Energy Efficiency Of Cellular Networks Research Articles

An Adaptive Cell Switch Off framework to Increase Energy Efficiency in Cellular Networks

An Adaptive Cell Switch Off framework to Increase Energy Efficiency in Cellular Networks

Implementation of small cell antenna based massive MIMO system for high spectrum and energy efficiencies

In order to achieve high data rates (DR) in the fifth generation (5G), Massive Multiple Input Multiple Output (m-MIMO) systems must be altered to boost spectral efficiency. These systems must be used in conjunction with Small Cell Antennas (SCA). When compared to a number of User Terminals (UTs) provided in the same time-frequency resource without significant inter-user interference, m-MIMO enables a significant increase in spectrum efficiency. This is accomplished by deploying a large number of antenna elements at the base station, anywhere from tens to hundreds. The evolution of SC technology has resulted in decreased latency, decreased energy consumption, and increased data rates, all of which are necessary conditions for the deployment of 5G. In this study, we construct an m-MIMO system with SCAs that takes into account partial channel state information. We do this by reaching DR in the lower limit by repeating pilot sequences in time division duplex. In this way, we are able to achieve our goal (TDD). Either implementing massive MIMO at the base stations (BSs) or overlaying SCAs on top of the infrastructure already in place may help improve the energy efficiency of cellular networks. We present some intriguing results that demonstrate that combining Massive MIMO with small cells may be able to drastically cut total power usage. Beam-forming techniques with a low level of complexity, such as the proposed multi-flow RZF beam-forming, also have the potential to

Optimized energy-aware cellular network planning with random waypoint user mobility

In this work, we aim to plan an energy-efficient cellular network that can take into account minimizing the cost and energy of the whole network and minimizing the distance between user and base station. Also, it takes the mobility of users into account using the random waypoint method to represent the user mobility. The design strategy depends on turning off as many base stations as possible to reduce the consumed power while keeping full or partial coverage and quality of service over the serviced area. We have implemented all work by using Matlab software.

A survey on sleep mode techniques for ultra-dense networks in 5G and beyond

The proliferation of mobile users with an attendant rise in energy consumption mainly at the base station has requested new ways of achieving energy efficiency in cellular networks. Many approaches have been proposed to reduce the power consumption at the base stations in response to the contribution of energy cost to the increase of OPEX of the mobile operators and the rise of the carbon footprint on global climate. As a springboard to the application of sleep mode methods in ultra-dense cellular networks, this paper provides a comprehensive survey of the base station sleep mode strategies in heterogeneous mobile networks from perspectives of modeling and algorithm design. Specifically, the sleep mode enabling strategies and sleep wake-up schemes are reviewed. The base station sleep-mode techniques in ultra-dense networks are further discussed as well as the challenges and possible solutions.

Uplink Power Allocation for Throughput and Energy Efficiency in Cellular Networks

Uplink Power Allocation for Throughput and Energy Efficiency in Cellular Networks

Temporal and Spatial Traffic Analysis Based on Human Mobility for Energy Efficient Cellular Network

With the drastic growth of Information and Communication Technology (ICT) industry, global energy consumption is exponentially increased by mobile communications. The huge energy consumption and increased environmental awareness have triggered great interests on the research of dynamic distribution of cell user and traffic, and then designing the energy efficient cellular network. In this paper, we explore the temporal and spatial characteristics of human mobility and traffic distribution using real data set. The analysis results of cell traffic illustrate the tidal effect in temporal and spatial dimensions and obvious periodic characteristics which can be used to design Base Station (BS) dynamic with sleeping or shut-down strategy. At the same time, we designed a new Cell Zooming and BS cooperation mode. Through simulation experiments, we found that running in this mode can save about 35% of energy consumption and guarantee the required quality of service.

Broadcasting Scalable Video With Generalized Spatial Modulation in Cellular Networks

This paper considers the transmission of scalable video via broadcast and multicast to increase spectral and energy efficiency in cellular networks. To address this problem, we study the use of generalized spatial modulation (GSM) combined with non-orthogonal hierarchical M-QAM modulations due to the capability to exploit the potential gains of large scale antenna systems and achieve high spectral and energy efficiencies. We introduce the basic idea of broadcasting/multicasting scalable video associated to GSM, and discuss the key limitations. Non-uniform hierarchical QAM constellations are used for broadcasting/multicasting scalable video while user specific messages are carried implicitly on the indexes of the active transmit antennas combinations. To deal with multiple video and dedicated user streams multiplexed on the same transmission, an iterative receiver with reduced complexity is described. 5G New Radio (NR) based link and system level results are presented. Two different ways of quadruplicating the number of broadcasting programs are evaluated and compared. Performance results show that the proposed GSM scheme is capable of achieving flexibility and energy efficiency gain over conventional multiple input multiple output (MIMO) schemes.

