Energy Efficient Resource Allocation for Phantom Cellular Networks

Handle URI:
http://hdl.handle.net/10754/609074
Title:
Energy Efficient Resource Allocation for Phantom Cellular Networks
Authors:
Abdelhady, Amr ( 0000-0002-5277-6420 )
Abstract:
Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE. First, we consider sparsely deployed cells experiencing negligible interference and assume perfect channel state information (CSI). For this setting, we propose an algorithm that finds the SE and EE resource allocation strategies. Then, we compare the performance of both design strategies versus number of users, and phantom cells share of the total available resource units (RUs). We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It is found that increasing phantom cells share of RUs decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. Second, we consider the densely deployed phantom cellular networks and model the EE optimization problem having into consideration the inevitable interference and imperfect channel estimation. To this end, we propose three resource allocation strategies aiming at optimizing the EE performance metric of this network. Furthermore, we investigate the effect of changing some of the system parameters on the performance of the proposed strategies, such as phantom cells share of RUs, number of deployed phantom cells within a macro cell coverage, number of pilots and the maximum power available for transmission by the phantom cells BSs. It is found that increasing the number of pilots deteriorates the EE performance of the whole setup, while increasing maximum power available for phantom cells transmissions reduces the EE of the whole setup in a less severe way than increasing the number of pilots. It is found also that increasing phantom cells share increases the EE metric in the dense deployment case. Thus, it is always useful to allocate most of the network RUs to the phantom cells tier.
Advisors:
Alouini, Mohamed-Slim ( 0000-0003-4827-1793 )
Committee Member:
Shihada, Basem ( 0000-0003-4434-4334 ) ; Genton, Marc G. ( 0000-0001-6467-2998 )
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Electrical Engineering Program
Program:
Electrical Engineering
Issue Date:
Apr-2016
Type:
Thesis
Appears in Collections:
Theses; Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.advisorAlouini, Mohamed-Slimen
dc.contributor.authorAbdelhady, Amren
dc.date.accessioned2016-05-11T13:56:58Zen
dc.date.available2016-05-11T13:56:58Zen
dc.date.issued2016-04en
dc.identifier.urihttp://hdl.handle.net/10754/609074en
dc.description.abstractMulti-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE. First, we consider sparsely deployed cells experiencing negligible interference and assume perfect channel state information (CSI). For this setting, we propose an algorithm that finds the SE and EE resource allocation strategies. Then, we compare the performance of both design strategies versus number of users, and phantom cells share of the total available resource units (RUs). We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It is found that increasing phantom cells share of RUs decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. Second, we consider the densely deployed phantom cellular networks and model the EE optimization problem having into consideration the inevitable interference and imperfect channel estimation. To this end, we propose three resource allocation strategies aiming at optimizing the EE performance metric of this network. Furthermore, we investigate the effect of changing some of the system parameters on the performance of the proposed strategies, such as phantom cells share of RUs, number of deployed phantom cells within a macro cell coverage, number of pilots and the maximum power available for transmission by the phantom cells BSs. It is found that increasing the number of pilots deteriorates the EE performance of the whole setup, while increasing maximum power available for phantom cells transmissions reduces the EE of the whole setup in a less severe way than increasing the number of pilots. It is found also that increasing phantom cells share increases the EE metric in the dense deployment case. Thus, it is always useful to allocate most of the network RUs to the phantom cells tier.en
dc.language.isoenen
dc.subjectEnergy efficiencyen
dc.subjectphantom cellsen
dc.subjectresource allocationen
dc.subjectSpectral efficiencyen
dc.subjectfractional programmingen
dc.subjectDC programmingen
dc.titleEnergy Efficient Resource Allocation for Phantom Cellular Networksen
dc.typeThesisen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentElectrical Engineering Programen
thesis.degree.grantorKing Abdullah University of Science and Technologyen_GB
dc.contributor.committeememberShihada, Basemen
dc.contributor.committeememberGenton, Marc G.en
thesis.degree.disciplineElectrical Engineeringen
thesis.degree.nameMaster of Scienceen
dc.person.id132624en
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