Energy efficiency of LTE macro base station

Abdulkafi, Ayad Atiyah; Kiong, Tiong Sieh; Koh, Johnny Siaw Paw; Chieng, David; Ting, Alvin; Ghaleb, Abdulaziz M.

doi:10.1109/istt.2012.6481597

Cited by 15 publications

(11 citation statements)

References 11 publications

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“…The cell radius for each type of BS is calculated based on a cell coverage requirement of C D 95% by setting the transmit powers for MeNB, MieNB and PeNB to 46, 35 and 30 dBm, respectively. Our previous work in [20] has demonstrated the influence of BW on EE. It is shown that EE increases significantly as the BW increases.…”

Section: Numerical Results and Discussionmentioning

confidence: 99%

“…The cell coverage area C , which is the fraction of cell area where the received power of user terminal is above P min , can be written as

C MathClass-rel= Q (a) MathClass-bin+ normalexp ((), \frac{2 MathClass-bin- 2 ab}{b^{2}}) Q ((), \frac{2 MathClass-bin- ab}{b})

where the Q‐function is defined as the probability that a Gaussian random variable X with mean 0 and variance 1 is greater than z

Q (z) MathClass-rel= prob (X ⩾ z) MathClass-rel= \frac{1}{\sqrt{2 π}} {falsefalse}_{MathClass-op\int}^{z} normalexp ((), MathClass-bin- \frac{x^{2}}{2}) dx

and

a MathClass-rel= \frac{P_{normalmin} MathClass-bin- P_{italicrx} (R_{g})}{σ_{ΨdB}} MathClass-punc, b MathClass-rel= \frac{10 α {normallog}_{10} (e)}{σ_{ΨdB}}

where α is the PL exponent and σ ψdB is the standard deviation of shadow fading, whereas P rx ( R g ) represents the received power at cell edge ( R g ). Hence, the coverage area of a cell is a function of receiver sensitivity P min , carrier frequency f , transmitted power P tx , PL exponent α and shadowing standard deviation σ ψdB . By limiting the coverage area to a certain size, the network performance in terms of achievable data rates and efficiencies within each BS can be estimated.…”

Section: Network Modelsmentioning

confidence: 99%

“…where˛is the PL exponent and dB is the standard deviation of shadow fading, whereas P rx .R g / represents the received power at cell edge .R g /. Hence, the coverage area of a cell is a function of receiver sensitivity P min , carrier frequency f , transmitted power P tx , PL exponent and shadowing standard deviation dB [19,20]. By limiting the coverage area to a certain size, the network performance in terms of achievable data rates and efficiencies within each BS can be estimated.…”

Section: Coverage Modelmentioning

confidence: 99%

See 2 more Smart Citations

Energy‐aware load adaptive framework for LTE heterogeneous network

Abdulkafi

Chieng

Kiong

et al. 2014

Trans. Emerging. Tel. Tech.

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One of the main approaches for improving the network energy efficiency (EE) is through the introduction of load adaptive techniques, where the network's components/subsystems are switched off when the network is lightly loaded. Optimising such a dynamic operation in a heterogeneous network (HetNet) remains an active topic of research. In this paper, a traffic load‐adaptive model that aims to evaluate the EE of base stations in Long Term Evolution (LTE) HetNet is presented. First, a model that simulates the load‐adaptive power consumption behaviour of LTE HetNet is developed. In this regard, a load adaptation factor is introduced to assess the network's EE performance. The model also adapts and predicts the achievable data rate of each base station with respect to the traffic load. Our study shows that the fully load‐adaptive LTE HetNet can significantly improve network's EE up to 10%, 40%, and 80% for high, medium, and low loads, respectively, as compared to the conventional non load‐adaptive HetNet. In addition, we show that the full adaptive network operation can achieve significant EE gains under a realistic daily traffic profile up to 86%. The proposed evaluation model is essential to assess the network EE and can be used in future studies that focus on improving the adaptation level of the already installed network equipments. Copyright © 2014 John Wiley & Sons, Ltd.

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Section: Numerical Results and Discussionmentioning

confidence: 99%

“…The cell coverage area C , which is the fraction of cell area where the received power of user terminal is above P min , can be written as

C MathClass-rel= Q (a) MathClass-bin+ normalexp ((), \frac{2 MathClass-bin- 2 ab}{b^{2}}) Q ((), \frac{2 MathClass-bin- ab}{b})

where the Q‐function is defined as the probability that a Gaussian random variable X with mean 0 and variance 1 is greater than z

Q (z) MathClass-rel= prob (X ⩾ z) MathClass-rel= \frac{1}{\sqrt{2 π}} {falsefalse}_{MathClass-op\int}^{z} normalexp ((), MathClass-bin- \frac{x^{2}}{2}) dx

and

a MathClass-rel= \frac{P_{normalmin} MathClass-bin- P_{italicrx} (R_{g})}{σ_{ΨdB}} MathClass-punc, b MathClass-rel= \frac{10 α {normallog}_{10} (e)}{σ_{ΨdB}}

Section: Network Modelsmentioning

confidence: 99%

Section: Coverage Modelmentioning

confidence: 99%

See 1 more Smart Citation

Energy‐aware load adaptive framework for LTE heterogeneous network

Abdulkafi

Chieng

Kiong

et al. 2014

Trans. Emerging. Tel. Tech.

