Optimal energy‐efficient resource allocation in uplink SC‐FDMA networks

Orakzai, Farooq Alam; Ahmad, Ayaz; Khan, Muhammad Toaha Raza; Iqbal, Muhammad

doi:10.1002/ett.3153

Cited by 11 publications

(17 citation statements)

References 30 publications

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“…The article by Wong et al is a seminal work on EE with QoS constraints for OFDMA whose main objective is to minimize the total transmit power. Contributions on EE optimization for uplink SC‐FDMA can be found in the following studies . In the work of Ahmad and Assaad, the total transmit power minimization problem subject to QoS constraints was studied as an integer binary optimization problem, and a low‐complexity solution was proposed by assuming canonical duality theory.…”

Section: State‐of‐the‐art and Main Contributionsmentioning

confidence: 99%

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Maximizing energy efficiency in SC‐FDMA uplink with QoS guarantees and user satisfaction

Braga

Lima

Maciel

et al. 2019

Trans Emerging Tel Tech

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Despite the advent of fifth-generation mobile networks in the next years, the Long-Term Evolution system still have an important role in the mobile communication scenario. Moreover, the development of solutions that fulfill the demand of new multimedia applications as well as provide an efficient use of the energy resources is one of the drivers of future networks. Therefore, in this article, we deal with the total energy efficiency maximization problem subject to minimum satisfaction constraints per service and quality of service in the uplink of Long-Term Evolution using single-carrier frequency-division multiple access. Although the formulated problem is a nonlinear combinatorial optimization problem, we obtain the optimal solution through algebraic manipulations and by using an iterative method. Motivated by the high computational complexity to obtain the optimal solution, we propose a heuristic solution with lower computational complexity. Realistic system-level simulations indicate that the proposed solution presents good performance regarding both outage rate and energy efficiency.Trans Emerging Tel Tech. 2019;30:e3674.wileyonlinelibrary.com/journal/ett

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Section: State‐of‐the‐art and Main Contributionsmentioning

confidence: 99%

“…Although transmit power was adapted to improve EE, the authors assumed an oversimplified frequency assignment based on round robin. The optimal solution for EE joint power and subchannel allocation in uplink SC‐FDMA was proposed by Orakzai et al to maximize the total individual EE.…”

Section: State‐of‐the‐art and Main Contributionsmentioning

confidence: 99%

Maximizing energy efficiency in SC‐FDMA uplink with QoS guarantees and user satisfaction

Braga

Lima

Maciel

et al. 2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

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“…The user k attainable data rate can be represented as follows:

R_{k}^{m} = W (||, N_{k}^{m}) \log_{2} ((), 1 + Γ_{k}),

where

N_{k}^{m}

is the allocated subchannels set to the k th user connected to RRH m . The EE is described as the amount of bits transmitted per unit consumption of energy at the source end, which is given as follows:

η_{k}^{m} = \frac{R_{k}^{m}}{P_{T}^{k}},

where

P_{T}^{k}

is the total energy consumption of user k connected to RRH m , which consists of two parts, the combined transmit powers on all its subchannels

\sum_{n ε N_{k}^{m}} p_{k, n}

and the circuit energy consumptions of user k connected to RRH m ,

p_{c k t, k}^{m}

, that is experienced by signal processing and various circuit blocks at the transmitter pckt,km further comprises of two parts, static and dynamic parts, which can be expressed as follows:

p_{c k t, k}^{m} = p_{k}^{s} + ε R_{k}^{m},

where

p_{k}^{s}

represents the static part and

ε R_{k}^{m}

represents dynamic power of user k , which is demonstrated as a linear function of attained data rate of the user.…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

“…ϵ denotes the consumption of dynamic power per unit data rate. The EE of k th user connected to RRH m can be modeled as follows:

η_{k}^{m} = \frac{R_{k}^{m}}{ξ \sum_{n ϵ N_{k}^{m}} p_{k, n} + p_{k}^{s} + ε R_{k}^{m}},

where ξ represents the reciprocal of the power amplifier's drain efficiency …”

Section: System Model and Problem Formulationmentioning

confidence: 99%

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Energy‐efficient resource allocation and RRH association in multitier 5G H‐CRANs

Ali

Ahmad

Khan

2018

Trans Emerging Tel Tech

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The rapid growth of connected devices and multimedia applications intensify the needs of high data rate and energy‐efficient networks. Multitier heterogeneous cloud radio access networks have been presented as a capable candidate for fifth‐generation networks for much higher data rate and energy efficiency (EE) than fourth generation. Therefore, in this paper, we consider the EE maximization in the uplink of a single‐carrier frequency division multiple access–based multitier heterogeneous cloud radio access network. We formulate a joint subchannel assignment, power allocation, and remote radio head association problem for EE maximization. Single‐carrier frequency division multiple access introduces subchannel exclusivity and subchannel adjacency constraints. These constraints, respectively, ensure the allocation of a subchannel to a single user at a time and the allocation of multiple subchannels to a user only if they are adjacent. In addition, we put constraints on each user's minimum data rate and maximum transmit power. Due to the simultaneous consideration of these four constraints, the solution of the formulated problem becomes harder. Therefore, a three‐step algorithm is developed, which solves this problem in an iterative manner. Simulation results verify that our proposed algorithm significantly improve the EE of the network.

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Energy‐efficient resource allocation for lifetime maximization in M2M networks

Tarerefa

Falowo

Ventura

2020

Int J Communication

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SummaryMachine‐to‐machine (M2M) communications is one of the major enabling technologies for the realization of the Internet of Things (IoT). Most machine‐type communication devices (MTCDs) are battery powered, and the battery lifetime of these devices significantly affects the overall performance of the network and the quality of service (QoS) of the M2M applications. This paper proposes a lifetime‐aware resource allocation algorithm as a convex optimization problem for M2M communications in the uplink of a single carrier frequency division multiple access (SC‐FDMA)‐based heterogeneous network. A K‐means clustering is introduced to reduce energy consumption in the network and mitigate interference from MTCDs in neighbouring clusters. The maximum number of clusters is determined using the elbow method. The lifetime maximization problem is formulated as a joint power and resource block maximization problem, which is then solved using Lagrangian dual method. Finally, numerical simulations in MATLAB are performed to evaluate the performance of the proposed algorithm, and the results are compared to existing heuristic algorithm and inbuilt MATLAB optimal algorithm. The simulation results show that the proposed algorithm outperforms the heuristic algorithm and closely model the optimal algorithm with an acceptable level of complexity. The proposed algorithm offers significant improvements in the energy efficiency and network lifetime, as well as a faster convergence and lower computational complexity.

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Optimal energy‐efficient resource allocation in uplink SC‐FDMA networks

Cited by 11 publications

References 30 publications

Maximizing energy efficiency in SC‐FDMA uplink with QoS guarantees and user satisfaction

Maximizing energy efficiency in SC‐FDMA uplink with QoS guarantees and user satisfaction

Energy‐efficient resource allocation and RRH association in multitier 5G H‐CRANs

Energy‐efficient resource allocation for lifetime maximization in M2M networks

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