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Towards green communication in 5G systems: Survey on beamforming concept

2020; Institution of Engineering and Technology; Volume: 15; Issue: 1 Linguagem: Inglês

10.1049/cmu2.12066

1751-8636

Khalid S. Mohamed, Mohamad Yusoff Alias, Mardeni Roslee, Y.M. Raji,

Advanced Wireless Communication Technologies

IET CommunicationsVolume 15, Issue 1 p. 142-154 ORIGINAL RESEARCH PAPEROpen Access Towards green communication in 5G systems: Survey on beamforming concept Khalid S. Mohamed, Corresponding Author khalidkaradh@hotmail.com orcid.org/0000-0001-5835-4299 Centre for Wireless Technology (CWT), Faculty of Engineering, Multimedia University, Persiaran Mutlimedia, Malaysia Correspondence Khalid S. Mohamed, Centre for Wireless Technology (CWT), Faculty of engineering, Multimedia University, Persiaran mutlimedia, Cyberjaya 63100, Malaysia. Email: khalidkaradh@hotmail.comSearch for more papers by this authorMohamad Y. Alias, Centre for Wireless Technology (CWT), Faculty of Engineering, Multimedia University, Persiaran Mutlimedia, MalaysiaSearch for more papers by this authorMardeni Roslee, orcid.org/0000-0001-8250-4031 Centre for Wireless Technology (CWT), Faculty of Engineering, Multimedia University, Persiaran Mutlimedia, MalaysiaSearch for more papers by this authorYusuf M. Raji, orcid.org/0000-0002-6838-2952 Fibre Optic Research Centre (FORC), Faculty of Engineering, Multimedia University, Persiaran Mutlimedia, MalaysiaSearch for more papers by this author Khalid S. Mohamed, Corresponding Author khalidkaradh@hotmail.com orcid.org/0000-0001-5835-4299 Centre for Wireless Technology (CWT), Faculty of Engineering, Multimedia University, Persiaran Mutlimedia, Malaysia Correspondence Khalid S. Mohamed, Centre for Wireless Technology (CWT), Faculty of engineering, Multimedia University, Persiaran mutlimedia, Cyberjaya 63100, Malaysia. Email: khalidkaradh@hotmail.comSearch for more papers by this authorMohamad Y. Alias, Centre for Wireless Technology (CWT), Faculty of Engineering, Multimedia University, Persiaran Mutlimedia, MalaysiaSearch for more papers by this authorMardeni Roslee, orcid.org/0000-0001-8250-4031 Centre for Wireless Technology (CWT), Faculty of Engineering, Multimedia University, Persiaran Mutlimedia, MalaysiaSearch for more papers by this authorYusuf M. Raji, orcid.org/0000-0002-6838-2952 Fibre Optic Research Centre (FORC), Faculty of Engineering, Multimedia University, Persiaran Mutlimedia, MalaysiaSearch for more papers by this author First published: 10 December 2020 https://doi.org/10.1049/cmu2.12066AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat Abstract Connectivity in recent wireless communication is accessible anywhere because of the large footprints of both cellular and WiFi networks. Yet, the broadcasting in wireless technology increases the susceptibility of signals to contemporary challenges such as interference, fading, and distortion. In addition, the energy of signals is lost because of Doppler effects and scattering caused by the obstacles in the channel. The use of smaller base stations, exploitation of higher frequencies and millimetre waves, and the expansion towards massive multiple-input multiple-output makes beamforming one of the most important key technologies in fifth generation (5G) systems. Besides the energy efficiency enhancements because of the narrower beamwidths, it reduces the broadcasting probability by adaptively steering the signals towards the targeted receivers while reducing the reception for nearby receiver, that is less interference. It also increases the energy efficiency of the signals because of the narrow beamwidth. In this work, the 5G technology challenges, two of the most known channel models, applications is briefly received. The fundamentals of beamforming technology are also described and provide the necessary information to understand the technology. 1 INTRODUCTION Extensive deployment of fifth generation (5G) communication started to take place in few countries around the world [1]. Therefore, extensive studies on channel modelling and signal measurements with respect to the physics fundamentals are needed to properly design the architecture whereby such signals are precisely transmitted and received [2]. The motivation of using such technology is that it promises higher data rates and enhanced network performance relative to the existing ones. This is typically achieved by exploiting wider ranges of bandwidth in higher frequency bands, for example 30 Gigahertz (GHz) [3]. For instance, millimetre wave (mmWave) communication provides up to 10 Terabits data rates and spectral efficiency (SE) of approximately 100 bps/Hz over a bandwidth of about 270 Megabits per second (Mbps) (30–300 GHz frequency band) [4, 5]. Figure 1 shows