Energy-Spectral Efficiency Tradeoffs in 5G Multi-Operator Networks With Heterogeneous Constraints

Aydin, Osman Enver; Jorswieck, Eduard A.; Aziz, Danish; Zappone, Alessio

doi:10.1109/twc.2017.2716948

Cited by 45 publications

(35 citation statements)

References 35 publications

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“…Consequently, numerous research studies, e.g., [13][14][15][16][17][18][19][20], have already addressed the issue of EE in mobile networks. Hence, due to increasing the energy consumption from large-scale deployment of small cells [21], in addition to SE, EE has also been considered as one of the key performance metrics for the design of future fifth-generation (5G) and beyond mobile systems [22][23][24]. Accordingly, several research works have already addressed both SE and EE together to investigate numerous critical concerns, including co-design framework, tradeoff, and joint optimization or maximization, of SE and EE.…”

Section: Related Work and Problem Statementmentioning

confidence: 99%

“…Likewise, in [27], the authors have developed a statistical framework to quantify area SE and EE performance of a user-centric cloud-based radio access network for 5G mobile systems. Moreover, the authors in [23] have proposed an optimization framework for EE and SE maximization in a network where radio resources are shared among multiple operators in 5G.…”

Section: Related Work and Problem Statementmentioning

confidence: 99%

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On Maximizing Energy and Spectral Efficiencies Using Small Cells in 5G and Beyond Networks

Saha

2020

Sensors

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Addressing high capacity at low power as a key design goal envisages achieving high spectral efficiency (SE) and energy efficiency (EE) for the next-generation mobile networks. Because most data are generated in indoor environments, an ultra-dense deployment of small cells (SCs), particularly within multistory buildings in urban areas, is revealed as an effective technique to improve SE and EE by numerous studies. In this paper, we present a framework exploiting the four most interconnected-domain, including, power, time, frequency, and space, in the perspectives of SE and EE. Unlike existing literature, the framework takes advantage of higher degrees of freedom to maximize SE and EE using in-building SCs for 5G and beyond mobile networks. We derive average capacity, SE, and EE metrics, along with defining the condition for optimality of SE and EE and developing an algorithm for the framework. An extensive system-level evaluation is performed to show the impact of each domain on SE and EE. It is shown that employing multiband enabled SC base stations (SBSs) to increase operating spectrum in frequency-domain, reusing spectrum to SBSs more than once per building in spatial-domain, switching on and off each in-building SBS based on traffic availability to reduce SBS power consumption in power-domain, and using eICIC to avoid co-channel interference due to sharing spectrum with SBSs in time-domain can achieve massive SE and EE. Finally, we show that the proposed framework can satisfy SE, EE, as well as user experience data rate requirements for 5G and beyond mobile networks.

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Section: Related Work and Problem Statementmentioning

confidence: 99%

Section: Related Work and Problem Statementmentioning

confidence: 99%

On Maximizing Energy and Spectral Efficiencies Using Small Cells in 5G and Beyond Networks

Saha

2020

Sensors

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“…Mathematically, CP i produces the linearly precoded signalsx i,1 according to (5) and (6), respectively, and obtains the quantized signalsx i,1 , whose covariance matrix depends on the correlation matrix Θ…”

Section: Multivariate Compressionmentioning

confidence: 99%

Multi-Tenant C-RAN With Spectrum Pooling: Downlink Optimization Under Privacy Constraints

Park

Simeone

Shamai

2018

IEEE Trans. Veh. Technol.

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Spectrum pooling allows multiple operators, or tenants, to share the same frequency bands. This work studies the optimization of spectrum pooling for the downlink of a multi-tenant Cloud Radio Access Network (C-RAN) system in the presence of inter-tenant privacy constraints. The spectrum available for downlink transmission is partitioned into private and shared subbands, and the participating operators cooperate to serve the user equipments (UEs) on the shared subband. The network of each operator consists of a cloud processor (CP) that is connected to proprietary radio units (RUs) by means of finite-capacity fronthaul links. In order to enable inter-operator cooperation, the CPs of the participating operators are also connected by finite-capacity backhaul links. Inter-operator cooperation may hence result in loss of privacy. Fronthaul and backhaul links are used to transfer quantized baseband signals.Standard quantization is considered first. Then, a novel approach based on the idea of correlating quantization noise signals across RUs of different operators is proposed to control the trade-off between distortion at UEs and inter-operator privacy. The problem of optimizing the bandwidth allocation, precoding, and fronthaul/backhaul compression strategies is tackled under constraints on backhaul and 2 fronthaul capacity, as well as on per-RU transmit power and inter-operator privacy. For both cases, the optimization problems are tackled using the concave convex procedure (CCCP), and extensive numerical results are provided.

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“…In [25][26][27][28][29], the EE of HCN under the PPP model is studied, and the strategies to optimize the EE are proposed from the aspects of transmit power, BS sleeping, BS density and so on. Also under the PPP model, [30][31][32] analyzes the relationship between EE and spectral efficiency (SE), [33][34][35][36][37] analyze or optimize the Area SE and EE of HCN. However, the EEs of HCNs based on non-PPP models have not been analytically investigated.…”

Section: Introductionmentioning

confidence: 99%

Coverage and Energy Efficiency Analysis for Two-Tier Heterogeneous Cellular Networks Based on Matérn Hard-Core Process

2019

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Due to the dense deployment of base stations (BSs) in heterogeneous cellular networks (HCNs), the energy efficiency (EE) of HCN has attracted the attention of academia and industry. Considering its mathematical tractability, the Poisson point process (PPP) has been employed to model HCNs and analyze their performance widely. The PPP falls short in modeling the effect of interference management techniques, which typically introduces some form of spatial mutual exclusion among BSs. In PPP, all the nodes are independent from each other. As such, PPP may not be suitable to model networks with interference management techniques, where there exists repulsion among the nodes. Considering this, we adopt the Matérn hard-core process (MHCP) instead of PPP, in which no two nodes can be closer than a repulsion radius from one another. In this paper, we study the coverage performance and EE of a two-tier HCN modelled by Matérn hard-core process (MHCP); we abbreviate this kind of two-tier HCN as MHCP-MHCP. We first derive the approximate expression of coverage probability of MHCP-MHCP by extending the approximate signal to interference ratio analysis based on the PPP (ASAPPP) method to multi-tier HCN. The concrete SIR gain of the MHCP model relative to the PPP model is derived through simulation and data fitting. On the basis of coverage analysis, we derive and formulate the EE of MHCP-MHCP network. Simulation results verify the correctness of our theoretical analysis and show the performance difference between the MHCP-MHCP and PPP modelled network.

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Energy-Spectral Efficiency Tradeoffs in 5G Multi-Operator Networks With Heterogeneous Constraints

Cited by 45 publications

References 35 publications

On Maximizing Energy and Spectral Efficiencies Using Small Cells in 5G and Beyond Networks

On Maximizing Energy and Spectral Efficiencies Using Small Cells in 5G and Beyond Networks

Multi-Tenant C-RAN With Spectrum Pooling: Downlink Optimization Under Privacy Constraints

Coverage and Energy Efficiency Analysis for Two-Tier Heterogeneous Cellular Networks Based on Matérn Hard-Core Process

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