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1、Ericsson White PaperBNEW-23:004809UENUpdated February 2023Recent technology developments have made Massive MIMO the preferred option for large-scale deployments in 5G mobile networks.Massive MIMO enables state-of-the-art beamforming and MIMO techniques that are powerful tools for improving end-user

2、experience,capacity,and coverage.As a result,Massive MIMO significantly enhances network performance in both uplink and downlink.Finding the most suitable Massive MIMO variants to achieve the potential performance gains and cost efficiency in a specific network deployment requires an understanding o

3、f the characteristics of Massive MIMO solutions.Massive MIMO for 5G networksMassive MIMO for 5G networksContentFebruary 20232ContentIntroduction 3What is a Massive MIMO solution?4Deployment scenarios 10Evolution of Massive MIMO 13Conclusion 14Key terms 15References 16Further reading 17Authors 18Mass

4、ive MIMO for 5G networksIntroductionFebruary 20233IntroductionEnd-user requirements continue to increase 1,putting high demands on the radio access network(RAN)to deliver increased coverage,capacity,and end-user throughput.Since data usage is currently increasing at a much faster rate than correspon

5、ding revenue,communications service providers(CSPs)must evolve the RAN in a way that enables a reduced cost per bit while meeting new demands for end-user performance.Even as a relatively new technology,Massive MIMO solutions have already proven to be instrumental in todays 5G mid-band deployments t

6、o meet the network requirements.Most Massive MIMO solutions have already undergone several hardware and software generations,making them highly competitive in terms of size,weight,cost,performance,energy efficiency,and ease-of-deployment.Massive MIMO for 5G networksWhat is a Massive MIMO solution?Fe

7、bruary 20234What is a Massive MIMO solution?A Massive MIMO solution or simply Massive MIMO(formerly called advanced antenna system,or AAS)is a combination of a Massive MIMO radio and a set of Massive MIMO features.A Massive MIMO radio consists of an antenna array tightly integrated with the hardware

8、 and software required for the transmission and reception of radio signals,and signal processing algorithms to support the execution of the Massive MIMO features.Compared to conventional systems,this solution provides much greater adaptivity and steerability,in terms of adapting the antenna radiatio

9、n patterns to rapidly time-varying traffic and multi-path radio propagation conditions.In addition,multiple signals may be simultaneously received or transmitted with different radiation patterns.Multi-antenna techniques Multi-antenna techniques(here referred to as Massive MIMO features)include all

10、variants of beamforming,null-forming,and MIMO.Applying Massive MIMO features to a Massive MIMO radio results in significant performance gains because of the higher degrees of freedom provided by a large number of radio chains.BeamformingDuring transmission,beamforming is the ability to direct radio

11、power through the radio channel toward a specific receiver,as shown in the top left quadrant of Figure 1.By adjusting the phase and amplitude of the transmitted signals,constructive addition of the corresponding signals at the user equipment receiver can be achieved which increases the received sign

12、al strength and,thus,the end-user throughput.Similarly during reception,beamforming is the ability to collect the signal power from a specific transmitter.The beams formed are constantly adapted to the surroundings to give high performance in both uplink(UL)and downlink(DL).Massive MIMO for 5G netwo

13、rksWhat is a Massive MIMO solution?February 20235Although often very effective,transmitting power in only one direction does not always provide an optimum solution.In multi-path scenarios,where the radio channel comprises multiple propagation paths from the transmitter to receiver through diffractio

14、n around corners and reflections against buildings or other objects,it is beneficial to send the same data stream in several different paths(direction and/or polarization)with phases and amplitudes controlled in a way that they add constructively at the receiver 2.This is referred to as generalized

15、beamforming,as shown in the upper right quadrant of Figure 1.As part of generalized beamforming,it is also possible to reduce interference to other UEs,which is known as null-forming.This is achieved by controlling the transmitted signals in a way that they cancel each other out at UEs that would ot

16、herwise be interfered.Note that the concept of generalized beamforming can be considerably more complex than illustrated in Figure 1,see for example 2,Ch.6.MIMO(Multiple Input,Multiple Output)techniques Spatial multiplexing,here referred to as MIMO,is the ability to transmit multiple data streams,us