the Federal Communication Commission (FCC) initiative of bandwidth allocation in 5G. Clearly, the existing long-term evolution (LTE) system will no longer be able to embrace the network demands such as data rates and spectrum needed neither solve for the challenges such as the excessive interference [6]. FIGURE 1Open in figure viewerPowerPoint FCC initiative to enable 5G Given that, investigations on the performance of the system with respect to the operating frequency and bandwidth such as the Terahertz (THz) bandwidths are already ongoing because of the high capacity figures it provide. On the other hand, higher frequencies are extremely fragile especially in wider distances which enforces the fact that higher frequencies are best for indoor communications [7, 8]. This has encouraged researchers to investigate the possibility of designing transmitters that are able to radiate stronger signals without increasing the power, examples of such techniques are beamforming, and multiple-input multiple-output (MIMO). These techniques enable high signal gains and may extend the reach of the signals but it also increases antenna sizes, and the complexity of antenna designs at both transmitters and receivers. This is evidenced by the study in [9] which concluded that performance degradation is proportional to antenna size. The study has also highlighted some of the technical challenges that researchers should realise before approaching the technology. While massive MIMO and cell-free technologies are deemed to be some of the exciting innovations for the 5G communication paradigm, beamforming extends the use of such technologies by exploiting the broad range of antenna elements to provide high security, enhanced energy efficiency (EE), good communication reliability, and low signal processing complexity. Cell-free technology is one of the areas that could adopt the beamforming technology to enhance the directivity and connectivity in wireless networks whereby a user is connected to several distributed antennas instead of the conventional systems to insure maximum sum rate reception. [10, 11]. Subsequently, interference is considered the most destructive factor to wireless communication systems [12]. Therefore, the availability of proper channel models of the conventional LTE communication system such as Rayleigh [13], Okumura-Hata [14] etc. has made it easy for researchers to investigate and propose innovative ways to overcome the interference issue. Nevertheless, the existence of limited channel representation that precisely model 5G channels may have limited the availability of realistic simulation models. In that regard, two famous channel models were developed to visualise and understand the signal behaviour, namely: the third generation partnership project (3GPP) [15] and New York university simulation (NYUSIM) [16]. On the other hand, electromagnetic radiations are generally categorised into non-ionising radiations such as infra-red, microwave, radio frequency etc., and ionising radiations such as X-rays. The non-ionising radiations define the ones that have insufficient energy to break the atoms and turn them into ions, that is it does not cause any damages to the human body. Whereas the ionising radiations at high doses increase the risks of cancer, birth and DNA defects etc. [17]. However, concerns of thermal heating caused by the electromagnetic radiations were raised. Therefore, the FCC limits the maximum exposure to radio frequency energy measured by the specific absorption ratio (SAR) to 1.6 watts per kilogram for mobile phones. The FCC approval indicates that the device will never exceed the maximum exposure levels, but it does not describe the consumers exposure during normal use [18]. Given that, consumers may accidentally overheat a specific part of their body, for example head, torso, legs etc. while using their phones, for example talking for long durations on the phone. Therefore, manufacturers advise to keep phone conversations short, use of plug-in earpieces, and that a minimum distance of 5–20 mm to be maintained between the consumer's body and his/her phone. These recommendations make us wonder about the extent of the maximum exposure that human tissues can tolerate especially when considering cellular base stations that are deployed on top of houses and at the middle of residential areas. And while many people are happy with the pays of telecommunication companies for deploying cellular base stations on top of their houses, some are worried about the threats posed by these especially if the number of base stations is to be increased, for example in 5G communication systems. Despite the claims of the harmfulness of the electromagnetic signals, it can be said that through directional transmission, consumers' concerns will be put to rest. Not only this, but quality of service will also be improved. Therefore, the motivation of this paper is to address the efforts of some researchers on beamforming methods which contribute to minimising the radiations in all directions and enhance the network performance. The contributions are summarised as follows: 1. Enhanced understanding of interference in 5G communication and beamforming methods that achieves less interference (i.e. green communication). 