets has been extensively studied [8]- [13], the research in decentralized HetNets, where the SBSs make resource allocation decisions independently without information sharing, is still far from adequate, especially for the case of indoor deployment of plugand-play SBSs.…”

Section: Introductionmentioning

confidence: 99%

Self-Imitation Learning-Based Inter-Cell Interference Coordination in Autonomous HetNets

Yan

Yang²,

Cheny

et al. 2021

IEEE Trans. Netw. Serv. Manage.

View full text Add to dashboard Cite

Recently, mobile operators have been shifting to an intelligent autonomous network paradigm, where the mobile networks are automated in a plug-and-play manner to reduce the manual intervention. Under this circumstance, serious intercell interference becomes inevitable which may severely deteriorate system throughput performance and users' quality of service (QoS), especially for dense residential small base station (SBS) deployment. This paper proposes an intelligent inter-cell interference coordination (ICIC) scheme for autonomous heterogeneous networks (HetNets), where the SBSs agilely schedule sub-channels to individual users at each Transmit Time Interval (TTI) with aim of mitigating interferences and maximizing longterm throughput by sensing the environment. Since the reward function is inexplicit and only few samples can be used for priortraining, we formulate the ICIC problem as a distributed inverse reinforcement learning (IRL) problem following the POMDP games. We propose a non-prior knowledge based self-imitating learning (SIL) algorithm which incorporates Wasserstein Generative Adversarial Networks (WGANs) and Double Deep Q Network (Double DQN) algorithms for performing behavior imitation and few-shot learning in solving the IRL problem from both the policy and value. Numerical results reveal that SIL is able to implement TTI level's decision-making to solve the ICIC problem, and the overall network throughput of SIL can be improved by up to 19.8% when compared with other known benchmark algorithms.

show abstract

Self-Organizing Algorithms for Interference Coordination in Small Cell Networks

Cited by 12 publications

References 37 publications

Rate-Splitting Multiple Access: Unifying NOMA and SDMA in MISO VLC Channels

Rate-Splitting Multiple Access: Unifying NOMA and SDMA in MISO VLC Channels

A Comparison of Reinforcement Learning Algorithms in Fairness-Oriented OFDMA Schedulers

Self-Imitation Learning-Based Inter-Cell Interference Coordination in Autonomous HetNets

Contact Info

Product

Resources

About