scholarly journals A Joint Power and Channel Scheduling Scheme for Underlay D2D Communications in the Cellular Network

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4799
Author(s):  
Zefang Lin ◽  
Hui Song ◽  
Daru Pan
Keyword(s):  
Energy Efficiency ◽  
Optimization Problem ◽  
Business Models ◽  
Base Station ◽  
User Equipment ◽  
D2d Communication ◽  
Power Relationship ◽  
Green Communications ◽  
Joint Power ◽  
The Impact

Device-to-device (D2D) communication, as one of the promising candidates for the fifth generation mobile network, can afford effective service of new mobile applications and business models. In this paper, we study the resource management strategies for D2D communication underlying the cellular networks. To cater for green communications, our design goal is to the maximize ergodic energy efficiency (EE) of all D2D links taking into account the fact that it may be tricky for the base station (BS) to receive all the real-time channel state information (CSI) while guaranteeing the stability and the power requirements for D2D links. We formulate the optimization problem which is difficult to resolve directly because of its non-convex nature. Then a novel maximum weighted ergodic energy efficiency (MWEEE) algorithm is proposed to solve the formulated optimization problem which consists of two sub-problems: the power control (PC) sub-problem which can be solved by employing convex optimization theory for both cellular user equipment (CUE) and D2D user equipment (DUE) and the channel allocation (CA) sub-problem which can be solved by obtaining the weighted allocation matrix. In particular, we shed light into the impact on EE metric of D2D communication by revealing the nonlinear power relationship between CUE and DUE and taking the QoS of CUEs into account. Furthermore, simulation results show that our proposed algorithm is superior to the existing algorithms.

scholarly journals Lagrangian Dual Decomposition for Joint Resource Allocation Optimization Problem in OFDMA Downlink Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Li-Jun Jia ◽  
Yu-Cheng He ◽  
Dong-Hua Chen ◽  
Lin Zhou
Keyword(s):  
Energy Efficiency ◽  
Optimization Problem ◽  
Joint Optimization ◽  
Original Form ◽  
Dual Decomposition ◽  
Joint Power ◽  
Lagrangian Dual ◽  
Joint Resource Allocation ◽  
Multiple Variable ◽  
Variable Coupling

This paper proposes an efficient method for joint power and subcarrier allocation in a multicell multiuser OFDMA downlink network. The joint optimization problem is formulated with the objective of maximizing the energy efficiency subject to the constraints on the quality of service in sum transmission rates for each cell and the total transmit power for the network. Due to intercell cochannel interferences and multiple variable coupling, the problem is intractable in its original form. To relax the difficulties in coordinating cochannel interferences, we introduce the tolerable interferences constraints for interference channels. To cope with the multiple variable coupling, we decompose the joint optimization problem into two iterative processes of user scheduling and a parametric convex optimization problem, where the energy efficiency is treated as the parameter and approached by bisection search. Then, by double dual decomposition, the parametric convex problem is transformed into Lagrangian dual problems at two levels of cells and subcarriers, and a decentralized solution is obtained in closed form. Based on the reformulations, an iterative subgradient algorithm is presented for approaching the joint optimization problem with acceptable complexity. Computer simulations are conducted to validate the proposed algorithm and examine the effects of various system parameters.

scholarly journals Area Spectral Efficiency and Energy Efficiency Tradeoff in Ultradense Heterogeneous Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Lanhua Xiang ◽  
Hongbin Chen ◽  
Feng Zhao
Keyword(s):  
Energy Efficiency ◽  
Heterogeneous Networks ◽  
Spectral Efficiency ◽  
Point Processes ◽  
Optimization Problem ◽  
Focal Point ◽  
Base Station ◽  
Data Traffic ◽  
Total Energy Consumption ◽  
Area Spectral Efficiency

In order to meet the demand of explosive data traffic, ultradense base station (BS) deployment in heterogeneous networks (HetNets) as a key technique in 5G has been proposed. However, with the increment of BSs, the total energy consumption will also increase. So, the energy efficiency (EE) has become a focal point in ultradense HetNets. In this paper, we take the area spectral efficiency (ASE) into consideration and focus on the tradeoff between the ASE and EE in an ultradense HetNet. The distributions of BSs in the two-tier ultradense HetNet are modeled by two independent Poisson point processes (PPPs) and the expressions of ASE and EE are derived by using the stochastic geometry tool. The tradeoff between the ASE and EE is formulated as a constrained optimization problem in which the EE is maximized under the ASE constraint, through optimizing the BS densities. It is difficult to solve the optimization problem analytically, because the closed-form expressions of ASE and EE are not easily obtained. Therefore, simulations are conducted to find optimal BS densities.