2. Summarised, yet efficient presentation on the important 5G channel modelling models. 3. The evaluations of different interference mitigation techniques provide clearer understanding of the effectiveness of beamforming techniques. 4. The presentation of different works on this issue promotes the work to be a reference for beamforming in future 5G systems. The remainder of this paper is divided as follows: Section 2 describes the 5G systems and addresses the concerns in relation to it, the channel models are addressed in Section 3. Section 4 discusses the interference aspect in 5G systems and provides some of the research contributions that link beamforming and interference mitigation in 5G communication system. Beamforming fundamentals and how it can be implemented are presented in Section 5, and Section 6 summarises the paper. 2 5G COMMUNICATION SYSTEM The motivation behind the development of 5G system (i.e. the rapid unprecedented growth of the network, and the increasing network demands) has triggered the researchers to approach the limitations of the fourth generation (4G) communication systems to underlay the new 5G system specifications and services. This network growth can be illustrated in Figure 2 in which the network supports numerous kinds of communications (e.g. agricultural monitoring services [19, 20], medical services [21] etc.). In such environments, the amount of information exchanged is impressively large which requires advanced technologies to cater for such. The relation between the frequency and the data rate is a major concern whereas low frequencies will not be able to support such demands and high frequencies cannot support wider coverages. Various studies concluded that the traffic is expected to grow to 24.3 Exabytes per month by 2019 on top of the requirements of emerging new services such as cloud computing, smart homes, drone systems, multimedia streaming, point-to-point communication etc. which has now been exceeded already. Therefore, 5G communication system is the revolution of wireless communication in which impressive applications and exceptional data rates and performance are supported. This necessitates fundamental changes in communication infrastructure and innovative realisation of the expected performance. Some of the 5G applications, services, and major challenges are described in the subsequent subsections. FIGURE 2Open in figure viewerPowerPoint The 5G communication environment 2.1 Internet of things Due to the rapid changes and implementation of new technologies and the trendy nature of the term, internet of things (IOT) is one of the most misused and misunderstood term in modern day technology [22]. Many years have passed since the appearance of the term and its emergence as one of the major research topics in information and communications technology (ICT) [23]. While many have considered IOT to be only radio frequency identification (RFID) devices, others thought they were just sensor networks, others considered it as a form of machine-to-machine type of communication. The consideration of IOT as mere sensor networks or RFID devices stems from the fact that these two technologies were the main enablers of IOT [24]. The discordant definition of IOT by different scientific literature due to their niche segment and application also failed to offer much clarity on the term. Another reason for this ambiguity is the huge overlap between IOT and other research areas and the generational evolution of IOT itself. However, IOT as defined by the international telecommunications union (ITU) is a global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies [25]. This network of interconnected things promises to deliver new services within and across industries. The ”things” in IOT refers to objects in the physical world (physical things) or of the information world (virtual world) that are able to be identified and integrated into communication networks as illustrated in Figure 3. It could be a person with a heart rate monitor, a home with smart electric meter, an automobile with sensors and actuators to enable autonomous features, and so on. Referring to the definition given by ITU in [25], IOT can be loosely regarded as the seamless internet-like connection of billions of IOT devices (physical things) designed to perform non-complex tasks. These