A New Heuristic Algorithm for Energy and Spectrum Efficient User Association in 5G Heterogeneous Networks

Javad-Kalbasi, Mohammad; Naghsh, Zahra; Mehrjoo, Mehri; Valaee, Shahrokh

doi:10.1109/pimrc48278.2020.9217199

Cited by 6 publications

(3 citation statements)

References 13 publications

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“…• Average Network Energy Efficiency An important consideration while creating cell selection methods is energy efficiency (EE). It is the entire data rates that can be achieved divided by the total power used [75]. Equation (29) provides the energy efficiency formula, which is expressed in bits/joules.…”

Section: B Evaluation Of the Proposed A2t-boost 1) Evaluation Metricsmentioning

confidence: 99%

A2T-Boost: An Adaptive Cell Selection Approach for 5G/SDN-Based Vehicular Networks

Alablani

Arafah²

2023

IEEE Access

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Heterogeneous ultra-dense networks (HUDNs) are one of the key enabling technologies for the fifth-generation (5G) networks. They aim to provide high capacity, low installation cost, and distributed traffic loads. The cell selection is a challenging issue in HUDNs, due to the different characteristics of base stations (BSs) and the existence of a large number of them. Thus, the traditional cell selection scheme is not applicable in such a network. In this paper, a novel adaptive cell selection strategy is proposed, called adaptive two-tier based on adaptive boosting (A2T-Boost). It can adapt to the various characteristics of base stations, as well as the different movement features of mobile stations such as vehicles and pedestrian. It is a software-defined networking (SDN)/machine learning (ML)-based scheme. A real-world case is considered in the downtown of Los Angeles city. Simulation results demonstrate that A2T-Boost achieves high prediction performance and it outperforms other related schemes in terms of average number of handovers (HOs) by up to 50%. Moreover, it enhances the average achievable downlink sum-rates and network energy efficiency achieved by vehicles by up to 33.76%. Furthermore, the average packet delay is decreased using the proposed scheme by up to 12.87%.

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Section: B Evaluation Of the Proposed A2t-boost 1) Evaluation Metricsmentioning

confidence: 99%

A2T-Boost: An Adaptive Cell Selection Approach for 5G/SDN-Based Vehicular Networks

Alablani

Arafah²

2023

IEEE Access

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“…where C m and C p represent respectively the power consumed by the BS of the Macrocell and the Picocell, C o m and C o p represent respectively for each type of cell the power consumed at zero loads, and c represents the charge percentage. The study [22] published in the Huawei 5G white paper shows that the average power consumption of a BS 5G is about 300% to 350% greater than that of 4G BS. This study used field data from a Chinese operator to compare the average energy consumption between a 4G BS and a 5G BS at different load levels.…”

Section: B Energy Consumption Modelingmentioning

confidence: 99%

Towards Sustainable 5G Networks: A Proposed Coordination Solution for Macro and Pico Cells to Optimize Energy Efficiency

et al. 2023

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The 5th generation of mobile communications, currently being rolled out, aims to improve network performance and efficiency over the older generations. With mmWaves, densified cell deployment is necessary for 5G networks, increasing capacity and improving network coverage. This imposes a considerable increase in the energy consumption of the 5G stations, which not only increases operating expenses for operators but also burdens the environment. Optimizing the energy consumption of 5G networks would be necessary to curb the energy curve. In this context, this paper presents a new algorithm called Energy Consumption Optimization Algorithm (ECOA), which combines cell selection and standby techniques to optimize energy consumption while preserving network performance. A comparison is conducted between ECOA and standard cell selection modes to evaluate the performance of the conventional approach. Our algorithm exhibits good performance, particularly in high-density, high-load scenarios. For instance, in a site with 25 Pico base stations serving 500 users, our algorithm achieves an average throughput of 23 Mb/s per user while consuming 1750.75 W of energy. This represents a 2.44% increase in energy consumption compared to the optimal solution.

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“…In [ 29 ], the maximum secure area is considered. There are also papers that consider energy efficiency as association policy as in [ 30 , 31 , 32 , 33 ]. In [ 34 ], the transmission power is minimized by minimizing the number of active small-cells with a constraint on the minimum achievable rate.…”

Section: Introductionmentioning

confidence: 99%

User-Cell Association for Security and Energy Efficiency in Ultra-Dense Heterogeneous Networks

Marabissi

Mucchi

Morosi

2021

Sensors

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The last decades have been characterized by an exponential increase in digital services. The demand is foreseen to further increase in the next years, and mobile networks will have to mandatorily supply connections to enable digital services with very different requirements, from ultra high speed to ultra low latency. The deployment and the coexistence of cells of different size, from femto to macro, will be one of the key elements for providing such pervasive wireless connection: the ultra dense networks (UDN) paradigm. How to associate users and base stations is one of the most investigated research topics. Many criteria can be drawn, from minimization of power consumption to optimization of throughput. In this paper we propose a new utility to optimize two of the most important features of future mobile connection: security and energy consumption. By using our utility it is possible to jointly select the base station to be activated in a UDN, and associate users to the base stations with the aim of maximizing the secure throughput by spending the minimum energy. Moreover, we propose a heuristic that allows to achieve performance very close to the optimal one with reduced complexity. Effectiveness of the proposed approach is proved by means of comparison with benchmark approaches.

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A New Heuristic Algorithm for Energy and Spectrum Efficient User Association in 5G Heterogeneous Networks

Cited by 6 publications

References 13 publications

A2T-Boost: An Adaptive Cell Selection Approach for 5G/SDN-Based Vehicular Networks

A2T-Boost: An Adaptive Cell Selection Approach for 5G/SDN-Based Vehicular Networks

Towards Sustainable 5G Networks: A Proposed Coordination Solution for Macro and Pico Cells to Optimize Energy Efficiency

User-Cell Association for Security and Energy Efficiency in Ultra-Dense Heterogeneous Networks

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