On the Energy Efficiency-Spectral Efficiency Trade-off in Cel- lular Systems

2016 ◽  
pp. 379-430 ◽  
Keyword(s):  
Energy Efficiency ◽  
Spectral Efficiency ◽  
Trade Off

scholarly journals On the Energy Efficiency-Spectral Efficiency Trade-Off in the Uplink of CoMP System

2012 ◽  
Vol 11 (2) ◽  
pp. 556-561 ◽  
Author(s):  
Oluwakayode Onireti ◽  
Fabien Heliot ◽  
Muhammad Ali Imran
Keyword(s):  
Energy Efficiency ◽  
Spectral Efficiency ◽  
Trade Off

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>

On the Optimal Energy Efficiency and Spectral Efficiency Trade-Off of CF Massive MIMO SWIPT System

2021 ◽  
Author(s):  
Na Li ◽  
Yuan Yuan Gao ◽  
Kui Xu
Keyword(s):  
Energy Efficiency ◽  
Energy Harvesting ◽  
Information Transmission ◽  
Spectral Efficiency ◽  
Performance Optimization ◽  
Processing Unit ◽  
Processing Scheme ◽  
Selection Scheme ◽  
Trade Off ◽  
Central Processing

Abstract This paper studies a cell-free (CF) massive multi-input multi-output (MIMO) simultaneous wireless information and power transmission (SWIPT) system and proposes a user-centric (UC) access point (AP) selection method and a trade-off performance optimization scheme for spectral efficiency and energy efficiency. In this system, users have both energy harvesting and information transmission functions, and according to the difference between energy harvesting and information transmission, a flexible AP selection scheme is designed. This paper analyses the trade-off between energy efficiency and spectral efficiency, proposes an evaluation index that takes into account both energy efficiency and spectral efficiency, and jointly optimizes the AP selection scheme and the uplink (UL) and downlink (DL) time switching ratio to maximize the trade-off performance. Then, the non-convex problem is converted to a geometric planning (GP) problem to solve. The simulation results show that by implementing a suitable AP selection scheme and UL and DL time allocation, the information processing scheme on the AP side has a slight loss in spectral efficiency, but the energy efficiency is close to the performance of global processing on the central processing unit (CPU).

scholarly journals On the Trade-Off between Energy Efficiency and Spectral Efficiency in RIS-Aided Multi-User MISO Downlink

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1307
Author(s):  
Meng Zhang ◽  
Le Tan ◽  
Kelin Huang ◽  
Li You
Keyword(s):  
Energy Efficiency ◽  
Spectral Efficiency ◽  
Low Cost ◽  
Base Station ◽  
Trade Off ◽  
Optimization Framework ◽  
Single Output ◽  
Multiple Input ◽  
Fast Convergence Rate ◽  
Simulation Results

As reconfigurable intelligent surfaces (RISs) have been gradually brought to reality, a large amount of research has been conducted to investigate the immense benefits of RISs. That is because RISs enable us to artificially direct the radio wave propagating through the environment at a relatively low cost. This paper investigates the trade-off between spectral efficiency (SE) and energy efficiency (EE) in the RIS-aided multi-user multiple-input single-output downlink. We develop an optimization framework for designing the transmitting precoding at the base station and the phase shift values at the RIS to balance the EE-SE trade-off. The proposed iterative optimization framework for the design includes quadratic transform, alternating optimization, and weighted minimization mean-square error conversion. Simulation results illustrate our optimization framework algorithm exhibits effectiveness and a fast convergence rate.

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>

scholarly journals Interrelationship between Energy Efficiency and Spectral Efficiency in Cognitive Femtocell Networks: A Survey

2021 ◽  
Author(s):  
Joydev Ghosh
Keyword(s):  
Energy Efficiency ◽  
Wireless Networks ◽  
Spectral Efficiency ◽  
Multiple Access ◽  
State Of The Art ◽  
Femtocell Networks ◽  
Design Guideline ◽  
Trade Off ◽  
Potential Impact ◽  
Cognitive Femtocell

<div>In this paper, we initially dealt with the issue of spectrum allocation among macro (or “licensed”) and Femto (or “unlicensed”) users in an Orthogonal Frequency Devision Multiple Access (OFDMA) based dual-layer femtocell networks. This research contribution will lead to basic coin in the design of next generation (5G) wireless networks. This manuscript exemplifies the trade off issue of energy efficiency (EE) and spectral efficiency (SE) with both cooperative and non-cooperative architecture in cognitive femtocell networks. The pivotal concepts for each technology are described, along with their potential impact on 5G and the research challenges that remain. Further, the trade-off between EE and SE is reposed with respect to the state of the art. The obtained insightful observations from the trade-off analysis of EE ans SE can lead to provide design guideline for 5G wireless Networks.</div>

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