17、ing the same time and frequency resource,where each data stream can be beamformed differently.The purpose of MIMO is to increase throughput.MIMO builds on the basic principle that when the received signal quality is high,it is better to receive multiple streams of data with reduced power per stream,

18、than one stream with full power.Figure 1:Beamforming and MIMO with the different colors of the filled beams that represent different data streamsB.Generalized beamformingC.Single-user MIMOD.Multi-user MIMOServe single user through sending the same data stream in different directions and possibly for

19、ming zeros(nulls)in directions of other users.Increase data rates by transmitting several data streams to a user.At high load,serve more users simultaneously.XServe single users by directing the energy toward the user.A.BeamformingXMassive MIMO for 5G networksWhat is a Massive MIMO solution?February

20、 20236The potential is large when the received signal quality is high,and the beams carrying the data streams are designed not to interfere with each other.The potential diminishes when the mutual interference between streams increases.MIMO works in both UL and DL,but for simplicity,the description

21、below will be based on the DL.The details of how these work are explained in detail in 2,Ch.4,6,13.Single-user MIMO(SU-MIMO)is the ability to transmit one or multiple data streams,also called layers,from one transmitting array to a single user.SU-MIMO can thereby increase the throughput for that use

22、r and increase the capacity of the network.The number of layers that can be supported,called the rank,depends on the radio channel and the minimum number of antennas on each side.To distinguish between DL layers,a UE must have at least as many receiver antennas as there are layers.SU-MIMO can be ach

23、ieved by sending different layers on different polarizations in the same direction.SU-MIMO can also be achieved in a multi-path environment,where there are many radio propagation paths of similar strength between the Massive MIMO radio and the UE,by sending different layers on different propagation

24、paths,as shown in the bottom left quadrant of Figure 1.In multi-user MIMO(MU-MIMO),which is shown in the bottom right quadrant of Figure 1,different layers in separate beams are transmitted to different users using the same time and frequency resource,thereby increasing the network capacity.To use M

25、U-MIMO,the system needs to find two or more users that need to transmit or receive data at the very same time.Also,for efficient MU-MIMO,the interference between the users should be kept low.This can be achieved by using generalized beamforming with null forming such that when a layer is sent to one

26、 user,nulls are formed in the directions of the other simultaneous users.The achievable capacity gains from MU-MIMO depend on receiving each layer with good signal-to-interference-and-noise-ratio(SINR).As with SU-MIMO,the total DL power is shared between the different layers,and therefore the power(

27、and thus SINR)for each user is reduced as the number of simultaneous MU-MIMO users increases.Also,as the number of users grows,the SINR will further deteriorate due to mutual interference between the users.Therefore,the network capacity typically improves as the number of MIMO layers increases to a

28、point at which power sharing and interference between users result in diminishing gains and eventually also losses.It should be noted that the practical benefits of many layers in MU-MIMO are limited by the fact that,in todays real networks,even with a high number of simultaneously connected users,t

29、here tend not to be many users who want to receive data simultaneously.This is due to the bursty(chatty)nature of data transmission to most users.Since the Massive MIMO and the transport network must be dimensioned for the maximum number of layers,the CSP needs to consider how many layers are requir

30、ed in their networks.In typical mobile broadband(MBB)deployments with the current 64T64R Massive MIMO variants,the vast majority of the DL and UL capacity gains can be achieved with up to 8 layers.For other services than MBB,e.g.fixed wireless access(FWA),there is use for more layers compared to MBB

31、.Eight layers are however usually sufficient also for FWA.Massive MIMO for 5G networksWhat is a Massive MIMO solution?February 20237Acquiring channel knowledge for Massive MIMOKnowledge of the radio channels between the antennas of the user and those of the base station is a key enabler for beamform

32、ing and MIMO,both for UL reception and DL transmission.This allows the Massive MIMO to adapt the number of layers and determine how to beamform them.For UL reception of data signals,channel estimates can be determined from known signals received on the UL transmissions.Channel estimates can be used

