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Green Wireless Telecommunication: Shift Towards 5G Network

Green Wireless Telecommunication: Shift Towards 5G Network

Author:  Harikrishnan P A, Rittu Madanamohan



With the rapid growth and evolution of information and communication technology, energy consumption is also growing at a very fast rate. It has also been reported mobile operators are among the top energy consumers. The energy consumption is growing even more with the deployment of 4G systems worldwide. Thus, there is an urgent need to shift from pursuing high capacity and spectral efficiency to energy efficient design. By reducing the power consumption of wireless networks, we can improve their energy efficiency. The energy efficiency of 5G networks is expected to be increased 100x times from 1000 mW /Mbps/sec in IMT-2000(International Mobile Telecommunication) to 10 mW/Mbps/sec in IMT-Advance and future IMT (Akshita Abrol,2016)

Energy efficiency is becoming a matter of great concern in the telecommunications community due to a number of reasons such as huge data rate requirements, increasing price of energy, the ecological impact of carbon, pressure and social responsibility for fighting climate change. The main focus is on relaying techniques between the Base station and the Mobile stations as a means to reduce the power consumption as well as to save the operator from incurring the huge cost of deployment of a new base station. (WILEY’s Text Book, 2015) (Akshita Abrol, 2016)

From the users’ perspective as well, energy efficiency is the need of the hour. The battery capacity is increasing only 1.5x per decade and has always been a concern for the user. In the future networks, there will be unbounded access to information and sharing of data everywhere and every time with the ever-increasing number of energy hungry applications. Therefore, to satisfy users’ demand for battery life, energy efficiency in wireless communication is imperative. Another factor under consideration is the health concern of the user. High power radiated by handsets while in use tend to harm the user in close proximity. Hence, shifting towards more energy efficient techniques becomes all the more important. (Akshita Abrol, and Rakesh Kumar Jha, 2016)

The need for adopting green communication has been realized worldwide. There is a focus on following a holistic approach for power optimization. The next generation architectures focus on developing new technology, cell deployment strategies and resource allocation policies to improve the energy efficiency of a wireless communication network. (WILEY’s Text Book, 2015)

Rise Of Fifth Generation (5g):

The 4G network soon will be replaced by the next generation 5G network to meet the increasing demand for high data rate. To meet the demand of the subscribers, improvement in the energy efficiency of the next generation networks is imperative. Green communication will play a major role in this. 5G includes techniques like Massive MIMO, Beam division multiple access, D2D communication and use of multiple radio access technologies. The power requirement of the network increases with the frequency in use. The prescribed safe RF exposure limit according to ICNIRP guidelines expressed in terms of power density (watt per square meter) is f/200 where f is the frequency in MHz. To maximize the efficiency upcoming systems, the scheduling of time and frequency resources needs to be coordinated with the power optimization techniques. The future networks providing even more data rate will require more such power saving techniques. (Akshita Abrol, 2016)



                       Fig 1. 5G Ecosystem (5GM Research Lab, Czech Technical University 2017)



(a) Power consumption of a wireless cellular network (b) Power consumption distribution in a BS.


Fig 2. Breakdown of power consumption in a cellular network and BS (Wu, J, 2015) (Hasan, 2011)


Energy Efficient Techniques in Telecommunication:

To make the network energy efficient, we have various ways like forming energy efficient architectures or using energy efficient radio technologies or obtaining energy efficiency in resource management. We concentrate our attention on power optimization using SWIPT, MILLIMETER WAVES, MASSIVE MIMO, C-RAN, SMALL CELLS and their integration with 5G network.


  • Simultaneous Wireless Information and Power Transfer (SWIPT)

Recently due to greater demand for energy efficiency in wireless communication, there is a lot of interest in integrating energy harvesting technologies in a wireless communication system. The upcoming technology is WPT (Wireless Power Transfer) where nodes charge their batteries from electromagnetic radiations. (K. Huang, 2013)

Strong signals increase power transfer but at the same time, they also increase the amount of interference. This technique can be most useful in the case of a sensor node or for the upcoming technology of Internet of Things in which the control signals will be used to charge the access point. The future networks will overcome its problems of path loss with the use of MIMO, small cells and mm waves. The element used for this purpose is a Rectenna, which converts microwave energy to direct current. This is achieved by splitting of the received signal to two orthogonal signals. SWIPT involves modification in the existing communication system. There can be three scenarios where we use SWIPT:

  • Near field scenario: Power is transferred using inductor or capacitor coupling and up to tenths of watt can be transferred with a range of 1 m.
  • Far field Scenario: Power is transferred using directive power beaming with directive antennas up to mW and range of several meters.
  • Far field low power scenario: Power is transferred with RF power scavenging up to micro Watts with a range of several km