Joint Allocation of Computational and Communication Resources to Improve Energy Efficiency in Cellular Networks

Mobile cloud computing (MCC) is a new technology that has been developed to overcome the restrictions of smart mobile devices (e.g. battery, processing power, storage capacity, etc.) to send a part of the program (with complex computing) to the cloud server (CS). In this paper, we study a multi-cell with multi-input and multi-output (MIMO) system in which the cell-interior users request service for their processing from a common CS. Also, the problem of the optimum offloading is considered as an optimization problem with optimization parameters including communication resources (such as bandwidth, transmit power and backhaul link capacity) and computational resources (such as the capacity of cloud server) in the downlink network. The main goal is to minimize the total energy consumption by mobile users (MUs) for processing with the delay limitation for each use. This issue leads to a non-convex problem and to solve the problem, we use successive convex approximation (SCA) method. We finally show that the joint optimization of these parameters leads to reducing the energy consumption of the network with simulation examples.

Modeling and Analysis of Energy Efficient Cellular Networks

Modeling and Analysis of Energy Efficient Cellular Networks

Optimal Resource and Power Allocation With Relay Selection for RF/RE Energy Harvesting Relay-Aided D2D Communication

Device-to-device (D2D) communication is considered as a promising technology for improving both the spectral and energy efficiencies of cellular networks by reusing the resources of conventional cellular users (CUs) for direct communication of two nearby devices in a spatial manner. When the channel between the two D2D devices is highly attenuated, it is necessary to use an intermediate relay to achieve reliable and flexible relay-aided D2D communication. In order to motivate the cooperative relays to participate, it is assumed that they can harvest energy from radio frequency (RF) signals based on the power splitting (PS) protocol as well as renewable energy (RE) sources. However, resource sharing between the cellular and relay-aided D2D links leads to mutual interference that degrades their sum rate. Considering the energy-harvesting relays (EHRs) and downlink (DL) resource sharing, this paper aims to maximize the sum rate of both the links without degrading the quality of service (QoS) requirements of all users. Our maximization problem is formulated as a mixed-integer nonlinear programming (MINLP) problem that cannot be solved in a straightforward manner. Therefore, we propose a low complexity algorithm, namely the resource and power allocation with relay selection EH-aided algorithm (RPRS-EH), which determines the reuse partners, the PS factor sub-optimal value with optimal links power allocation, and provides two different strategies for optimal relay selection. The numerical results show the behavior of the proposed algorithm under various parameters as well as its considerable performance when compared to one of the most recent algorithms in terms of the links sum rate and relay energy efficiency.

Cellular throughput optimization by game-based power adjustment and outband D2D communication

Device-to-device (D2D) communication is a promising option for the fifth generation (5G) mobile communication network to reduce energy consumption and increase throughput, which makes high throughput applications possible. Also, the improvement for energy and spectrum efficiency is critical in such applications. Without occupation of cellular spectrum resources, outband D2D communication is increasingly applied to high throughput applications to increase spectrum supply. However, energy efficiency is still a key issue that needs to be addressed. Moreover, the overall energy efficiency in cellular networks is severely limited by cell-edge devices. Therefore, in this paper, we apply multi-hop relay-aided outband D2D communication to cellular networks and propose a game-based power adjustment method to address throughput optimization problem. Firstly, we model an interaction relationship of power adjustment for each transmission path as a potential game, where a new utility function is designed for each player (i.e., the receiving end of a transmission path) to evaluate its action gain and to determine whether taking action or not. And then, it is proved that the utility function is an ordinal potential function (OPF) and the game of power adjustment is an ordinal potential game (OPG), which guarantees the convergence of game decision process. Moreover, we propose a new game decision algorithm, which has quicker convergence speed than the existing typical algorithm. In addition, we design a network-assisted distributed processing architecture for solving throughput optimization problem, including receiving mode selection, verification for relay selection, and transmission power adjustment, which can ease the burden of centralized processing. The experimental results show that our scheme is superior to the existing typical work in terms of throughput, delay, energy efficiency, continuous service ability, and convergence performance.

