Energy-Efficient Massive MIMO Network

Main Article Content

Israa Hilme Ahmed
https://orcid.org/0009-0001-6850-936X
Ayad Atiyah Abdulkafi
https://orcid.org/0000-0002-1160-6011

Abstract

Massive Multiple-Input Multiple-Output (Massive MIMO) is widely regarded as a highly promising technology for the forthcoming generation of wireless systems. The massive MIMO implementation involves the integration of a substantial number of antenna elements into base stations (BSs) to enhance spectral efficiency (SE) and energy efficiency (EE). The energy efficiency (EE) of base stations (BSs) has become an increasingly important issue for telecommunications network operators due to the need to take care of profitability while simultaneously minimizing their detrimental effects on the environment and addressing economic challenges faced by wireless communication operators. In this paper, the EE of massive MIMO networks and the relationship between EE, SE, and other parameters like bandwidth (B), number of antennas (M), circuit power, and number of users’ equipment (K) are discussed and investigated. For a fixed circuit power (PFIX), simulation results showed that the EE could be increased by about 1.12 as the number of antennas was doubled. The findings in this work also indicated an almost linear relationship between maximum EE and optimal SE, with a massive increase in the number of antennas when the power consumed by each antenna (PBS) was included in circuit power. In addition, when considering the power consumed per user’s equipment (PUE) impact, the SE increased with the ratio (M/K), in which SE showed a cubic relationship against M/K. On the other hand, the EE increased with M/K ratio until M/K reached a specific value. The maximum EE (and hence optimum SE) was achieved by massive MIMO, where the number of antennas was three times the number of users. However, EE started degrading after this value, as the number of antennas was considered larger than the users’ and consumed more energy, resulting in EE degradation.

Metrics

Metrics Loading ...

Article Details

Section
Articles

Plaudit

References

Ye J, He Y, Ge X, Chen M. Energy efficiency analysis of 5G Ultra-dense networks based on random way point mobility models. 19th International Symposium on Wireless Personal Multimedia Communications (WPMC): IEEE; 2016. pp. 177-182.

Boshkovska E, Ng DWK, Dai L, Schober R. Power-efficient and secure WPCNs with hardware impairments and non-linear EH circuit. IEEE Transactions on Communications 2017;66(6):2642-2657. DOI: https://doi.org/10.1109/TCOMM.2017.2783628

Shahab MM, Hardan SM, Hammoodi AS. A new Transmission and Reception Algorithms for Improving the Performance of SISO/MIMO-OFDM Wireless Communication System. Tikrit Journal of Engineering Sciences 2021;28(3):146-158. DOI: https://doi.org/10.25130/tjes.28.3.11

Nawaf SF. Channel Capacity Improvement of MIMO Communication Systems using Different Techniques. Tikrit Journal of Engineering Sciences 2018;25(1):36-41. DOI: https://doi.org/10.25130/tjes.25.1.06

Larsson EG, Edfors O, Tufvesson F, Marzetta TL. Massive MIMO for next generation wireless systems. IEEE communications magazine 2014;52(2):186-195. DOI: https://doi.org/10.1109/MCOM.2014.6736761

Al-Heety, A. T., Islam, M. T., Rashid, A. H., Ali, H. N. A., Fadil, A. M., & Arabian, F.Performance Evaluation of Wireless data traffic in Mm wave massive MIMO communication. Indones J Electr Eng Comput Sci 2020;20(3). DOI: https://doi.org/10.11591/ijeecs.v20.i3.pp1342-1350

Jahid A, Hossain S. Dimensioning of zero grid electricity cellular networking with solar powered off-grid BS. 2017 2nd International Conference on Electrical & Electronic Engineering (ICEEE): IEEE; 2017. p. 1-4. DOI: https://doi.org/10.1109/CEEE.2017.8412862

Jahid A, Ahmad AS, Hossain MF. Energy efficient BS cooperation in DPS CoMP based cellular networks with hybrid power supply. 2016 19th International Conference on Computer and Information Technology (ICCIT): IEEE; 2016. p. 93-98. DOI: https://doi.org/10.1109/ICCITECHN.2016.7860175

Malmodin J, Lundén D. The energy and carbon footprint of the global ICT and E&M sectors 2010–2015. Sustainability 2018;10(9):3027. DOI: https://doi.org/10.3390/su10093027

Malmodin J, Bergmark P, Lundén D. The future carbon footprint of the ICT and E&M sectors. On Information and Communication Technologies 2013;12.