devices (physical things) which are usually equipped with sensors, actuators, processors and communication modules to perform a specific meaningful task are usually constrained by their limited capabilities in terms of computational power and storage resources. Although these limited capabilities may seem as a disadvantage at first, they are actually a desirable feature of IOT devices (physical things). IOT devices (physical things) are often required to be extremely power efficient, as they often work on batteries and are required to work for many years in the field under a single charge. Depending on their design and application, these devices will continuously gather, transmit, receive, manipulate, and act on data in real time over a particular time period without the need for human intervention. Such a continuous exchange of data has been envisaged to put a lot of pressure on the current network. FIGURE 3Open in figure viewerPowerPoint Internet of things connectivity The prediction that billions of IOT devices will be connected in the near future (an average of six to seven devices per person) has led to question as to how to connect all these devices with the current wireless infrastructure. The current infrastructure lacks the capacity to cater for all these with a minimal amount of lag. This, among many other reasons has led to the emergence of the 5G wireless network technology. 5G standards are designed to support IOT with promising features and tackle the challenges peculiar to the current 4G LTE standards. These features include [26]: - More connected devices: the number of connected devices is expected to increase to at least 10 times more than the current figures. - Higher data rates: similarly, least of 10 times higher data rates. - Less energy consumption: comparatively lower energy consumption. - Ultra low latency: extremely low latency of <1 ms. - Users per area volume: the number of users per area is also expected to expand 1000 times higher. The potential use cases for IOT may include [27]: - Smart home: recent technologies enable automating of house appliances such as television, doors, thermostat, surveillance systems etc. and allow full control of the house from a remote location. - Smart cities: this describes urban areas that utilises IOT sensor networks and technologies to collect, analyse, and process data such as air quality, temperature, and humidity. - Smart metering: this is achieved through electronic devices that are able to record energy consumption and relay it to suppliers for billing and monitoring purposes. - Smart agriculture: IOT also enables using modern technology to enhance not only the quality but the quantity of agricultural products through soil and data monitoring and managing, respectively. - Smart transportation: in conjunction with the smart cities applications and sensors, this is expected to allow intelligent transportation in which no traffic congestion occurs. - eHealth services: accessing and monitoring patients health records, conditions, diseases diagnosis, and remote surgery. - Environmental monitoring: this helps in reducing the pollution, energy consumption, global warming etc. - Industrial control: machineries in factories and industrial firms is reliable. - Smart wearables: such as fitness and sports to monitor the physical performance during trainings. - Automotive driving or internet of vehicles: self-driving and thinking vehicles to enable trip duration and road optimisation. 2.2 Requirements There are seven key elements recognised by Samsung to enable 5G communication, these are: Gigabits data rate in both peak hours and cell edges, higher spectral efficiency, exceptional mobility, cost efficiency, continuous connectivity, and low latency [28]. In comparison to conventional communication systems, a 5G system is expected to deliver minimum data rates of 10 Gbps regardless of users locations. The network infrastructure is also expected to be much heaver than in LTE. Therefore, it is supposed to be acceptable price-wise. Nevertheless, it should be able to support cloud computing and storage services, provide a latency of less than 5 ms in which pre-crash sensing for vehicles for instance is possible [29]. Furthermore, for the system to be able to support high data rates, it should also be capable of supporting a minimum spectral efficiency of about 10 bps/Hz. Hence, it adopts the usage of MIMO systems, and advanced coding and modulation schemes. 5G systems are also expected to provide mobility on demand services for speeds up to 300–500 km/h. 3 CHANNEL MODELLING Mainly, two channel models are described in this section, namely: the NYUSIM and the 3GPP. The latter describes the model form 6 to 100 GHz while the former describes the model of 0.5–100 GHz known as the mmWave [16, 30, 31]. The most evident differences are described below: - The definition of clusters: 1. 