33、to determine how to combine the signals received to improve the desired signal power and mitigate interfering signals,either from other cells or within the same cell.DL transmission,on the other hand,is typically more challenging than UL reception because channel knowledge needs to be available befo

34、re transmission.Whereas basic beamforming has relatively low requirements on the necessary channel knowledge,generalized beamforming has higher requirements as more details about the multi-path propagation are needed.Furthermore,mitigating interference by using null-forming for MU-MIMO is even more

35、challenging,since more details of the channels typically need to be characterized with high granularity and accuracy.There are two basic ways of acquiring DL channel knowledge:UE feedback and UL channel estimation.To acquire DL channel knowledge based on UE feedback,the base station transmits known

36、signals in the DL that UEs can use for channel estimation.Relevant channel information is then extracted from the channel estimates and fed back to the base station.What type of DL channel knowledge can be acquired based on UL channel estimation,also referred to as UL sounding,depend on whether time

37、 division duplex(TDD)or frequency division duplex(FDD)is used.For TDD,the same frequency is used for both UL and DL transmission.Since the radio channel is reciprocal(the same in UL and DL),detailed short-term channel estimates from UL transmission of known signals can be used to determine the DL tr

38、ansmission beams.This is referred to as reciprocity-based beamforming.For full channel estimation,signals should be sent from each UE antenna and across all frequencies.For FDD,where different frequencies are used for UL and DL,the channel is not fully reciprocal.Longer-term channel knowledge(such a

39、s dominant directions)can,however,be obtained by suitable averaging of UL channel estimate statistics.The suitable channel knowledge scheme to use depends on UL coverage and UE capabilities.In cases where UL coverage is limiting,UE feedback offers a more robust operation,whereas full UL channel esti

40、mation is applicable in scenarios with good coverage.In short,both reciprocity and UE feedback-based beamforming are needed.Antenna array structureThe purpose of using a rectangular antenna array,as shown in section A of Figure 2,is to enable high-gain beams and make it possible to steer those beams

41、 over a range of angles in horizontal and vertical directions.The gain is achieved,in both UL and DL,by constructively combining signals from several antenna elements.Typically,the more antenna elements there are,the higher the gain.Steerability is achieved by individually controlling the amplitude

42、and phase of smaller parts of the antenna array.This is usually done by dividing Massive MIMO for 5G networksWhat is a Massive MIMO solution?February 20238the antenna array into so called sub-arrays(groups of non-overlapping elements pairs),as shown in section C of Figure 2 and by applying two dedic

43、ated radio chains per sub-array(one per polarization)to enable control,as shown in section D.In this way,it is possible to control the direction and other properties of the created beam.To see how an antenna array creates steerable high-gain beams,we start with an antenna array of a specific size,wh

44、ich is then divided into sub-arrays of different sizes.For illustrative purposes,we describe only one dimension.The same principles do,however,apply to both vertical and horizontal dimensions.The array gain is referred to as the gain achieved when all sub array signals are added constructively(in ph

45、ase).The size of the array gain,relative to the gain of one sub-array,depends on the number of sub-arrays for example,two sub-arrays give an array gain of 2(i.e.3 dB).By changing the phases of the sub-array signals in a certain way,this gain can be achieved in any direction,as shown in section A of

46、Figure 3.Each sub-array has a certain radiation pattern describing the gain in different directions.The gain and beam width depend on the size of the sub-array and the properties of the individual antenna elements.There is a trade-off between sub-array gain and beam width the larger the sub-array,th

47、e higher the gain and the narrower the beam width,as illustrated in section B of Figure 3.The total antenna gain is the product of the array gain and the sub-array gain,as shown in section C of Figure 3.The total number of elements determines the maximum gain and the sub-array partitioning allows th

48、e steering of high-gain beams over the range of angles.Moreover,the sub-array radiation pattern determines the envelope of the narrow beams(the dashed shape in section C of Figure 3).This has an implication on how to choose an antenna array structure in a real deployment scenario with specific cover

49、age requirements.Since each sub-array is normally connected to two radio chains and each radio chain is associated with a cost in terms of additional components,it is important to consider Figure 2:A typical antenna array(A)is made up of rows and columns of individual dual-polarized antenna element