Riva D. GeSI SMARTer 2020: The Role of ICT in Driving a Sustainable Future. 2012.

Initiative Ge-S. SMARTer2030, ICT solutions for 21st century challenges. Executive Summary: ICT Solutions for 21st Century Challenges 2015;8.

Andrae AS, Edler T. On global electricity usage of communication technology: trends to 2030. Challenges 2015;6(1):117-157. DOI: https://doi.org/10.3390/challe6010117

Mohammed BF. Position control of solar panel receiver by joint generated power and received signal power maximization. Tikrit Journal of Engineering Sciences 2018;25(3):24-29. DOI: https://doi.org/10.25130/tjes.25.3.05

Alsharif MH. Comparative analysis of solar-powered base stations for green mobile networks. Energies 2017;10(8):1208. DOI: https://doi.org/10.3390/en10081208

Lubritto, C., Petraglia, A., Vetromile, C., Curcuruto, S., Logorelli, M., Marsico, G., & D’Onofrio, A. Energy and environmental aspects of mobile communication systems. Energy 2011;36(2):1109-1114. DOI: https://doi.org/10.1016/j.energy.2010.11.039

Hou J, Gao Y. Greenhouse wireless sensor network monitoring system design based on solar energy. 2010 International Conference on Challenges in Environmental Science and Computer Engineering: IEEE; 2010. p. 475-479. DOI: https://doi.org/10.1109/CESCE.2010.274

Yi G, Guiling S, Weixiang L, Yong P. Wireless sensor node design based on solar energy supply. 2nd International Conference on Power Electronics and Intelligent Transportation System (PEITS): IEEE 2009. p. 203-207.

Zedan MH, Khalaf HJ, Shaker AM. Optimum Design of Parabolic Solar Collector with Exergy Analysis. Tikrit Journal of Engineering Sciences 2017;24(4):49-57. DOI: https://doi.org/10.25130/tjes.24.4.06

Björnson E, Hoydis J, Sanguinetti L. Massive MIMO networks: Spectral, energy, and hardware efficiency. Foundations and Trends® in Signal Processing 2017;11(3-4):154-655. DOI: https://doi.org/10.1561/2000000093

Shannon CE. A mathematical theory of communication. The Bell system technical journal 1948;27(3):379-423. DOI: https://doi.org/10.1002/j.1538-7305.1948.tb01338.x

Hardan SM. Improvement The Transmission Efficiency For Wireless Packet Communication Systems Using Automatic Control for power And Time Slot Width Of Slotted Non persistent ISMA Protocol. Tikrit Journal of Engineering Science (TJES) 2011;18(3):81-88. DOI: https://doi.org/10.25130/tjes.18.4.05

Assarut R, Husada MG, Yamamoto U, Onozato Y. Data rate improvement with dynamic reassignment of spreading codes for DS-CDMA. Computer Communications 2002;25(17):1575-1583. DOI: https://doi.org/10.1016/S0140-3664(02)00054-3

Kunihiro K, Hori S, Kaneko T. High efficiency power amplifiers for mobile base stations: Recent trends and future prospects for 5G. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences 2018;101(2):374-384. DOI: https://doi.org/10.1587/transfun.E101.A.374

Zhang J, Wei Y, Björnson E, Han Y, Jin S. Performance analysis and power control of cell-free massive MIMO systems with hardware impairments. IEEE Access 2018;6:55302-55314. DOI: https://doi.org/10.1109/ACCESS.2018.2872715