This technique can be used in wireless charging of relay nodes, which are power, constrained. In 5G networks, with the coming of Massive MIMO technology more and more stray RF signals will be available which can be harnessed at the relays to harvest power. SWIPT, as discussed, is more successful in the near field scenario.  (I. Krikidis, 2014)

  • millimeter waves

Millimeter waves are expected to be one of the most promising technology of 5G. It is expected to solve the problem of bandwidth allocation for faster delivery of high quality video and multimedia content. With the growth of wireless industry, the demands of the consumer are increasing day by day, which may lead to the problem of congestion of the network by 2020. To overcome this in 5G, the wireless signals are being moved to a higher frequency band operating at millimeter wavelength between 30 and 300 GHz on the radio spectrum. The data rates are expected to increase to multi gigabit per second in the future. However, with the shift towards millimeter range, there will be high path loss and signal attenuation leading to limited communication range. (Y. Niu, 2015)

As the millimeter, range wavelength is very small so it will utilize spatial multiplexing techniques for both transmission and reception. Massive MIMO will play a major role in the millimeter range. Appropriate signal processing techniques such as adaptive beamforming will enable the transmitting node to direct signal towards the desired receiver. Hence, steerable array antennas will be used in the millimeter range spectrum to obtain high data rate and capacity. (T. S. Rappaport et al, 2013)

  • Massive MIMO:

In the 4G systems, MIMO is the key technology used to increase network capacity. It provides both diversity gain by sending the same signals through different paths between transmitter and receiver antennas as well as multiplexing gain by transmitting independent signals in parallel through spatial channels. Both also help in reducing energy efficiency (W. Liu, 2005). If the relation between transmission distance and energy consumption for SISO, SIMO and MIMO is compared, there is no doubt that MIMO consumes more circuit power due to more number of antennas (S. Cui, 2004). Therefore, it is beneficial for longer transmission distances. However, practically users are equipped with single antenna. So to overcome this limitation virtual MIMO also known as MU-MIMO has been proposed.

In 5G networks, a variant of MIMO is proposed in which a very large number of antennas are employed at the base station called Massive MIMO. Using this technology, the base station can communicate with multiple users simultaneously in the same frequency band hence providing high multiplexing as well as array gain at the same time. Massive MIMO technology is not only spectrum efficient but energy efficient as well. It is revealed that transmit power is decreased by the number of antennas at the base station so as to get same data rate like single antenna systems considering channel state information is known. (H. Q. Ngo, 2014)

Besides power scaling law, the ways for improving energy efficiency in Massive MIMO systems have also received considerable attention. The energy efficiency decreases with an increase in spectral efficiency with perfect channel state information has been shown. Whereas with imperfect channel state information, the energy efficiency increases with spectral efficiency in low power region and decreases in high power region. It is obvious that there are a large number of antennas in Massive MIMO, which consume high circuit power hence causing considerable reduction in energy efficiency. The technique of switching off some of the base station antennas is suggested similar to MIMO to improve the energy efficiency of the system. (E. Björnson, 2013)

  • C-RAN:

C-RAN is an acronym gaining popularity in the wireless industry, though it refers to two different meanings. The first meaning is a centralized radio access network, while the second meaning is cloud-based RAN. Both meanings are related concepts and involve a new architecture for network equipment at cell sites. Cloud-based RAN is a novel mobile architecture that has the potential to handle as many base stations as the network needs using the concept of virtualization. In C-RAN, the baseband and channel processing is virtualized and shared among operators in a centralized baseband pool. Such centralization and sharing allows for more dynamic traffic handling and better utilization of resources including base stations deployments. Such architecture would have the potential to decrease the expenses cost as base stations are virtualized instead of physically deployed in different areas. In addition, it reduces the energy and power consumption compared to traditional networks due to the fact that base stations will be located on the same physical device. (L. Chen, 2014)

The C-RAN architecture is designed to allow mobile operators to move the baseband processing unit to a central location in support of multiple remote radio heads. Until recently, the BBU was almost always located on-site near the bottom of the cellular antenna. C-RAN offers mobile operators the possibility to centralize multiple BBUs (Baseband Unit) in a single location, either at a cell site or at a centralized BBU pool location. This allows telecoms to simplify the amount of equipment needed at each individual cell site, among other benefits. The deployment of a C-RAN architecture also allow operators to save money, as it can cut costs in at least two ways. First, real estate is almost always less expensive at a data center location than at a cell tower site. Through this architecture, mobile operators can consolidate base station equipment for multiple cell sites at a central office or data center. Second, power loss is much lower with fiber than with cable, so the fiber connection associated with C-RAN can reduce operating expenses. 5G networks will need faster response times than today’s LTE networks as it includes connecting critical machines (M2M) as well as personal mobile devices. Therefore, C-RAN can lay the groundwork for the future 5G networks. (China Mobile Research Institute, 2011)

  • Small Cells:

Small cells are an umbrella term used for operator-controlled, low-powered and low-cost base stations operating in licensed spectrum. They can be densely deployed in order to provide high data rates. Small cells can be of different sizes depending on which they are classified as: –

  • Femto cells (up to 100 m)
  • Pico cells (up to 200 m)
  • Micro cells (up to 500 m)

Small cells can have a centralized base station or remote radio heads which can be wired or wireless with core network. They reduce the distance between the user and BS hence also reducing the transmit power required to overcome the pathless, especially in the indoor environment hence improving the Energy Efficiency of both uplink and downlink communication.

