scholarly journals Energy-Efficient and Reliable Internet of Things for 5G: A Framework for Interference Control

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2165
Author(s):  
Radwa Ahmed Osman ◽  
Amira I. Zaki
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Cellular Networks ◽  
Communication Networks ◽  
Network Performance ◽  
Optimization Technique ◽  
Base Station ◽  
Optimization Strategy ◽  
Interference Control ◽  
Proposed Model

The Internet of Things (IoT) is one of the promising paradigms that enable massive machines and devices to communicate with each other in future communication networks to promote a high level of awareness about our world and improve our daily life. IoT devices (IoTDs) communicate with an IoT base station (IoTBS) or IoT gateway (IoTG) by sharing the resources of other cellular users (CUEs). Due to the leakage of the spectral efficiency, interference exists among IoTG and base station (BS) due to CUEs and IoTDs. In this paper, a new framework is proposed called the interference control model. This proposed model aims to control the interference among IoTG and BS and is based on using the Lagrange optimization technique to reduce interference and maximize the energy efficiency and reliability of the IoT and cellular networks in fifth-generation (5G) systems. First, we formulate the multi-objective optimization problem to achieve the objective of the proposed model. Then, based on the optimization strategy, we derive the closed-form expressions of key quality-of-service (QoS) performance such as system reliability, throughput, and energy efficiency. Finally, the proposed algorithm has been evaluated and examined through different assumptions and several simulation scenarios. The obtained results validate the effectiveness and the accuracy of our proposed idea and also indicate significant improvement in the network performance of IoT and cellular networks.

scholarly journals Energy Efficiency Analysis of Cache-Enabled Cellular Networks with Limited Backhaul

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Congshan Fan ◽  
Tiankui Zhang ◽  
Zhimin Zeng ◽  
Yue Chen
Keyword(s):  
Energy Efficiency ◽  
Cellular Networks ◽  
Network Performance ◽  
Content Delivery ◽  
Base Station ◽  
Library Size ◽  
Improve Energy Efficiency ◽  
Delivery Probability ◽  
Content Popularity ◽  
Geometry Method

Caching in the cellular networks has been proposed as a promising technology for reducing the content delivery latency and backhaul cost. Since the backhaul capacity is limited in the practical scenario, the network performance analysis of base station (BS) caching should address the effects of the limited backhaul. This paper investigates the energy efficiency of the cache-enabled cellular networks with the limited backhaul based on the stochastic geometry method. First, the successful content delivery probability (SCDP), which depends on the successful access delivery probability, successful backhaul delivery probability, and cache hit ratio, is analyzed under the limited backhaul. Based on the obtained SCDP results, we derive the analytical expressions of throughput, power consumption, and energy efficiency for various scenes including the general case, the interference-limited case, and the mean load approximation case. The accuracy of theoretical analysis is verified by the Monte Carlo simulation. The simulation results show that BS caching can dramatically improve energy efficiency when the content popularity is skewed, the content library size is small, and the backhaul capacity is relatively small. Furthermore, it is confirmed that there exists an optimal BS density which maximizes the energy efficiency of the cache-enabled cellular networks.

scholarly journals Energy Efficiency Maximization for UAV-Assisted Emergency Communication Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Haibin Niu ◽  
Xinyu Zhao ◽  
Liming Hou ◽  
Dongjun Ma
Keyword(s):  
Energy Efficiency ◽  
Communication Networks ◽  
Nonconvex Optimization ◽  
Bandwidth Allocation ◽  
Optimization Problem ◽  
Energy Savings ◽  
Low Cost ◽  
Optimization Technique ◽  
Base Station ◽  
Effective Capacity

Using unmanned aerial vehicles (UAVs) in emergency communications is a promising technology because of their flexible deployment, low cost, and high mobility. However, due to the limited energy of the onboard battery, the service duration of the UAV is greatly limited. In this paper, we study an emerging energy-efficient UAV emergency network, where a UAV works as an aerial base station to serve a group of users with different statistical quality-of-service (QoS) constraints in the downlink. In particular, the energy efficiency of the UAV is defined as the sum effective capacity of the downlink users divided by the energy consumption of the UAV, which includes the energy consumed by communication and the energy consumed by hovering. Then, we formulate an optimization problem to maximize the energy efficiency of the UAV by jointly optimizing the UAV’s altitude, downlink transmit power, and bandwidth allocation while meeting a statistical delay QoS requirement for each user. The formulated optimization problem is a nonlinear nonconvex optimization problem of fractional programming, which is difficult to solve. In order to deal with the nonconvex optimization problem, the following two steps are used. First, we transform the fractional objective function into a tractable subtractive function. Second, we decompose the original optimization problem into three subproblems, and then, we propose an efficient iterative algorithm to obtain the energy efficiency maximization value by using the Dinkelbach method, the block coordinate descent, and the successive convex optimization technique. Extensive simulation results show that our proposed algorithm has significant energy savings compared with a benchmark scheme.

