An Alternating Optimization Algorithm for Energy Efficiency in Heterogeneous Networks

2018 ◽  
Vol 4 (1) ◽  
pp. 1 ◽  
Author(s):  
Kha Ha ◽  
Tien Ha
Keyword(s):  
Energy Efficiency ◽  
Heterogeneous Networks ◽  
Optimization Problems ◽  
Minimum Mean Square Error ◽  
Minimum Energy ◽  
Iterative Algorithms ◽  
Base Station ◽  
Small Cells ◽  
Total System ◽  
Design Problems

This paper studies the problems of precoding designs to achieve the energy efficiency (EE) in the uplink heterogeneous networks in which the multiple small cells are deployed in a macro-cell.  We consider two design problems which maximize either the total system energy efficiency (SEE) or the minimum energy efficiency (MinEE) among users subject to the transmit power constraints at each user and interference constraints caused to the macro base station. Since the optimization problems are non-convex fractional programming in matrix variables, it cannot be straightforward to obtain the optimal solutions. To tackle with the non-convexity challenges of the design problems, we adopt the relationships between the minimum mean square error (MMSE) and achievable data rate to recast the EE problems into ones more amenable. Then, we employ the block coordinate ascent (BCA) and the Dinkelbach methods to develop efficient iterative algorithms in which the closed form solutions are obtained or the semi-definite programming (SDP) problems are solved at each iteration. Simulation results are provided to investigate the EE performance of the EE optimization as compared to those of the spectral efficiency (SE) optimization.

Spectral and energy efficiency analysis of uplink heterogeneous networks with small-cells on edge

2014 ◽  
Vol 13 ◽  
pp. 27-41 ◽  
Author(s):  
Muhammad Zeeshan Shakir ◽  
Hina Tabassum ◽  
Khalid A. Qaraqe ◽  
Erchin Serpedin ◽  
Mohamed-Slim Alouini
Keyword(s):  
Energy Efficiency ◽  
Heterogeneous Networks ◽  
Efficiency Analysis ◽  
Small Cells ◽  
Energy Efficiency Analysis

scholarly journals Massive MIMO: Achievable Energy Efficiency for 5G systems with Multi-user Environment

2019 ◽  
Vol 8 (2) ◽  
pp. 6527-6534
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Path Loss ◽  
Antenna System ◽  
Base Station ◽  
Small Cells ◽  
Limiting Factors ◽  
Improve Energy Efficiency ◽  
User Terminal ◽  
Simulation Results

Massive Multi-Input and Multi-Output (MIMO) antenna system potentially provides a promising solution to improve energy efficiency (EE) for 5G wireless systems. The aim of this paper is to enhance EE and its limiting factors are explored. The maximum EE of 48 Mbit/Joule was achieved with 15 user terminal (UT)s. This problem is related to the uplink spectral efficiency with upper bound for future wireless networks. The maximal EE is obtained by optimizing a number of base station (BS) antennas, pilot reuse factor, and BSs density. We presented a power consumption model by deriving Shannon capacity calculations with closed-form expressions. The simulation result highlights the EE maximization with optimizing variables of circuit power consumption, hardware impairments, and path-loss exponent. Small cells achieve high EE and saturate to a constant value with BSs density. The MRC scheme achieves maximum EE of 36 Mbit/Joule with 12 UTs. The simulation results show that peak EE is obtained by deploying massive BS antennas, where the interference and pilot contamination are mitigated by coherent processing. The simulation results were implemented by using MATLAB 2018b.

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 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 Energy-Spectral Efficiency Trade-Offs in Full-Duplex MU-MIMO Cloud-RANs with SWIPT

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Xuan-Xinh Nguyen ◽  
Ha Hoang Kha
Keyword(s):  
Energy Efficiency ◽  
Spectral Efficiency ◽  
Optimization Problems ◽  
Iterative Algorithms ◽  
Full Duplex ◽  
Total Power ◽  
Achievable Rate ◽  
Power Splitting ◽  
Radio Access ◽  
Trade Offs

The present paper investigates the trade-offs between the energy efficiency (EE) and spectral efficiency (SE) in the full-duplex (FD) multiuser multi-input multioutput (MU-MIMO) cloud radio access networks (CRANs) with simultaneous wireless information and power transfer (SWIPT). In the considered network, the central unit (CU) intends to concurrently not only transfer both energy and information toward downlink (DL) users using power splitting structures but also receive signals from uplink (UL) users. This communication is executed via FD radio units (RUs) which are distributed nearby users and connected to the CU through limited capacity fronthaul (FH) links. In order to unveil interesting trade-offs between the EE and SE metrics, we first introduce three conventional single-objective optimization problems (SOOPs) including (i) system sum rate maximization, (ii) total power minimization, and (iii) fractional energy efficiency maximization. Then, by making use of the multiobjective optimization (MOO) framework, the MOO problem (MOOP) with the objective vector of the achievable rate and power consumption is addressed. All considered problems are nonconvex with respect to designing variables comprising precoding matrices, compression matrices, and DL power splitting factors; thus, it is extremely intractable to solve these problems directly. To overcome these issues, we develop iterative algorithms by utilizing the sequential convex approximation (SCA) approach for the first two SOO problems and the SCA-based Dinkelbach method for the fractional EE problem. Regarding the MOOP, we first rewrite it as an SOOP by applying the modified weighted Tchebycheff method and, then, propose the iterative algorithm-based SCA to find its optimal Pareto set. Various numerical simulations are conducted to study the system performance and appealing EE-SE trade-offs in the considered system.