Energy efficiency analysis of multi-antenna cellular networks with strategic sleep relay

Energy efficiency (EE) of cellular networks has attracted considerable attention recently. However, EE of relay-assisted cellular networks where the macro base stations (MBSs) are equipped with the multi-antenna has not been thoroughly addressed. This paper considered the downlink transmission of multi-antenna relay-assisted cellular networks, meanwhile, a strategic sleep scheme was used in relay stations (RSs), which dynamically adjusted the RS working mode according to whether the number of users serviced by the relay exceeds a given threshold. A geometric model was built to derive the coverage probability and mean achievable rate from the MBSs to user (UE), the MBS to RS, the RS to UE links and analyze the system EE. It is shown that the energy efficiency of cellular network with strategic sleep RS is slightly higher than that of cellular network with non-sleeping strategy. Furthermore, the MBS equipped with multi-antenna has better impact on energy efficiency and spectral efficiency than the MBS with single antenna.

Optimal Mode Selection Algorithms in Multiple Pair Device-to-Device Communications

Device-to-Device (D2D) communications have been proposed to improve spectrum and energy efficiency of cellular networks. One of the most critical issues in D2D networks is the selection of the communication modes for multiple D2D pairs in a cell. In this article, relay-assisted mode, in addition to basic cellular and direct D2D modes, is taken into account to improve the link performance of D2D pairs. We investigate the optimal mode selection schemes to maximize cell-wise capacity based on the reuse of cellular uplink channels in different multi-pair D2D communication scenarios. We discover that the optimal mode selection problem can be transformed into a linear programming problem with polynomial computational complexity. The exact analytical solutions for optimal mode selection are derived and can be useful to cellular operators to maximize the cellwise capacity.

Energy- and Spectral-Efficiency Trade-Off for D2D-Multicasts in Underlay Cellular Networks

Underlay in-band device-to-device (D2D) multicast communication, where the same content is disseminated via direct links in a group, has the potential to improve the spectral and energy efficiencies of cellular networks. However, most of the existing approaches for this problem only address either spectral efficiency (SE) or energy efficiency (EE). We study the tradeoff between SE and EE in a single cell D2D integrated cellular network, where multiple D2D multicast groups (MGs) may share the uplink channel with multiple cellular users. We explore SE-EE tradeoff for this problem by formulating the EE maximization problem with constraint on SE and maximum available transmission power. A power allocation algorithm is proposed to solve this problem and its efficacy is demonstrated via extensive numerical simulations. The tradeoff between SE and EE as a function of density of D2D MGs, and maximum transmission power of an MG is characterized.

An energy aware user‐centric cooperative mode switching scheme for 5G networks

In this paper, we propose an user‐centric energy efficient relay‐based cellular mode switching scheme for fifth generation cellular networks. It is a feasible approach to tackle the increased network demands of wireless industry, while improving the quality of experience (QoE). We also introduce a dynamic relay management algorithm, where the network will guarantee the preset QoE measurement parameters. If the source and target mobile nodes are within the proximity area, then the system switches to device‐centric mode. In order to improve the network performance, the system may select relay nodes (RNs). If the performance metrics are less than the threshold value, then the network adds additional RN(s) where necessary. The proposed work offers less signaling overhead as compared to modern cellular state‐of‐art networks such as 4G/LTE. This is a key component related to energy efficient cellular networks. The numerical analysis demonstrates the performance improvement in terms of energy consumption with a high degree of movement probability.

