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.

Robust Power Allocation for NOMA Heterogeneous Networks with EH under Imperfect CSI

2021 ◽  
Author(s):  
Xin Song ◽  
Xue Huang ◽  
Yiming Gao ◽  
Haijun Qian
Keyword(s):  
Energy Efficiency ◽  
Outage Probability ◽  
Power Allocation ◽  
Heterogeneous Networks ◽  
Optimization Problem ◽  
Base Station ◽  
Probabilistic Constraints ◽  
Allocation Scheme ◽  
Imperfect Csi ◽  
Robust Power Allocation

Abstract A robust power allocation is proposed for downlink non-orthogonal multiple access (NOMA) heterogeneous networks with EH (Energy harvesting) under imperfect channel state information (CSI). In order to achieve green communication, an EH-aided scheme by leveraging energy from macro base station (MBS) signal and interference signal transmitted from other SBSs is proposed, which reduces the power burden and energy consumption of the SBS. In order to conform to the actual communication scenario, we construct an energy efficiency optimization function under imperfect CSI with considering the constraint of the outage probability interference power in macro cell user (MCU). However, the formulated optimization problem is non-convex due to the fractional form of the objective function and the probabilistic constraints of the outage probability limit. To cope with this problem, we propose a robust power allocation scheme. Firstly, the probabilistic problem is converted into a robust non-probabilistic problem by the minimax probability machine (MPM) and robust optimization theory. Then, the robust non-probabilistic problem can be transformed into the convex optimization problem via Dinkelbach method and sequential convex programming. Finally, the optimal transmission powers of the small cell users (SCUs) are obtained by Lagrange dual approach. The simulation results show that the robust power allocation scheme for NOMA heterogeneous networks with EH under imperfect CSI can significantly improve energy efficiency compared with traditional power allocation algorithms.

Spectral Efficiency Self-Optimization through Dynamic User Clustering and Beam Steering

2016 ◽  
pp. 137-155
Author(s):  
Md Salik Parwez ◽  
Hasan Farooq ◽  
Ali Imran ◽  
Hazem Refai
Keyword(s):  
Spectral Efficiency ◽  
Large Scale ◽  
Optimization Problem ◽  
Focal Point ◽  
Beam Steering ◽  
Clustering Algorithms ◽  
Performance Comparison ◽  
Base Stations ◽  
User Clustering ◽  
A Cell

This paper presents a novel scheme for spectral efficiency (SE) optimization through clustering of users. By clustering users with respect to their geographical concentration we propose a solution for dynamic steering of antenna beam, i.e., antenna azimuth and tilt optimization with respect to the most focal point in a cell that would maximize overall SE in the system. The proposed framework thus introduces the notion of elastic cells that can be potential component of 5G networks. The proposed scheme decomposes large-scale system-wide optimization problem into small-scale local sub-problems and thus provides a low complexity solution for dynamic system wide optimization. Every sub-problem involves clustering of users to determine focal point of the cell for given user distribution in time and space, and determining new values of azimuth and tilt that would optimize the overall system SE performance. To this end, we propose three user clustering algorithms to transform a given user distribution into the focal points that can be used in optimization; the first is based on received signal to interference ratio (SIR) at the user; the second is based on received signal level (RSL) at the user; the third and final one is based on relative distances of users from the base stations. We also formulate and solve an optimization problem to determine optimal radii of clusters. The performances of proposed algorithms are evaluated through system level simulations. Performance comparison against benchmark where no elastic cell deployed, shows that a gain in spectral efficiency of up to 25% is possible depending upon user distribution in a cell.

scholarly journals User Association and Power Control for Energy Efficiency Maximization in M2M-Enabled Uplink Heterogeneous Networks with NOMA

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5307 ◽  
Author(s):  
Shuang Zhang ◽  
Guixia Kang
Keyword(s):  
Energy Efficiency ◽  
Power Control ◽  
Heterogeneous Networks ◽  
Base Station ◽  
Sequential Optimization ◽  
User Association ◽  
Decode And Forward ◽  
Vast Number ◽  
Machine Type ◽  
Machine Type Communication

To support a vast number of devices with less energy consumption, we propose a new user association and power control scheme for machine to machine enabled heterogeneous networks with non-orthogonal multiple access (NOMA), where a mobile user (MU) acting as a machine-type communication gateway can decode and forward both the information of machine-type communication devices and its own data to the base station (BS) directly. MU association and power control are jointly considered in the formulated as optimization problem for energy efficiency (EE) maximization under the constraints of minimum data rate requirements of MUs. A many-to-one MU association matching algorithm is firstly proposed based on the theory of matching game. By taking swap matching operations among MUs, BSs, and sub-channels, the original problem can be solved by dealing with the EE maximization for each sub-channel. Then, two power control algorithms are proposed, where the tools of sequential optimization, fractional programming, and exhaustive search have been employed. Simulation results are provided to demonstrate the optimality properties of our algorithms under different parameter settings.

scholarly journals Joint Spectral Efficiency and Energy Efficiency in FFR-Based Wireless Heterogeneous Networks