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 An Optimal Cluster-Head Selection algorithm for Wireless Sensor Networks

2020 ◽  
Vol 19 ◽  
Keyword(s):  
Energy Efficiency ◽  
Network Lifetime ◽  
Environmental Conditions ◽  
Signal Strength ◽  
Base Station ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Control Technique ◽  
The Impact

The energy utilization is one of the most common challenges in Wireless Sensor Network (WSN), as frequent communication between the sensor nodes (SNs) results in huge energy drain. Moreover, optimization and load balancing within the WSN are the significant concern to grant intellect for the extensive period of network lifetime. As a matter of fact, many WSNs are deployed and operating outdoors is exposed to varying environmental conditions, which may further set grounds for severe performance degradation of such networks. Therefore, it is necessary to take into consideration the factors like radio signal strength in order to reduce the impact and to adapt to varying environmental conditions. Since clustering is a topological control technique to reduce the activity of SNs transceivers, it extensively increases overall system scalability and energy efficiency. It selects CH to manage the entire network to achieve longevity in WSN. In this paper, we present an optimal CH selection (OCHS) algorithm which is also based on environmental conditions to achieve energy efficiency and enhanced network lifetime. The originality of this work is that we have taken into consideration the received signal strength index (RSSI) of SNs from the base-station (BS). The OCHS algorithm mainly focuses on maximizing the network lifetime based on RSSI values and residual energy levels of SNs. TheOCHS algorithm is simulated on Cooja Simulator and its performance is compared with existing LEACH and HEED protocols. Simulation analysis and results proved that our OCHS algorithm can effectively enhance the network lifetime by two times and thus it is an energy-efficient way to choose a CH.

scholarly journals Data Rate Maximization in RIS-Assisted D2D Communication with Transceiver Hardware Impairments

Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 200
Author(s):  
Hongxia Zheng ◽  
Chiya Zhang ◽  
Yatao Yang ◽  
Xingquan Li ◽  
Chunlong He
Keyword(s):  
Optimization Problem ◽  
Original Problem ◽  
Optimal Solution ◽  
Base Station ◽  
D2d Communication ◽  
Convex Optimization Problem ◽  
Hardware Impairments ◽  
Convex Problems ◽  
Rate Maximization ◽  
Power Limit

We maximize the transmit rate of device-to-device (D2D) in a reconfigurable intelligent surface (RIS) assisted D2D communication system by satisfying the unit-modulus constraints of reflectin elements, the transmit power limit of base station (BS) and the transmitter in a D2D pair. Since it is a non-convex optimization problem, the block coordinate descent (BCD) technique is adopted to decouple this problem into three subproblems. Then, the non-convex subproblems are approximated into convex problems by using successive convex approximation (SCA) and penalty convex-concave procedure (CCP) techniques. Finally, the optimal solution of original problem is obtained by iteratively optimizing the subproblems. Simulation results reveal the validity of the algorithm that we proposed to solve the optimization problem and illustrate the effectiveness of RIS to improve the transmit rate of the D2D pair even with hardware impairments.

scholarly journals Energy Efficiency Maximized Resource Allocation for Opportunistic Relay-Aided OFDMA Downlink with Subcarrier Pairing

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Tao Wang ◽  
Chao Ma ◽  
Yanzan Sun ◽  
Shunqing Zhang ◽  
Yating Wu
Keyword(s):  
Resource Allocation ◽  
Energy Efficiency ◽  
Multiple Access ◽  
Operation Mode ◽  
Base Station ◽  
Transmission Protocol ◽  
Relay Station ◽  
Frequency Division ◽  
Subcarrier Pairing ◽  
The Impact

This paper studies the energy efficiency (EE) maximization for an orthogonal frequency division multiple access (OFDMA) downlink network aided by a relay station (RS) with subcarrier pairing. A highly flexible transmission protocol is considered, where each transmission is executed in two time slots. Every subcarrier in each slot can either be used in direct mode or be paired with a subcarrier in another slot to operate in relay mode. The resource allocation (RA) in such a network is highly complicated, because it has to determine the operation mode of subcarriers, the assignment of subcarriers to users, and the power allocation of the base station and RS. We first propose a mathematical description of the RA strategy. Then, a RA algorithm is derived to find the globally optimum RA to maximize the EE. Finally, we present extensive numerical results to show the impact of minimum required rate of the network, the user number, and the relay position on the maximum EE of the network.

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.

Toward Green Evolution of Cellular Networks by High Order Sectorisation and Small Cell Densification

2017 ◽  
pp. 1-28
Author(s):  
Abdelrahman Arbi ◽  
Timothy O'Farrell ◽  
Fu-Chun Zheng ◽  
Simon C. Fletcher
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
Network Capacity ◽  
Base Station ◽  
Small Cell ◽  
Small Cells ◽  
Deployment Strategy ◽  
Energy Efficiency Improvement ◽  
The Impact

Network densification by adding either more sectors per site or by deploying an overlay of small cells is always considered to be a key method for enhancing the RAN coverage and capacity. The impact of these two techniques on cellular network energy consumption is investigated in this chapter. The aim is to find an energy efficient deployment strategy when trading-off the order of sectorisation with the intensity of small cell densification. A new enhanced base station power consumption model is presented, followed by a novel metric framework for the evaluation of the RAN energy efficiency. The use of the power model and the proposed metrics is demonstrated by applying them to a RAN case study when the two techniques are used to improve the network capacity. In addition, the chapter evaluates the amount of network energy efficiency improvement when various adaptive sectorisation schemes are implemented. The results show that the strategy of adding more sectors is less energy efficient than directly deploying an overlay of small cells, even when adaptive sectorisation is implemented.

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