50、pairs(B).Antenna arrays can be divided into sub-arrays(C),with each sub-array(D)connected to two radio chains,normally one per polarization.A.B.C.D.Massive MIMO for 5G networksWhat is a Massive MIMO solution?February 20239the performance benefits of additional steerability when choosing a cost-effic

51、ient array structure.Figure 3:An array of sub-arrays supporting high total antenna gain and steerability6 dB42423 dB6 dBArray gainTotal antenna gainSub-array gainx=A.C.B.6 dB3 dB0 dBMassive MIMO for 5G networksDeployment scenariosFebruary 202310Deployment scenariosDetermining what kind of Massive MI

52、MO configuration is most appropriate and cost-effective for a particular deployment scenario requires a mix of knowledge about the scenario,possible site constraints,and available Massive MIMO features,particularly the need for vertical steerability of beams,the applicability of reciprocity-based be

53、amforming and the gain from MU-MIMO.It should be noted that horizontal beamforming is a very effective feature that provides large gains in all scenarios since the users are generally spread in the horizontal dimension.Therefore,a large number of columns is beneficial in all scenarios.We have chosen

54、 three typical use cases to illustrate different aspects of Massive MIMO deployment:rural/suburban,urban low-rise,and dense urban high-rise.More comprehensive and practically useful recommendations can be found in 3.The scenarios,including relevant characteristics,suitable Massive MIMO configuration

55、s,and performance potential are depicted in Figure 4.More elaborate evaluations of the performance achievable with Massive MIMO are available in reference 2 and 3.Massive MIMO for 5G networksDeployment scenariosFebruary 202311Table 1:Comparison of the simplest regular 5G device with the simplest and

56、 the most advanced RedCap deviceDense urban high-riseA.Relative capacityISD-200-500mMU-MIMOSU-MIMO2x1 sub-array-64T64R2T16T32T64TUrban low-riseB.Relative capacityISD-500-1000mMU-MIMOSU-MIMO4x1 sub-array-32T32R2T16T32T64TSurburban and ruralC.Relative capacityISD 1000mMU-MIMOSU-MIMO8x1 sub-array-16T16

57、R2T16T32T64TFigure 4:Suitable Massive MIMO configurations,schematic MU-MIMO and SU-MIMO usage ranges,and typical capacity gains in different deployment scenariosDeployment scenario#1:Dense urban high-riseAs depicted in section A of Figure 4,the dense urban high-rise scenario is characterized by high

58、-rise buildings,short inter-site-distances(ISDs)of 200-500m,large traffic volume,and high subscriber density with significant user spread in the vertical dimension.The main network evolution driver has increased capacity or equivalently high end-user throughput for a given traffic load.For conventio

59、nal non-beamformed systems such as 2T2R,the vertical spread of users in combination with the small ISD creates a situation where many users are outside the vertical main beam of the nearest base station.Together with the high site density,this leads to a situation where the signals from interfering

60、base stations are strong,and severe interference problems may occur.Desired Massive MIMO characteristics in the dense urban high-rise scenario include an antenna area large enough to ensure sufficient coverage(UL cell-edge data rate).Further,the vertical coverage range needs to be large enough to co

61、ver the vertical spread of users.This calls for small sub-arrays,which have a wide beam in the vertical direction.Partitioning the antenna into small vertical sub-arrays results in high-gain beams that can be steered over a large range of angles and effectively addresses the interference problems se

62、en with conventional systems.The Massive MIMO radio needs to have a sufficient number of radio chains to support the relatively large number of sub-arrays.The good coverage and large spread of users mean that the potential for reciprocity-based beamforming and MU-MIMO with a relatively large number

63、of multiplexed users is high,and the Massive MIMO radio Massive MIMO for 5G networksDeployment scenariosFebruary 202312should support these techniques.A good trade-off between complexity and performance could be achieved with 64 radio chains controlling small sub-arrays.Deployment scenario#2:Urban l

64、ow-rise The urban low-rise scenario illustrated in section B of Figure 4 represents many of the larger cities around the world,including the outskirts of many high-rise cities.Base stations are typically deployed on rooftops,with inter-site distances of a few hundred meters.Compared to the dense urb

