A Coalitional Model Predictive Control for the Energy Efficiency of Next-Generation Cellular Networks

Masero, Eva; Fletscher, Luis Alejandro; Maestre, J. M.

doi:10.3390/en13246546

Cited by 9 publications

(3 citation statements)

References 39 publications

(50 reference statements)

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“…This work also suggests that BSs are the prime contributors to the total power consumption of the cellular network through the chart shown in Figure 1. Authors in [22] also studied the methods to reduce the grid power consumption of cellular networks through renewable energy without affecting user service quality by utilising a coalitional technique to manage the association between the user and the BS; however, BS-Sw was not considered in this work.…”

Section: Related Work and Contributionsmentioning

confidence: 99%

Energy-Efficient Joint Base Station Switching and Power Allocation for Smart Grid Based Hybrid-Powered CoMP-Enabled HetNet

Euttamarajah

Tan

2021

Future Internet

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With the rapid proliferation of wireless traffic and the surge of various data-intensive applications, the energy consumption of wireless networks has tremendously increased in the last decade, which not only leads to more CO2 emission, but also results in higher operating expenditure. Consequently, energy efficiency (EE) has been regarded as an essential design criterion for future wireless networks. This paper investigates the problem of EE maximisation for a cooperative heterogeneous network (HetNet) powered by hybrid energy sources via joint base station (BS) switching (BS-Sw) and power allocation using combinatorial optimisation. The cooperation among the BSs is achieved through a coordinated multi-point (CoMP) technique. Next, to overcome the complexity of combinatorial optimisation, Lagrange dual decomposition is applied to solve the power allocation problem and a sub-optimal distance-based BS-Sw scheme is proposed. The main advantage of the distance-based BS-Sw is that the algorithm is tuning-free as it exploits two dynamic thresholds, which can automatically adapt to various user distributions and network deployment scenarios. The optimal binomial and random BS-Sw schemes are also studied to serve as benchmarks. Further, to solve the non-fractional programming component of the EE maximisation problem, a low-complexity and fast converging Dinkelbach’s method is proposed. Extensive simulations under various scenarios reveal that in terms of EE, the proposed joint distance-based BS-Sw and power allocation technique applied to the cooperative and harvesting BSs performs around 15–20% better than the non-cooperative and non-harvesting BSs and can achieve near-optimal performance compared to the optimal binomial method.

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Section: Related Work and Contributionsmentioning

confidence: 99%

Energy-Efficient Joint Base Station Switching and Power Allocation for Smart Grid Based Hybrid-Powered CoMP-Enabled HetNet

Euttamarajah

Tan

2021

Future Internet

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“…Using this foundation, a Coalitional Model Predictive Control (C-MPC) strategy was developed and applied on different applications such as cellular networks in [21,22] or an eight-coupled tank process [23]. Thus, the agents charged with controlling the local sub-systems can form coalitions depending on the activation of the communication links between them.…”

Section: Introductionmentioning

confidence: 99%

A Coalitional Distributed Model Predictive Control Perspective for a Cyber-Physical Multi-Agent Application

Maxim

Caruntu

2021

Sensors

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Following the current technological development and informational advancement, more and more physical systems have become interconnected and linked via communication networks. The objective of this work is the development of a Coalitional Distributed Model Predictive Control (C- DMPC) strategy suitable for controlling cyber-physical, multi-agent systems. The motivation behind this endeavour is to design a novel algorithm with a flexible control architecture by combining the advantages of classical DMPC with Coalitional MPC. The simulation results were achieved using a test scenario composed of four dynamically coupled sub-systems, connected through an unidirectional communication topology. The obtained results illustrate that, when the feasibility of the local optimization problem is lost, forming a coalition between neighbouring agents solves this shortcoming and maintains the functionality of the entire system. These findings successfully prove the efficiency and performance of the proposed coalitional DMPC method.

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“…According to [2], the internet subscribers will be uplifted to 59.7% globally by 2022 from 44.3% in 2018 and cellular data traffic will be three times from 2018 to 2021, about 49 exabytes increasing data demand. In addition, 8 billion mobile users are expected to increase by 2030 and over 10% global 5G mobile devices will be connected by 2023, which put an immense pressure to the existing networks and conventional utility grid as well [3]. This volatile escalation of global traffic urges telecom operators to deploy massive number of cellular base stations to handle future demand by fulfilling extra spectrum requirement.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficient Throughput Aware Traffic Load Balancing in Green Cellular Networks

et al. 2021

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With the augmentation of affordable multimedia wireless gadgets, the ubiquitous availability of internet access and the rapid pace of mobile traffic motivate research towards fifth generation (5G) communications to realize energy-efficient cloud radio access networks (C-RAN) with guaranteed quality of experience. Exploiting green energy harvesting for powering the C-RAN substantially alleviates the energy procurement from the utility grid, carbon footprint and operational expenses. In this paper, we propose a new dynamic point selection coordinated multipoint (DPS CoMP) based load balancing paradigm emphasizing on achievable throughput and energy efficiency by reducing utility grid consumption from a network level perspective. This paper investigate the radio efficiency, energy efficiency (EE) and average on-grid energy saving addressing the key challenges of tempo-spatial dynamics of traffic intensity and renewable energy (RE) generation under a wide range of networks setup. Endeavoring load balancing technique strives a balance in network utilities such as green energy utilization and user association based on BS coordination in a cluster. Provision of cell sleep approach is contemplated for energy saving by turning off lightly base stations (BSs) during low traffic arrivals. The proposed CoMP based load balancing algorithm proficiently manages resource block allocation to the new users and elevated the energy efficiency over the conventional location and traffic centric mechanisms. Extensive system-level simulations manifest that the suggested framework enable adjustable trade-off between radio efficiency and EE, and saves 22% on-grid power consumption and increases EE index by 32%. Afterwards, an exhaustive comparison of the proposed method with the existing schemes is pledged for further validation highlighting sustainable 5G wireless systems.INDEX TERMS Energy efficiency, coordinated multipoint, hybrid power supply, centralized RAN, load balancing, cell zooming, green communication.

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A Coalitional Model Predictive Control for the Energy Efficiency of Next-Generation Cellular Networks

Cited by 9 publications

References 39 publications

Energy-Efficient Joint Base Station Switching and Power Allocation for Smart Grid Based Hybrid-Powered CoMP-Enabled HetNet

Energy-Efficient Joint Base Station Switching and Power Allocation for Smart Grid Based Hybrid-Powered CoMP-Enabled HetNet

A Coalitional Distributed Model Predictive Control Perspective for a Cyber-Physical Multi-Agent Application

Energy Efficient Throughput Aware Traffic Load Balancing in Green Cellular Networks

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