Call-Level Performance Analysis of a Power Line Communication Network Under Disturbance

2011 ◽  
Vol 12 (3) ◽  
Author(s):  
Shensheng Tang ◽  
Yi Xie
Keyword(s):  
Communication Networks ◽  
Orthogonal Frequency Division Multiplexing ◽  
Performance Metrics ◽  
Steady State Solution ◽  
Power Line ◽  
Base Station ◽  
Channel Noise ◽  
Power Line Communication ◽  
Proposed Model ◽  
Level Performance

Power line communication (PLC) is a promising technique for information transmission using existing power lines. We analytically model a finite-source PLC network subject to channel noise (disturbance) and evaluate its call-level performance through a queueing theoretic framework. The proposed PLC network model consists of a base station (BS), which is located at a transformer station and connected to the backbone communication networks, and a number of subscriber stations that are interconnected with each other and with the BS via the power line transmission medium. An orthogonal frequency division multiplexing based transmission technique is assumed to be used for providing the transmission channels in a frequency spectrum. The channels are subject to failure during service due to disturbance. We determine the steady-state solution of the proposed model and derive a set of performance metrics of interest. Numerical and simulation results are presented to show the derived metrics with respect to different system parameters. The proposed modeling method can be used for evaluation and design of future PLC networks.

scholarly journals A Novel Interference Avoidance Based on a Distributed Deep Learning Model for 5G-enabled IoT

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6555
Author(s):  
Radwa Ahmed Osman ◽  
Sherine Nagy Saleh ◽  
Yasmine N. M. Saleh
Keyword(s):  
Energy Efficiency ◽  
Deep Learning ◽  
Optimization Technique ◽  
Data Communication ◽  
Learning Model ◽  
Base Station ◽  
System Throughput ◽  
Interference Avoidance ◽  
5G Networks ◽  
Deep Learning Model

The co-existence of fifth-generation (5G) and Internet-of-Things (IoT) has become inevitable in many applications since 5G networks have created steadier connections and operate more reliably, which is extremely important for IoT communication. During transmission, IoT devices (IoTDs) communicate with IoT Gateway (IoTG), whereas in 5G networks, cellular users equipment (CUE) may communicate with any destination (D) whether it is a base station (BS) or other CUE, which is known as device-to-device (D2D) communication. One of the challenges that face 5G and IoT is interference. Interference may exist at BSs, CUE receivers, and IoTGs due to the sharing of the same spectrum. This paper proposes an interference avoidance distributed deep learning model for IoT and device to any destination communication by learning from data generated by the Lagrange optimization technique to predict the optimum IoTD-D, CUE-IoTG, BS-IoTD and IoTG-CUE distances for uplink and downlink data communication, thus achieving higher overall system throughput and energy efficiency. The proposed model was compared to state-of-the-art regression benchmarks, which provided a huge improvement in terms of mean absolute error and root mean squared error. Both analytical and deep learning models reached the optimal throughput and energy efficiency while suppressing interference to any destination and IoTG.

A Super Base Station Architecture for Future Ultra-Dense Cellular Networks: Toward Low Latency and High Energy Efficiency

2018 ◽  
Vol 56 (6) ◽  
pp. 35-41 ◽  
Author(s):  
Mingjin Gao ◽  
Jun Li ◽  
Dushantha Nalin K. Jayakody ◽  
He Chen ◽  
Yonghui Li ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Cellular Networks ◽  
High Energy ◽  
Base Station ◽  
Low Latency ◽  
High Energy Efficiency

scholarly journals Cell Throughput based Sleep Control Scheme for Heterogeneous Cellular Networks

2018 ◽  
Vol 12 (1) ◽  
pp. 26-33
Author(s):  
Prapassorn Phaiwitthayaphorn ◽  
Kazuo Mori ◽  
Hideo Kobayashi ◽  
Pisit Boonsrimuang
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Cellular Networks ◽  
Operating Cost ◽  
Reducing Power ◽  
Network Capacity ◽  
Base Station ◽  
Base Stations ◽  
Improve Energy Efficiency ◽  
Sleep Control