There is a Small Cell Access point, which will be installed on buildings and will communicate with Base Station. The Mobile Stations located inside the building will only need to communicate to the SCA and not to the far located base station hence decreasing both the load and power requirement. Deployment of Small cells requires minimum changes in the current standard and can save a lot of user’s battery consumption. The trade-off between traffic offloading and energy consumption can be implemented through BS sleeping strategy (To improve EE by switching off small cell base stations (BSs) or keeping them in energy-saving mode while preserving the quality of service (QoS)).(A. Prasad, 2013)

Energy saving by different techniques: (Akshita Abrol, 2016)


S.No Technique Energy Efficiency
1 SWIPT 30%
2 Beam steering (4 antennas) 55%
3 Small Cells 11.1%
4 C-RAN 21.2%
5 Massive MIMO 30.7 Mbit/J


Current projects in energy efficiency in wireless communication:

S.No Project Name Year of Initiation Aim of Research Area of Research Reference ( URL)
1 5GrEEn January 2013 To design environment friendly 5G mobile networks Efficient mobile access networks and backhaul solutions


To develop the 5G framework with efficient integration of various technologies 5G radio access network design and developing an open –Source 5G evaluation and visualization tool
3 Green Wireless Communication 2013 To lower energy consumption of future wireless radio systems Development and performance analysis of new wireless channel estimation techniques, Transceiver design optimization under uncertainty and BS sleeping strategy.
4 Greenet July 2011 To analyze, design and optimize energy efficient wireless communication systems and networks  

Cooperative communications, cognitive networks and network coding.
5 GreenTouch 2010 To deliver the architecture, specifications and roadmap to increase network energy efficiency by a factor of 1000  

Energy efficient cloud, optical networks and home networks.
6 OPERA-Net2 December 2011 To reduce the overall environmental impact of mobile radio networks by extending the results of OPERA-Net project. Energy and material efficiency and use of renewable energy for telecom networks.


Future Challenges:

The next generation networks are expected to meet the needs of the consumers along with providing a solution for green communication. Use of new techniques such as SWIPT, massive MIMO, mm wave as well as continued use of small cells and relays in the next generation networks will impose new research challenges.

SWIPT is a promising technology for future but has unsatisfactory results for longer distances due to high path loss. Spatial diversity can be used to overcome this path loss. Thus, use of massive MIMO along with SWIPT need to be investigated for better results. Also, efficient circuit modules need to be developed, which can reduce the power splitting loss as well as cost of the hardware.

Energy efficient resource management helps in saving huge amount of power. The handoff and coverage issues between neighboring small cells and their impact on EE needs to be further estimated. The QoS requirement of a particular application and time varying channel condition and its relation with EE needs to be developed.

The next generation networks are expected to support heterogeneous networks. So, interference management as well as handoff between various networks with respect to EE needs to be studied. The tradeoff between spectral and energy efficiency for heterogeneous networks also needs further investigation. The EE of massive MIMO network with full duplex relay channel needs to be studied. The EE of massive MIMO in multiple cell scenario needs to be investigated to eliminate the effect of interference.

Further research also needs to be carried out for efficient implementation of base station sleep modes to save maximum possible power. The power allocation strategy by base station to small cells and its impact on the energy efficiency of the network needs investigation. The power control strategy and efficient algorithm in D2D communication to minimize interference at the same time ensuring optimum SNR needs to be developed. The tradeoff between power consumed by hardware and power saving of the network by using massive MIMO with beamforming in the millimeter range also needs to be investigated along with the overall energy efficiency of the network.


We have discussed the growing need for energy efficiency in the next generation networks. We have analyzed the trends in the field of wireless communications in the last decade, which indicated a shift towards pursuing green communication for the next generation network. The importance of choosing the appropriate EE metric has also been discussed. Further, we have gone through the various techniques, which can be used in the future for optimizing the power of the network and the presented, a summary of the work that has already been done to improve energy efficiency of network using these techniques. EE techniques such as Massive MIMO, C-RAN, SMALL CELLS and SWIPT have been briefed and few projects undergoing on Green Communication was mentioned. Various challenges for future research for improving EE of wireless network have also been discussed.


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