Energy efficiency based on relay station deployment and sleep mode activation of eNBs for 4G LTE-A network
TL;DR: A novel relay station (RS) deployment scheme and base station (BS) sleep mode algorithm is proposed to minimize the power consumption of eNBs and the evaluation results show the efficiency of the proposed work.
Abstract: The energy efficiency is considered as a major issue due to large power consumption of eNBs in heterogeneous cellular networks. In this paper, a novel relay station (RS) deployment scheme a...
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TL;DR: This paper presents a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with a flexible mode selection scheme along with truncated channel inversion power control and provides guidelines for selecting the network parameters.
Abstract: Device-to-device (D2D) communication enables the user equipments (UEs) located in close proximity to bypass the cellular base stations (BSs) and directly connect to each other, and thereby, offload traffic from the cellular infrastructure. D2D communication can improve spatial frequency reuse and energy efficiency in cellular networks. This paper presents a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with a flexible mode selection scheme along with truncated channel inversion power control. Different from the existing mode selection schemes where the decision on mode selection is made based only on the D2D link distance (i.e., distance between two UEs using D2D mode of communication), the proposed mode selection scheme for a UE accounts for both the D2D link distance and cellular link distance (i.e., distance between the UE and the BS). The developed framework is used to analyze and understand how the underlaying D2D communication affects the cellular network performance. Through comprehensive numerical analysis, we investigate the expected performance gains and provide guidelines for selecting the network parameters.
26 citations
16 May 2020
TL;DR: In this paper, the authors discuss the implementation of mobility prediction for resource management in mobile communication networks and discuss the challenges expected from 5G networks with related statistical facts, predictive mobility management is introduced with its distinctive applications.
Abstract: Owing to the challenging nature of emerging applications, such as augmented reality, 4 K video streaming, and remote surgery, 5G networks are expected to deal with a broad range of issues including higher data rate provision, less energy consumption, lower latency, etc.
Therefore, intelligent and proactive network management is envisioned to be an integral part of 5G in order to make the communication networks more agile, dynamic, and efficient. In this regard, mobility prediction has gained a significant amount of attention owing to their diverse application domains.
This article focuses on discussing the implementation of mobility prediction for resource management in mobile communication networks. After describing the challenges expected from 5G networks with related statistical facts, predictive mobility management is introduced with its distinctive applications.
After that, the use of mobility prediction in communication networks is elaborated according to different resource types, such as radio, energy, and built‐in resources, and the corresponding state‐of‐the‐art literature is classified accordingly.
1 citations
1 citations
29 Jan 2021
TL;DR: A new approach to the management of the base stations and the relay stations is introduced using a fuzzy dynamic distribution of the BSs and RSs in the center according to the distribution of users using a sleep mode activation of these stations which is seen as the key to reducing grid power consumption.
Abstract: In the current generation of cellular networks, practitioners and researchers have shown a keen interest in green wireless communication due to its capability to create eco-efficient networks. To adapt to the increase in traffic and services for all mobile subscribers, Base stations (BSs) and relay stations (RSs) must be deployed more and more in order to meet the growth in this demand. However, increasing the number of BSs or RSs can increase energy consumption and reduce efficiency as it is responsible for large carbon dioxide (CO2) emissions. In this paper, we introduce a new approach to the management of the base stations and the relay stations using a fuzzy dynamic distribution of the BSs and RSs in the center according to the distribution of users. We use, secondly, a sleep mode activation of these stations which is seen as the key to reducing grid power consumption. The performance and the effectiveness of the proposed approach are clarified by a simulation example that reveals the capacity of our strategy in reducing energy consumption.
TL;DR: In this paper , a traffic-based power consumption minimization and node deployment for the LTE green cellular networks is proposed, which aims to maximize the coverage area, minimize the overlapping area and minimize the power consumption cost.