2018 ◽  
Vol 67 (9) ◽  
pp. 8154-8168 ◽  
Author(s):  
Bei Xie ◽  
Zekun Zhang ◽  
Rose Qingyang Hu ◽  
Geng Wu ◽  
Apostolos Papathanassiou
Keyword(s):  
Energy Efficiency ◽  
Heterogeneous Networks ◽  
Spectral Efficiency ◽  
Wireless Heterogeneous Networks

scholarly journals Cell Outage Detection and Compensation in Two-Tier Heterogeneous Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Wenqian Xue ◽  
Hengzhi Zhang ◽  
Yong Li ◽  
Dong Liang ◽  
Mugen Peng
Keyword(s):  
Heterogeneous Networks ◽  
Nearest Neighbor ◽  
Network Capacity ◽  
Vertical Handover ◽  
Base Station ◽  
Data Traffic ◽  
Traffic Demand ◽  
Planning Optimization ◽  
And Performance ◽  
Optimizing Algorithm

Heterogeneous networks (HetNets) can increase network capacity through complementing the macro-base-station with low-power nodes, in response to the ongoing exponential growth in data traffic demand. While, unprecedented challenges exist in the planning, optimization, and maintenance in HetNets, especially activities such as cell outage detection and mitigation are labor-intensive and costly. One potential solution to address these issues is to introduce the extensively attracted self-organizing network (SON). This paper is mainly devoted to cell outage detection and compensation methods in two-tier HetNets where macrocell and picocells are coexisted. AK-nearest neighbor (KNN) classification algorithm is employed to detect the cell outage automatically. Consider the breakdown picocell can reload its degraded service to the overlapped macrocell via vertical handover; only the breakdown macrocell executes the performance compensation. Power adjustment on each resource block is carried out via Lagrange optimizing algorithm to compensate the breakdown cell. Through intensive numerical experiments, with the help of our proposal, the outage cells can be successfully detected and performance gain for the outage macrocell can reach 91.4% withα=1/3.

scholarly journals An Optimal Energy Efficiency of a Two-tier Network in Control-Data Separation Architecture

2020 ◽  
pp. 545-550
Author(s):  
Zaid Mujaiyid Putra Bin Ahmad Baidowi ◽  
◽  
Xiaoli Chu
Keyword(s):  
Energy Efficiency ◽  
Point Processes ◽  
Threshold Value ◽  
Base Station ◽  
Base Stations ◽  
Mobile Users ◽  
Maximization Problem ◽  
User Association ◽  
Data Separation ◽  
Cell Base

In this paper, we propose to maximize the Energy Efficiency (EE) of a two-tier network by jointly optimizing the number of active small cell base stations (SBSs) and the user-cell association. We apply the concept of signaling and data separation where a macro cell base station (MBS) provides full coverage while the SBSs provide high data transmission. First, we model the spatial distributions of the SBSs and mobile users following two independent Poisson Point Processes (PPP) and derive the expressions for the Signal-to-Interference Ratio (SIR), user cell associations, power consumption and energy efficiency of the Heterogeneous Network (HetNet). Then, we formulate the EE maximization problem and solve it by proposing the Switching off Decision and User Association (SODUA) algorithm. The algorithm associates a mobile user to an SBS that offers the highest SIR and calculates the load of each SBS. The algorithm, then, decides to switch off the SBSs that have fewer mobile users than a threshold value, where the mobile users will be offloaded to a nearby SBS that offers the highest SIR. Finally, we calculate the EE of the HetNet. We compare the EE achieved by the proposed algorithm (i.e. after offloading) and that "without offloading". The results show that the proposed algorithm improves the EE of the HetNet and that the EE cannot be further improved by switching off more SBSs than a certain number.

scholarly journals A trade-off between Energy Efficiency and Spectral Efficiency in macro-femtocell networks

2021 ◽  
Author(s):  
Joydev Ghosh
Keyword(s):  
Energy Efficiency ◽  
Spectral Efficiency ◽  
Analytical Framework ◽  
Weighting Factor ◽  
Base Station ◽  
Fine Tuning ◽  
Pareto Optimal ◽  
Femtocell Networks ◽  
Transmit Power ◽  
Trade Off

<div>Obtaining large spectral efficiency (SE) and energy efficiency (EE) subject to quality of experience (QoE) is one of the prime concerns for the wireless next generation networks, however a major confrontation with its trade-off which is becoming apparent while optimizing both SE and EE parameters concurrently. In this work, an analytical framework for a cognitive-femtocell network is proposed to be dealt with and overcome the situations regarded as unwelcome. Here, the conflict of SE-EE trade-off in downlink (DL) transmission is expressed methodically by Pareto Optimal Set (POS) based on a multi-empirical most effective use of a resource scheme as a function of femto base station (FBS) and macro base station (MBS) transmit power and base station (BS) density, respectively. Then, SE and EE are formulated in a utility function by applying Cobb-Douglas production function to transform the multi- mpirical difficulty into the single-empirical optimization case. Besides, it is analytically shown that the SE-EE trade-off can be optimize through a distinctive universal optimum among the Pareto optimal by fine tuning the weighting metric other than BS transmit power and density, respectively. Simulation results validate that it is possible to obtain the EE-SE trade-off with SINR threshold at different weighting factor.</div>

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