3GPP: it is described by multiple angles and delay probability density function in which the group of beams must depart from distinct angle of departure (AoD). The characteristics of a cluster are often described by SAGE and KPowerMeans algorithms in [32, 33]. 2. NYUSIM: it is described by spatial lobe and time cluster concepts to illustrate the behaviour of the channel impulse response. While the time cluster defines the group of adjacent beams that are received from multiple directions in a short time frame, the spatial lobes define the directions of departure of these beams [34]. - Line of sight model: 1. 3GPP: described in Table 1. 2. NYUSIM: it is similar to 3GPP model but with squared equations whereby the values are obtained based on ray-tracing approach. - Large scale pathloss: The received signal P − in wireless communication systems is calculated simply by P + ( d B m ) + G ( d B ) + P L whereby P + is the transmitter power, G is the gain arguments, and P L is the large scale pathloss. Therefore, obtaining the pathloss gives a better realisation of the received power in 5G communication systems. Both 3GPP and NYUSIM adopt two different types of pathloss models, namely: close-in free space reference distance, and alpha–beta–gamma model whereby both models support different frequencies. However, NYSIM includes the same mathematical formulas of both but with fewer parameters and provide simpler analysis and increases accuracy. The two pathloss models are provided below [1]. 1. Close-in free space model: P L = 32.4 + 10 n l o g 10 ( d 3D ) + 20 l o g 10 ( f c ) + X σ (1)whereby d 3D is the 3D distance between the transmitter and receiver, f c is the carrier frequency in GHz, n is the pathloss exponent, X is the zero-mean Gaussian random variable with a standard deviation σ. 2. Alpha–beta–gamma model: P L = 10 α l o g 10 ( D 3D ) + β + 10 Γ l o g 10 ( f c ) + X α (2)whereby α and Γ are the pathloss dependency coefficients, and β is the pathloss optimised offset. It is noteworthy to mention that the described models are designed for omnidirectional transmissions. This is because joining multiple directional antenna gains does not contribute in calculating directional pathloss [16, 35, 36]. TABLE 1. Line of sight probability in 3GPP model [15] Scenario LOS probability RMa P LOS = 1 , d 2 D ≤ 10 m e x p − d 2 D − 10 1000 , 10 m < d 2 D UMI - Street canyon Outdoor users: P LOS = 1 , d 2 D ≤ 18 18 d 2 D + e x p − d 2 D 36 1 − 18 d 2 D , 18 < d Indoor users: use d 2D-out in the formula above instead of d 2D UMa Outdoor users: P LOS = 1 , d 2 D ≤ 18 m 18 d 2 D + e x p − d 2 D 63 1 − 18 d 2 D 1 + C ′ ( h U T ) 5 4 d 2 D 100 3 e x p − d 2 D 150 , 18 m < d 2 D Indoor users: user d 2 D − o u t in the formula above instead of d 2 D Indoor - mixed office P LOS = 1 , d 2 D ≤ 1.2 m e x p [ − d 2D − 1.2 4.7 , 1.2 m < d 2D < 6.5 m ] e x p [ − d 2D − 6.5 32.6 . 0.32 , 6.5 m ≤ d 2D ] Indoor - open office P LOS open-office = 1 , d 2D ≤ 5 m e x p [ − d 2D − 5 70.8 , 5 m < d 2D ≤ 49 m ] e x p [ − d 2D − 49 211.7 . 0.54 , 49 m < d 2D ] 4 INTERFERENCE IN 5G All signals in its basic form experience fading and undergo huge losses in the channel. To illustrate this, we look at Figure 4 in which the wave propagation is described. In Figure 4a, the base station has an omnidirectional antenna in which signals are propagating in all directions equally. In that sense, the user equipments are supposed to receive equal signal powers. However, it is not achievable due to the unequal distance at which the users are located. FIGURE 4Open in figure viewerPowerPoint Different RF propagation concepts On the other hand, user equipments receive much more improved signal powers when beams are not radiated equally in all directions which is done using different types of antennas. The terminology of forming the beams to a specific direction is familiarly known as beamforming (Figure 4b). The function used in beamforming determines the shape and the direction at which the beam is directed, that is number of antenna elements, their arrangement, the separation of elements, and the phase of each signal fed into each antenna element. In that regard, the work presented in [37] proposed a hybrid beamforming approach that is able to utilise the channel state information and come up with a beamsteering map codebook. The approach attempts to mitigate the interference between the sub bands caused by the carrier offsets of the orthogonal frequency division multiplexing (OFDM). Although the design seem to be complex, a digital beamformer with regulated channel inversion was used to lower the complexity. In [38], a 5G-IOT smart virtual antenna array is designed to eliminate the interference by precisely