65、an high-rise scenario,traffic per area unit is lower.There is generally a mix of building types,which creates multipath propagation between the Massive MIMO radio and the UE.Maximizing the antenna area is important for improving the UL cell-edge data rates,especially for higher frequency bands emplo

66、ying TDD.Due to larger ISDs and decreased vertical spread of users(lower buildings),the vertical coverage range can be decreased compared to dense urban high-rises;hence,larger vertical sub-arrays can be used and there is less gain from vertical beamforming.Using larger sub-arrays for a given antenn

67、a area means that fewer radio chains are required.Reciprocity-based beamforming schemes will work for most users,but there will be users with poor coverage that need to rely on techniques such as feedback-based beamforming.MU-MIMO is also appropriate at high loads due to the multi-path propagation e

68、nvironment,good link qualities,and UE pairing opportunities.A good trade-off between complexity and performance is a Massive MIMO radio with 16 to 32 radio chains.Deployment scenario#3:Rural/suburbanRural or suburban macro scenarios,as depicted in section C of Figure 4,are characterized by rooftop o

69、r tower-mounted base stations with inter-site distances ranging from one to several kilometers,low or medium population density and very small vertical user distribution.This scenario calls for a Massive MIMO radio with a large antenna area and the ability to support horizontal beamforming.Vertical

70、beamforming,however,does not provide any significant gains as the vertical user spread is low.Therefore,large vertical sub-arrays with small vertical coverage areas are possible.Reciprocity-based beamforming is supported for a smaller fraction of users than in the other scenarios,and MU-MIMO gains a

71、re more limited.A good trade-off between complexity and performance is a Massive MIMO radio with 8 to 16 radio chains.Massive MIMO for 5G networksEvolution of Massive MIMO February 202313Evolution of Massive MIMO The brief explanation of Massive MIMO above reflects the solutions in use to date(2022-

72、Q4).The evolution of Massive MIMO is very rapid,and several tracks are being investigated to achieve higher performance.A few examples include the use of higher numbers of radio chains,larger array panels,the use of new and higher frequencies,and the use of multiple transmission points(multi-TRP).In

73、 addition to advancements in technologies specific to Massive MIMO,the use of interworking between Massive MIMO and conventional radios on other frequency bands add additional capacity beyond the sum of the two,respectively.Other developing technologies,e.g.artificial intelligence and machine learni

74、ng(AI/ML)will also be applied in Massive MIMO to improve performance.Yet other technology developments,relating to for example energy performance,cost efficiency,and site deployment,are coming into use to make Massive MIMO a highly competitive and commercially viable option for mass deployment in a

75、large variety of scenarios.Massive MIMO is also used to support a growing number of services in addition to MBB.Today Massive MIMO is already used for FWA,IoT and new industries and in the near future also XR services.With the development of private networks,the number of services supported is expec

76、ted to grow very fast.Massive MIMO for 5G networksConclusionFebruary 202314ConclusionRecent technology developments have made Massive MIMO(advanced antenna systems)a preferred option for large-scale deployments in 4G and 5G mobile networks.Massive MIMO enables state-of-the-art beamforming and MIMO t

77、echniques that are powerful tools for improving end-user experience,capacity,and coverage.As a result,Massive MIMO significantly enhances network performance in both uplink and downlink.The Massive-MIMO solution toolbox is versatile and selecting a suitable Massive MIMO(2x)solution depends on aspect

78、s such as deployment environment,traffic load variations and ease-of-deployment.Massive MIMO products provide significant benefits across a very wide range of deployment scenarios,making it possible for mobile network operators to enjoy the benefits of cost-efficient Massive MIMO across their networ

79、ks.Massive MIMO solutions have already proven invaluable in many 5G deployments,and their importance will likely to increase even further in future network deployments.Massive MIMO for 5G networksKey termsFebruary 202315Key termsMassive MIMO radio Hardware unit that comprises an antenna array,radio

80、chainsand parts of the baseband,all tightly integrated to facilitate Massive MIMO featuresMassive MIMO feature A multi-antenna feature(such as beamforming or MIMO)that can be executed in the Massive MIMO radio,in the baseband unit or bothMassive MIMO Massive MIMO radio+Massive MIMO featuresMassive M