Abstract: The energy utilization of green cellular networking or cellular network infrastructure has become a popular research domain due to the economic concern of network operators and global climate change. Also, due to the growth of wireless networks, the authors are attracted to finding novel relay station (RS) deployment techniques to support high user density and high data rate services by reducing energy consumption and operating costs of different network elements. The location of RSs greatly influences how far a cell can be covered. Therefore, the deployment RS plays a major role in widening the cell's coverage radius. To solve these challenges and to realize greener network designs by maximizing power consumption with QoS assurance, a novel traffic-based power consumption minimization and node deployment for the LTE green cellular networks is proposed. Also, key performance indicators (KPIs) are required to monitor and improve network performance. KPIs control the accomplished resource utilization and the quality of services. The research work comprises RS deployment, traffic estimation, and power allocation. Power losses, communication delays, increased implementation costs, and decreased throughput are the effects of an inappropriate RS deployment. Therefore, this research introduces the transmission area-based relay stations deployment scheme (TARSD) with multiobjective functions maximization of coverage area, minimization of the overlapping area and the minimization of power consumption cost. Traffic estimation helps to identify future capacity requirements and enables improved planning and decision-making. The deployment scheme of a cellular network relies on network traffic estimation. Nash traffic entropy learning algorithm (NTEL) is used to estimate traffic, and based on the estimated eNB switching ON/OFF is performed to minimize power consumption. Inter cell interference (ICI) can impact the performance of the LTE network. Several power allocation schemes can be used to improve system performance to achieve the optimal trade-off between interference and signal-to-noise ratio (SINR). Because of its good performance and efficacy in improving the mutual information between a channel's input and output, the enhanced low complexity water-filling (ELCWF) has been widely employed in power allocation with its increment and decrement properties. This research studies the statistical behaviour of a Received Signal Strength Indicator (RSSI), Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ) and Signal to Interference noise Ratio (SINR). Also, statistical analysis of cost versus coverage performance is examined. Under the 7th simulation run, the proposed method yields the best coverage of 88.81 and 98.74%, respectively. In the experimental scenario, for the proposed model, the deployment cost for BS and RS are 27 and 13 units, the average throughput per user is 9.74 Mbps, and the coverage ratio is 97% under the BS candidate location of 20, respectively. In the power allocation stage, if the number of users is 50, the proposed model yields a power consumption of 0.2 watts, throughput of 23.4 Mbps, delay of 15ms and SINR of 20.12dB, respectively.
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TL;DR: A potential cellular architecture that separates indoor and outdoor scenarios is proposed, and various promising technologies for 5G wireless communication systems, such as massive MIMO, energy-efficient communications, cognitive radio networks, and visible light communications are discussed.
Abstract: The fourth generation wireless communication systems have been deployed or are soon to be deployed in many countries. However, with an explosion of wireless mobile devices and services, there are still some challenges that cannot be accommodated even by 4G, such as the spectrum crisis and high energy consumption. Wireless system designers have been facing the continuously increasing demand for high data rates and mobility required by new wireless applications and therefore have started research on fifth generation wireless systems that are expected to be deployed beyond 2020. In this article, we propose a potential cellular architecture that separates indoor and outdoor scenarios, and discuss various promising technologies for 5G wireless communication systems, such as massive MIMO, energy-efficient communications, cognitive radio networks, and visible light communications. Future challenges facing these potential technologies are also discussed.
2,048 citations
"Energy efficiency based on relay st..." refers background in this paper
...The cellular network plays a major role for the deployment of efficient communication system [1]....
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TL;DR: This paper proposes a practically implementable switching-on/off based energy saving algorithm that can be operated in a distributed manner with low computational complexity and describes how the proposed algorithms can be implemented in practice at the protocol-level and also estimates the amount of energy savings through a first-order analysis in a simple setting.
Abstract: In this paper, we investigate dynamic base station (BS) switching to reduce energy consumption in wireless cellular networks. Specifically, we formulate a general energy minimization problem pertaining to BS switching that is known to be a difficult combinatorial problem and requires high computational complexity as well as large signaling overhead. We propose a practically implementable switching-on/off based energy saving (SWES) algorithm that can be operated in a distributed manner with low computational complexity. A key design principle of the proposed algorithm is to turn off a BS one by one that will minimally affect the network by using a newly introduced notion of network-impact, which takes into account the additional load increments brought to its neighboring BSs. In order to further reduce the signaling and implementation overhead over the air and backhaul, we propose three other heuristic versions of SWES that use the approximate values of network-impact as their decision metrics. We describe how the proposed algorithms can be implemented in practice at the protocol-level and also estimate the amount of energy savings through a first-order analysis in a simple setting. Extensive simulations demonstrate that the SWES algorithms can significantly reduce the total energy consumption, e.g., we estimate up to 50-80% potential savings based on a real traffic profile from a metropolitan urban area.