directing the generalised frequency division multiplexing (GFDM) beams towards the targeted angles. Although the interference is mitigated, the performance raises few concerns due to the availability of limited higher frequencies channel models. On the other hand, the authors of [39] analysed the end-fire arrangement arrays to combat interference in MIMO infrastructure in 12.9 GHz frequency band. OFDM techniques were also used to suppress the interference of in-band dull duplex channels. However, both reports did not discuss the performance in terms of bit error rates and throughput ratios. The smart antenna is another approach in which the antenna is able to construct a different beam for each user at the simultaneously. The antenna can hop to any beam at any given time [40]. With the aid of smart antennas, other techniques can be used to suppress the interference [41] such as zero-forcing (ZF) of [42, 43], or time division multiple access (TDMA) techniques in [44]. In [45], a combined beam antenna that operates in 28 GHz frequency band is proposed. The design relies on combining two different radiating elements to obtain a wider beam that has a high gain. On the azimuth plane, wider beams are obtained by microstrip patches while the higher gain is achieved using a wave-guide aperture in the elevation plane. Besides the reduced antenna size, the antenna can also constructively reduce interference by optimising the radiation of the two radiating parts. In [46], an uplink interference computation algorithm was designed for 70 and 80 GHz frequency bands to mitigate the interference by sectoring the cell zones and exclude certain zones from the transmission via switching off certain beams. Moreover, the spatial power control method helps in elevating the coverage area affects resulting from the beam on/off method. This also supports the fact that no coordination between the current and the 5G systems is needed. In [47], the interference in 2.6 GHz frequency band is mitigated using beamforming whereby an array antenna consisting of 4 antenna elements that gives a 40° beamwidth was used. The proposed scheme relies on estimating the locations of the users by obtaining the angles of the users in relation to their respective femtocells. Subsequently, the users are re-associated to the femtocell that gives the highest interference plus noise ratio (SINR). Although the spectral efficiency and throughput were considerably enhanced, the interference occurrence probability can inflate in dense deployment environments. The same authors in [48] improved the performance by utilising TDMA to time the transmissions instead of re-associating the users which improved the throughput even further and mitigated the outage probability to less than 5%. It is understood that the amount of interference produced by an antenna that has a specific beamwidth, can be related to the distance between the antenna and the mobile station. Hence, it can be said that altering the radiation pattern of an antenna can significantly reduce the interference to the surrounding environment [49]. More works that utilised beamforming can be found in [50]. Technically, the transmitted or received beams can be represented in two ways, namely, Cartesian and polar. Although both represent the same thing, different information can be extracted from the two representation. For instance, the beamwidth information can be obtained from the Cartesian representation, and the angle at which the beam is directed can be obtained from the polar representation. It can now be understood that beamforming techniques can be exploited to achieve the following: - Enhanced signal quality: narrower beamwidths have stronger directivity and longer coverage. - Less interference contribution: users do receive some amount of neighbouring base stations signals due to the omnidirectional propagation of signals. However, if the beamwidths are narrowed down, the beams are said to be directed towards the desired users only, that is less interference. - Improved network capacity: when beams are more directional, antenna gain is higher in which it increases the signal to SINR, and spectral efficiency. Thus, higher capacity. - Increased frequency reuse: it also gives room for reusing the frequency in other beams whereby one beam does not interfere with other beams. - Mitigation of multipath effects: the directivity of beams enhances the transmission which helps in mitigating the multipath effects. - Enhanced angle of arrival estimation: because of the directivity of the antenna, the angle of arrival is easier to be estimated because of reduced multipath effects. - Tracking of moving objects: in that sense, it can be called beamsteering which simply refers to constantly changing the beam direction to track objects. In general, bea