The mobile traffic continuously grows at a rapid rate driven by the widespread use of wireless devices. Along with that, the demands for higher data rate and better coverage lead to increase in power consumption and operating cost of network infrastructure. The concept of heterogeneous networks (HetNets) has been proposed as a promising approach to provide higher coverage and capacity for cellular networks. HetNet is an advanced network consisting of multiple kinds of base stations, i.e., macro base station (MBS), and small base station (SBS). The overlay of many SBSs into the MBS coverage can provide higher network capacity and better coverage in cellular networks. However, the dense deployment of SBSs would cause an increase in the power consumption, leading to a decrease in the energy efficiency in downlink cellular networks. Another technique to improve energy efficiency while reducing power consumption in the network is to introduce sleep control for SBSs. This paper proposes cell throughput based sleep control which the cell capacity ratio for the SBSs is employed as decision criteria to put the SBSs into a sleep state. The simulation results for downlink communications demonstrate that the proposed scheme improves the energy efficiency, compared with the conventional scheme.

scholarly journals Stochastic Geometry Analysis of Downlink Spectral and Energy Efficiency in Ultradense Heterogeneous Cellular Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Jiaqi Lei ◽  
Hongbin Chen ◽  
Feng Zhao
Keyword(s):  
Energy Efficiency ◽  
Cellular Networks ◽  
Stochastic Geometry ◽  
Density Ratio ◽  
Base Station ◽  
Small Cell ◽  
Base Stations ◽  
Heterogeneous Cellular Networks ◽  
Downlink Throughput ◽  
The Impact

The energy efficiency (EE) is a key metric of ultradense heterogeneous cellular networks (HCNs). Earlier works on the EE analysis of ultradense HCNs by using the stochastic geometry tool only focused on the impact of the base station density ratio and ignored the function of different tiers. In this paper, a two-tier ultradense HCN with small-cell base stations (SBSs) and user equipments (UEs) densely deployed in a traditional macrocell network is considered. Firstly, the performance of the ultradense HCN in terms of the association probability, average link spectral efficiency (SE), average downlink throughput, and average EE is theoretically analyzed by using the stochastic geometry tool. Then, the problem of maximizing the average EE while meeting minimum requirements of the average link SE and average downlink throughput experienced by UEs in macrocell and small-cell tiers is formulated. As it is difficult to obtain the explicit expression of average EE, impacts of the SBS density ratio and signal-to-interference-plus-noise ratio (SINR) threshold on the network performance are investigated through numerical simulations. Simulation results validate the accuracy of theoretical results and demonstrate that the maximum value of average EE can be achieved by optimizing the SBS density ratio and the SINR threshold.

scholarly journals Context-Aware Mode Selection for 5G Multi-Hop Cellular Networks

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 840
Author(s):  
Lucas-Estañ ◽  
Gozalvez ◽  
Sepulcre
Keyword(s):  
Cellular Networks ◽  
Network Performance ◽  
Mode Selection ◽  
Base Station ◽  
Operating Conditions ◽  
Context Aware ◽  
5G Networks ◽  
D2d Communications ◽  
Selection Scheme ◽  
Wide Range

In the present day, 5G and beyond networks are being designed to support the future increase of data traffic and service demands. To support such increase, 5G networks will incorporate device-centric technologies with adequate mechanisms to scale and handle the growing and very large number of connected devices and traffic demands. Device-centric technologies include Device-to-Device (D2D) communications and Multi-hop Cellular Networks (MCNs). In device-centric wireless networks, devices will be able to connect to the network using two different connection modes: through a traditional cellular connection, or through a multi-hop cellular connection based on D2D communications with intermediate mobile devices. Device-centric technologies will therefore provide new connectivity options and significant opportunities to enhance the capacity and efficiency of 5G networks. However, new challenges will need to be addressed. One of them is the selection of the most adequate connection mode for each mobile device, because it will be key to improve the network performance and efficiency. This work proposes a context-aware mode selection scheme capable of identifying and selecting the most adequate connection mode for each device under a wide range of deployment and operating conditions. The proposed scheme estimates the benefits and risks of each connection mode based on context information available at the base station guaranteeing low signaling overhead. The obtained results show that the proposed mode selection scheme helps achieving throughput gains higher than 200% compared to traditional single-hop cellular communications for devices at the cell edge, and significant gains are also achieved compared to other mode selection schemes implemented and evaluated.

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