Game Theoretical Power Control in Heterogeneous Network

Isnawati, Anggun Fitrian; Afandi, Mas Aly

doi:10.1109/icoict52021.2021.9527439

Cited by 5 publications

(4 citation statements)

References 19 publications

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“…The objective of the study was to evaluate the performance of seven advanced power control algorithms, specifically DPC [42], Kozkie Gojic [43], Isnawati [44], Thalabani [45], Luyong Zhang [46], Al Guamei [47], and Proposed model, in managing a network of Femtocells. The selected works represent a variety of approaches to power control in wireless networks, ranging from distributed power control, SIR-based algorithms, game theoretical approaches, to chaos theory-based methods.…”

Section: Experiments Setupmentioning

confidence: 99%

Optimizing Femtocell Networks: A Novel Game Theory Based Power Management Model for Enhanced SINR and Energy Efficiency

Airlangga,

Sihombing,

Bata

et al. 2024

IEEE Access

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This research presents a novel game theory based model for femtocell power management, engineered to significantly enhance the Signal-to-Interference-plus-Noise Ratio (SINR) while optimizing energy consumption across wireless communication networks. Femtocells, as a solution to the increasing demand for high-quality indoor network coverage, face challenges in power management and interference mitigation. Our proposed model addresses these issues, providing a sophisticated algorithmic approach that ensures high SINR levels without a proportional increase in power usage. Through a series of simulations, the model's performance was evaluated against existing power management techniques. The results, delineated across several tables, revealed that the proposed model consistently achieved and often surpassed targeted SINR levels with modest power consumption increments, even at high targets. Notably, at a SINR target of 20, the model sustained a high SINR of 23.62 while maintaining a reasonable energy profile. Additionally, the model exhibited exceptional operational efficiency, characterized by low execution times and rapid convergence rates, across varying network conditions. This responsiveness is essential for adapting to user mobility and varying traffic patterns, particularly in dense urban settings and during peak usage periods.

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Section: Experiments Setupmentioning

confidence: 99%

Optimizing Femtocell Networks: A Novel Game Theory Based Power Management Model for Enhanced SINR and Energy Efficiency

Airlangga,

Sihombing,

Bata

et al. 2024

IEEE Access

Self Cite

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“…The problem addressed in this study is lies in the limitations closely associated to systems that rely on a single radio access technology (RAT) and a single specific spectrum band used for data transmission. As a result, this approach is unable to manage communications among users effectively and appropriately, exposing the reliability of services to be relatively low, and ultimately leading to network congestion, service outages, and greatly increased delay [3,4]. In response to addressing this issue, the heterogeneous networks (Het-Nets) turns out to be a practical strategic solution, which are made possible by multi-connectivity and incorporate a variety of access technologies, such as wifi and cellular systems.…”

Section: Introductionmentioning

confidence: 99%

Distributed Reinforcement Learning–based Seamless Multi-Connectivity Solution for Heterogeneous 5GNR and Wi-Fi Networks

2024

IJIES

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The integration of 5G New Radio (5G-NR) and Wi-Fi networks in heterogeneous environments holds significant promise for delivering critical services with relatively high reliability and low latency. In this paper, we tackle the critical challenge of establishing robust multi-connectivity within heterogeneous systems integrating 5G NR and Wi-Fi systems. In this context, our focus is on optimizing a new, distributed multi-Connectivity solution, with a main emphasis on identifying the ideal base stations (BSs) and Wi-Fi access points (APs) with their respective spectrum associations. This solution is essential for ensuring low-latency and reliable communication required, particularly for mission-critical services. The simulation results demonstrate the significant advantages of the proposed algorithm compared to reference schemes. It leads to network performance improvements by enhancing system utility function, reducing service access time, and increasing packet success rates, through high-quality connectivity with relatively low interference probability. In particular, for mission-critical services, the proposed algorithm leads to a 16 % and 41% increase in effective network throughput when the offered load is 190 Mbps, which outperforms the benchmark approaches. Furthermore, it improves the utility function by approximately 0.12, and 0.19 compared to the reference approaches. This reflects a substantial improvements in success delivery rates for mission-critical services by 10 % and 18 %, respectively, when compared to the reference approaches, particularly evident at an offered load of approximately 190Mbps.

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“…Recently, game theory has gained substantial attention as a powerful tool to address these challenges [13] [36] [37]. Game theory provides a framework to model the strategic interactions among self-interested UAVs, facilitating the design of distributed algorithms that can achieve optimal resource allocation solutions.…”

Section: Introductionmentioning

confidence: 99%

Distributed Subcarrier Assignment and Discrete Power Allocation for Multi-UAV Millimeter-Wave Cooperative OFDMA Networks With Heterogeneous QoS Consideration

Wang,

You,

et al. 2023

IEEE Access

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In this paper, we formulate Subcarrier Assignment and Discrete Power Allocation for multi-UAV millimeter-wave cooperative Orthogonal Frequency Division Multiple Access (OFDMA) networks as a joint optimization problem considering the heterogeneous user data rate quality-of-service (QoS) requirements. The formulated joint optimization problem, named Discrete Power and Subcarrier Allocation (DPSA), is a nonconvex and mixed-integer nonlinear programming (MINP) problem, making it NP-hard to solve. We then transform the DPSA into the Subcarrier and Power Resource Efficient Cooperative Potential Game (SRECPG) based on game theory which facilitates distributed execution. We analyze the conditions under which a Nash Equilibrium (NE) exists in the SRECPG and provide rigorous proof of its existence. Furthermore, to enhance computational efficiency, we propose a BR-SSO algorithm based on better response dynamics. BR-SSO dramatically reduces the computational burden compared to the best response dynamics based on local exhaustive search (BRLES) while still ensuring convergence to a NE. Through extensive simulations, we demonstrated the effectiveness of the proposed SRECPG and BR-SSO algorithms. The results show significant improvements in throughput, fairness, and QoS guarantees compared to the baseline schemes. Our approach offers valuable insights into the design of efficient resource allocation schemes for multi-UAV millimeter-wave networks with varying QoS demands.INDEX TERMS Constrained potential game, downlink multi-cell OFDMA, Nash Equilibrium, unmanned aerial vehicle, blockage, millimeter-wave, resource allocation

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Game Theoretical Power Control in Heterogeneous Network

Cited by 5 publications

References 19 publications

Optimizing Femtocell Networks: A Novel Game Theory Based Power Management Model for Enhanced SINR and Energy Efficiency

Optimizing Femtocell Networks: A Novel Game Theory Based Power Management Model for Enhanced SINR and Energy Efficiency

Distributed Reinforcement Learning–based Seamless Multi-Connectivity Solution for Heterogeneous 5GNR and Wi-Fi Networks

Distributed Subcarrier Assignment and Discrete Power Allocation for Multi-UAV Millimeter-Wave Cooperative OFDMA Networks With Heterogeneous QoS Consideration

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