scholarly journals Interference Mitigation and Power Minimization in 5G Heterogeneous Networks

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1723
Author(s):  
Mayada Osama ◽  
Salwa El Ramly ◽  
Bassant Abdelhamid
Keyword(s):  
Power Consumption ◽  
Heterogeneous Networks ◽  
Power Efficiency ◽  
Interference Mitigation ◽  
Data Rate ◽  
Small Cells ◽  
Total System ◽  
Cell Region ◽  
System Data ◽  
Increasing Demand

Macro cells’ (MCs) densification with small cells (SCs) is one of the promising solutions to cope with the increasing demand for higher data rates in 5G heterogeneous networks (HetNets). Unfortunately, the interference that arises between these densely deployed SCs and their elevated power consumption have caused huge problems facing the 5G HetNets. In this paper, a new soft frequency reuse (SFR) scheme is proposed to minimize the interference and elevate the network throughput. The proposed scheme is based on on/off switching the SCs according to their interference contribution rate (ICR) values. It solves the interference problem of the densely deployed SCs by dividing the cell region into center and edge zones. Moreover, SCs on/off switching tackles the elevated power consumption problem and enhances the power efficiency of the 5G network. Furthermore, our paper tackles the irregular nature problem of 5G HetNets and compares between two different proposed shapes for the center zone of the SC: circular, and irregular shapes. Additionally, the optimum radius of the center zone, which maximizes the total system data rate, is obtained. The results show that the proposed scheme surpasses the traffic and the random on/off switching schemes, as it decreases the outage probability and enhances the total system data rate and power efficiency. Moreover, the results demonstrate the close performance of both the irregular and circular shapes for the center zone.

scholarly journals Energy Efficient and Delay Aware 5G Multi-Tier Network

2019 ◽  
Vol 11 (9) ◽  
pp. 1019
Author(s):  
Nahina Islam ◽  
Ammar Alazab ◽  
Johnson Agbinya
Keyword(s):  
Energy Efficiency ◽  
Mobile Network ◽  
Base Station ◽  
Small Cells ◽  
Sleep Mode ◽  
Indoor Environments ◽  
Data Traffic ◽  
5G Networks ◽  
Energy Expenditures ◽  
Markov Decision

Multi-tier heterogeneous Networks (HetNets) with dense deployment of small cells in 5G networks are expected to effectively meet the ever increasing data traffic demands and offer improved coverage in indoor environments. However, HetNets are raising major concerns to mobile network operators such as complex distributed control plane management, handover management issue, increases latency and increased energy expenditures. Sleep mode implementation in multi-tier 5G networks has proven to be a very good approach for reducing energy expenditures. In this paper, a Markov Decision Process (MDP)-based algorithm is proposed to switch between three different power consumption modes of a base station (BS) for improving the energy efficiency and reducing latency in 5G networks. The MDP-based approach intelligently switches between the states of the BS based on the offered traffic while maintaining a prescribed minimum channel rate per user. Simulation results show that the proposed MDP algorithm together with the three-state BSs results in a significant gain in terms of energy efficiency and latency.

scholarly journals Optimizing Power by Combining Small Cells with a Massive MIMO for Maximum Energy Efficiency under Two Path Loss Models

2019 ◽  
Author(s):  
Ch. Aravind Kumar
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Path Loss ◽  
Base Station ◽  
Design Criterion ◽  
Small Cell ◽  
Small Cells ◽  
Total Power ◽  
Efficient System ◽  
Loss Models

Currently, we are proceeding towards the 5th generationof wireless networks. The 5G is expected to utilize verywide bandwidth and would have the greater capacity comparedto 4G. Therefore, the energy efficiency is one of the prominentroles in the design criterion. To achieve the maximum energyefficiency, the typical approaches are to increase the throughputor to decrease the power consumption. Recently, the approachto combine the small cell access points to Massive MIMO hasbeen proved as one efficient way to achieve the maximum energyefficiency. In this work, the approach to combine two typeof network, namely Small Cell Access Point (SCA) and BaseStation (BS) with Massive MIMO, is considered for designing anenergy efficient system. We investigate further this approach byextending the simulation to cover both 3GPP LTE as well as IMT2020 environment with two different carrier frequencies underthree scenarios. The performance is measured and comparedwith the existing work in terms of total power consumptionper subcarrier of both the Base Station (BS) and Small CellAccess Points (SCAs). It is apparent that our proposed methodprovides the higher information rate at the same total powerper sub carrier than the existing work. Additionally, generalspeaking, the 3GPP path loss model provides the lower totalpower consumption per sub carrier at BS than IMT-2020, whileboth path loss models almost has no impact on total powerconsumption at SCAs, regardless of carrier frequency and thenumber of antennas adopted in Massive MIMO at BS.

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