Self Cite

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“…An investigation on the impact of these factors on EE has been presented in [46]. Authors of [116] presented the tradeoffs between gains in cell throughput and reception technologies and the increased energy consumption that they induced in cellular BSs. The EE in term of ECR of MIMO schemes applicable for 3GPP LTE is analyzed on different antenna configuration in [89] and [117].…”

Section: Bs's Energy-awarenessmentioning

confidence: 99%

CloudSwitch: A State-aware Monitoring Strategy Towards Energy-efficient and Performance-aware Cloud Data Centers

2016

KSII TIIS

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The research on optimization of cellular network's energy efficiency (EE) towards environmental and economic sustainability has attracted increasing attention recently. In this survey, we discuss the opportunities, trends and challenges of this challenging topic. Two major contributions are presented namely 1) survey of proposed energy efficiency metrics; 2) survey of proposed energy efficient solutions. We provide a broad overview of the state of-the-art energy efficient methods covering base station (BS) hardware design, network planning and deployment, and network management and operation stages. In order to further understand how EE is assessed and improved through the heterogeneous network (HetNet), BS's energy-awareness and several typical HetNet deployment scenarios such as macrocell-microcell and macrocell-picocell are presented. The analysis of different HetNet deployment scenarios gives insights towards a successful deployment of energy efficient cellular networks.

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“…Menghitung sensitifitas penerima (sensitivity receiver) Sensitifitas penerima (Pmin), seperti ditunjukkan pada formula (1), adalah daya minimum yang diterima dimana persyaratan throughput masih terpenuhi (Abdulkafi et al, 2012) atau rata-rata kuat sinyal minimum yang ditangkap antena dengan SINR yang cukup untuk skema modulasi yang digunakan untuk memenuhi persyaratan throughput minimum sebesar 95% dari nilai throughput maksimum yang mungkin (Belhouchet & Ebdelli, 2010 Dengan mengasumsikan model propagasi tertentu maka akan diperoleh radius cakupan dari sebuah BS berdasarkan rugi-rugi lintasan maksimum yang diperoleh dari perhitungan sebelumnya. Model propagasi dapat diklasifikasikan menjadi model empiris dan model deterministik (Singh, 2012 …”

Section: Coverage Analysis (Analisis Cakupan)unclassified

Kebutuhan Frekuensi untuk Public Protection and Disaster Relief (PPDR) Pita Lebar di Indonesia

Yuniarti¹

2015

BPOSTEL

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Demands regarding on application development of broadband Public Protection and Disaster Relief (PPDR) are increasing in recent years A B S T R A K Kata kunci : Public Protection and Disaster ReliefKejadian PP1 Kejadian PP2 LTE FDD LTE TDD Permintaan akan pengembangan aplikasi Public Protection and Disaster Relief (PPDR) pita lebar terus meningkat dalam beberapa tahun terakhir seiring dengan kebutuhan untuk tanggap bencana yang lebih efisien dan efektif. Penelitian ini mengidentifikasi kebutuhan frekuensi PPDR pita lebar di Indonesia yang meliputi kejadian harian (PP1) dan kejadian darurat besar (PP2) pada pita frekuensi 400 MHz dan 800 MHz. Teknik pemodelan dan simulasi digunakan untuk menghitung kebutuhan frekuensi berdasarkan data skenario dan jumlah kejadian yang diperoleh. Hasil penelitian menunjukkan bahwa kebutuhan frekuensi untuk mengakomodasi kejadian PP1 diperkirakan sebesar 2x10 MHz. Sedangkan, kebutuhan frekuensi untuk kejadian PP2 diperkirakan sebesar 2x20 MHz untuk LTE FDD atau 30 MHz untuk LTE TDD. PendahuluanKebutuhan dalam penanganan kejadian yang terkait dengan Public Protection and Disaster Relief (PPDR) yang lebih efisien dan lebih efektif mendorong peningkatan pengembangan aplikasi pita lebar seperti aplikasi video bergerak real time. Di sisi lain, aplikasi PPDR yang ada saat ini kebanyakan berada pada pita sempit yang mendukung aplikasi suara dan kecepatan data rendah, terutama di lebar pita kanal 25 kHz atau dibawahnya, termasuk di Indonesia (Yuniarti, 2013). ITU di dalam WRC-2015 mengagendakan untuk meninjau dan merevisi Resolusi 646 WRC-2003 untuk PPDR berdasarkan Resolusi 648 WRC-2012 tentang kajian untuk mendukung PPDR pita lebar (ITU, 2012).Frekuensi untuk keperluan penanganan sementara bencana (PPDR) di Indonesia dialokasikan pada pita 409 -417 MHz dan 422,5-426,25 MHz (Kementerian Komunikasi dan Informatika, 2010). Akan tetapi, meskipun telah terdapat alokasi frekuensi untuk PPDR, lembaga atau organisasi pemerintah terkait seperti kepolisian dan BNPB memiliki alokasi frekuensi khusus yang berada di luar alokasi PPDR. Dalam rangka pemanfaatan spektrum frekuensi radio yang lebih efisien, pemerintah dalam hal ini Kementerian Komunikasi dan Informatika merencanakan untuk menggabungkan seluruh alokasi frekuensi untuk instansi 1

show abstract

Energy efficiency of LTE macro base station

Cited by 15 publications

References 11 publications

Energy‐aware load adaptive framework for LTE heterogeneous network

Energy‐aware load adaptive framework for LTE heterogeneous network

CloudSwitch: A State-aware Monitoring Strategy Towards Energy-efficient and Performance-aware Cloud Data Centers

Kebutuhan Frekuensi untuk Public Protection and Disaster Relief (PPDR) Pita Lebar di Indonesia

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