397 citations
"Energy efficiency based on relay st..." refers background in this paper
...Switching on/off based dynamic BS operations permits the entire system of BS to turn off at low network traffic periods for significant power saving [13]....
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TL;DR: It is shown here that considering the effect of traffic-load-dependent factors on energy consumption may lead to noticeably lower benefit than in models that ignore this effect, and potential future research directions are discussed.
Abstract: Due to global climate change as well as economic concern of network operators, energy consumption of the infrastructure of cellular networks, or “Green Cellular Networking,” has become a popular research topic. While energy saving can be achieved by adopting renewable energy resources or improving design of certain hardware (e.g., power amplifier) to make it more energy-efficient, the cost of purchasing, replacing, and installing new equipment (including manpower, transportation, disruption to normal operation, as well as associated energy and direct cost) is often prohibitive. By comparison, approaches that work on the operating protocols of the system do not require changes to current network architecture, making them far less costly and easier for testing and implementation. In this survey, we first present facts and figures that highlight the importance of green mobile networking and then review existing green cellular networking research with particular focus on techniques that incorporate the concept of the “sleep mode” in base stations. It takes advantage of changing traffic patterns on daily or weekly basis and selectively switches some lightly loaded base stations to low energy consumption modes. As base stations are responsible for the large amount of energy consumed in cellular networks, these approaches have the potential to save a significant amount of energy, as shown in various studies. However, it is noticed that certain simplifying assumptions made in the published papers introduce inaccuracies. This review will discuss these assumptions, particularly, an assumption that ignores the effect of traffic-load-dependent factors on energy consumption. We show here that considering this effect may lead to noticeably lower benefit than in models that ignore this effect. Finally, potential future research directions are discussed.
384 citations
"Energy efficiency based on relay st..." refers background in this paper
...The deployment of cellular network based on smaller cells such as pico, micro and femto cells provides benefits in terms of energy reduction, high data rate and cost efficiency [9]....
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TL;DR: An iterative gradient user association and power allocation algorithm is proposed and shown to converge rapidly to an optimal point.
Abstract: Millimeter wave (mmWave) communication technologies have recently emerged as an attractive solution to meet the exponentially increasing demand on mobile data traffic. Moreover, ultra dense networks (UDNs) combined with mmWave technology are expected to increase both energy efficiency and spectral efficiency. In this paper, user association and power allocation in mmWave-based UDNs is considered with attention to load balance constraints, energy harvesting by base stations, user quality of service requirements, energy efficiency, and cross-tier interference limits. The joint user association and power optimization problem are modeled as a mixed-integer programming problem, which is then transformed into a convex optimization problem by relaxing the user association indicator and solved by Lagrangian dual decomposition. An iterative gradient user association and power allocation algorithm is proposed and shown to converge rapidly to an optimal point. The complexity of the proposed algorithm is analyzed and its effectiveness compared with existing methods is verified by simulations.
367 citations
"Energy efficiency based on relay st..." refers methods in this paper
...The complexity of the proposed algorithm was analyzed and its effectiveness was compared with existing methods in the simulations [24]....
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TL;DR: In this paper, the authors present a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with a flexible mode selection scheme along with truncated channel inversion power control.
Abstract: Device-to-device (D2D) communication enables the user equipments (UEs) located in close proximity to bypass the cellular base stations (BSs) and directly connect to each other, and thereby, offload traffic from the cellular infrastructure. D2D communication can improve spatial frequency reuse and energy efficiency in cellular networks. This paper presents a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with a flexible mode selection scheme along with truncated channel inversion power control. The developed framework is used to analyze and understand how the underlaying D2D communication affects the cellular network performance. Through comprehensive numerical analysis, we investigate the expected performance gains and provide guidelines for selecting the network parameters.
348 citations