An Efficient IR-HARQ Power Allocation for Relay-Aided Cellular Networks

Energy-efficient and reliable data transmission is a challenging task in wireless relay networks (WRNs). Energy efficiency in cellular networks has received significant attention because of the present need for reduced energy consumption, thereby maintaining the profitability of networks, which in turn makes these networks “greener”. The urban cell topography needs more energy to cover the total area of the cell. The base station does not cover the entire area in a given topography and adding more number of base stations is a cost prohibitive one. Energy-efficient relay placement model which calculates the maximum cell coverage is proposed in this work that covers all sectors and also an energy-efficient incremental redundancy-hybrid automatic repeat request (IR-HARQ) power allocation scheme to improve the reliability of the network by improving the overall network throughput is proposed. An IR-HARQ power allocation method maximizes the average incremental mutual information at each round, and its throughput quickly converges to the ergodic channel capacity as the number of retransmissions increases. Simulation results show that the proposed IR-HARQ power allocation achieves full channel capacity with average transmission delay and maintains good throughput under less power consumption. Also the impact of relaying performance on node distances between relay station and base station as well as between user and relay station and relay height for line of sight conditions are analyzed using full decode and forward (FDF) and partial decode and forward (PDF) relaying schemes. Compared to FDF scheme, PDF scheme provides better performance and allows more freedom in the relay placement for an increase in cell coverage.

An optimal dynamic sleeping control policy for single base stations in green cellular networks

Energy efficiency of cellular networks can be greatly improve if base stations (BSs) can be put into a low power operation mode during low load periods. In this paper, we present a new dynamic scheme to manage the sleep mode of energy-aware BSs that can be autonomously governed. This kind of BSs, such as those operating in heterogeneous or hyper-cellular networks, can be put to sleep without causing undesired coverage holes, thus preserving the cellular service over the whole coverage area. With the proposed mechanism, energy-aware BSs enter the sleep mode as soon as they have no traffic to send and then apply a coalescing algorithm that dynamically adjusts the length of the sleeping periods to maximize the energy savings while maintaining the average service delay around a target value at the same time.

Spatial spectral and energy efficiencies of cellular networks limited by co-channel interference and path loss in Nakagami-m fading environment

A comprehensive framework for design of hexagonal cellular network system in terms of spatial spectral and energy efficiencies is presented. The communication environment in the system is assumed to be Nakagami-m fading coupled with simplified path loss model and co-channel interference. Three base station antenna configurations namely, omni, 120° and 60° are considered. Closed-form expressions for spatial spectral and energy efficiencies and coverage probability are derived and illustrated as a function of signal-to-noise ratio, cell radius, reuse distance, path loss exponent factor, and fading figure. A discussion of trade-offs among spatial spectral efficiency, spatial energy efficiency, and coverage probability as a function of parameters of cellular system and propagation environment is also provided. Numerical results show that the use of sectorized antenna system in the cellular network provides significant improvements even under severe propagation and interference conditions. For example, it is observed that the 120° base station antenna configuration system provides nearly double the spatial energy efficiency relative to the omni configuration system.

A Study of Densification Management Using Energy Efficient Femto-Cloud Based 5G Mobile Network

Energy efficiency in wireless communication becomes essential. Power optimization of mobile radio systems has gained attention of network operators because energy costs make up a huge part of operational expenditure. In this regard, deployments of low power small cell base stations considerably raise the challenge of energy-efficient cellular networks. Network densification refers to densification over space, for example dense small cell deployment like picocell, femtocell, and frequency utilization of larger segments of radio spectrum in dissimilar bands. In this article we have illustrated the cause factors of densification and described its effects. The deployment layouts of different base stations are studied and compared with conventional macro-femtocell systems from the perspective of area power consumption and signal-to-interference-plus-noise-ratio.

System-Level Modeling and Optimization of the Energy Efficiency in Cellular Networks—A Stochastic Geometry Framework

In this paper, we analyze and optimize the energy efficiency of downlink cellular networks. With the aid of tools from stochastic geometry, we introduce a new closed-form analytical expression of the potential spectral efficiency (bit/sec/m2). In the interference-limited regime for data transmission, unlike currently available mathematical frameworks, the proposed analytical formulation depends on the transmit power and deployment density of the base stations. This is obtained by generalizing the definition of coverage probability and by accounting for the sensitivity of the receiver not only during the decoding of information data, but during the cell association phase as well. Based on the new formulation of the potential spectral efficiency, the energy efficiency (bit/Joule) is given in a tractable closed-form formula. An optimization problem is formulated and is comprehensively studied. It is mathematically proved, in particular, that the energy efficiency is a unimodal and strictly pseudo-concave function in the transmit power, given the density of the base stations, and in the density of the base stations, given the transmit power. Under these assumptions, therefore, a unique transmit power and density of the base stations exist, which maximize the energy efficiency. Numerical results are illustrated in order to confirm the obtained findings and to prove the usefulness of the proposed framework for optimizing the network planning and deployment of cellular networks from the energy efficiency standpoint.