81、IMO for 5G networksReferencesFebruary 202316References1.Ericsson Mobility Report,June 2022 available at https:/ 2.Asplund,et al,“Advanced Antenna Systems for 5G Network Deployments:Bridging the Gap Between Theory and Practice”,1st Edition,Elsevier 2020,ISBN:978-0-12-820046-9,Advanced Antenna Systems

82、 for 5G Network Deployments-1st Edition()3.Asplund et al,“The Massive MIMO handbook”,Ericsson 2022 https:/ MIMO for 5G networksFurther readingFebruary 202317Further reading1.Ericsson Technology Review,Designing for the future:the 5G NR physical layer,available at:https:/ Technology Review,Evolving L

83、TE to fit the 5G future,available at:https:/ Technology Review,5G radio access,available at:https:/ Antenna Systems for 5G Network Deployments:Bridging the Gap Between Theory and Practice 1st Edition,Elsevier 2020,ISBN:978-0-12-820046-9,Advanced Antenna Systems for 5G Network Deployments-1st Edition

84、()5.Asplund et al,“The Massive MIMO handbook”,Ericsson 2022,https:/ 6.Astely,D.,von Butovitsch,P.,Faxr,S.,Larsson,E.,“Meeting 5G network requirements with Massive MIMO”,2022,February 16,https:/ Antenna Systems for 5G”,5G Americas White Paper,2019,Aug,5G-Americas_Advanced-Antenna-Systems-for-5G-White

85、-Paper.pdf(5gamericas.org)8.Ericsson,Blogg,Massive MIMO solutions accelerate 5G mid-band Ericsson.9.5G NR:The Next Generation Wireless Access Technology,1st Edition,August 2018,Dahlman,E;Parkvall,S;Skld,J,available at:https:/ accesstechnology/dahlman/978-0-12-814323-0 10.NR-The New 5G Radio-Access T

86、echnology,Stefan Parkvall,Erik Dahlman,Anders Furuskr,Mattias Frenne,2018 IEEE 87th Vehicular Technology Conference:VTC2018-Spring,36 June 2018,Porto,Portugal 11.Fredric Kronestedt,Henrik Asplund,Anders Furuskr,Du Ho Kang,Magnus Lundevall,Kenneth Wallstedt,The advantages of combining NR with LTE at

87、existing sites,Ericsson Technology Review,available at:https:/ MIMO for 5G networksAuthorsFebruary 202318AuthorsPeter von Butovitsch joined Ericsson in 1994 and currently serves as Technology Manager at Systems&Technology.He has held various positions at Ericsson Research and in RAN system design ov

88、er the years,and from 1999 to 2014 he worked for Ericsson in Japan and China.He holds both an M.Sc.in engineering physics and a Ph.D.in signal processing from KTH Royal Institute of Technology in Stockholm,Sweden.In 2016,he earned an MBA from Leicester University in the UK.David Astely is currently

89、a Principal Researcher with Ericsson Research in the radio area.He received his Ph.D.in signal processing from KTH Royal Institute of Technology in 1999 and has been with Ericsson since 2001,where he has held various positions in both research and product development.Massive MIMO for 5G networksAuth

90、orsFebruary 202319Anders Furuskr joined Ericsson Research in 1997 and is currentlya senior expert focusing on radio resource management and performanceevaluation of wireless networks.He has an M.Sc.in electrical engineeringand a Ph.D.in radio communications systems,both from KTH Royal Instituteof Te

91、chnology in Stockholm.Bo Gransson is the Senior Expert in Multi Antenna Systems&Architectures.He joined Ericsson Research in 1998,where he worked with research and standardization of 3G and 4G physical layer with a special interest in MIMO and beamforming technologies.He later moved to the Systems&T

92、echnology organization to work closer to the implementation of multi antenna technologies.He holds an M.Sc.in electrical engineering and engineering physics from Linkping University(Sweden)and a Ph.D.in signal processing from KTH Royal Institute of Technology in Stockholm.Massive MIMO for 5G network

93、sAuthorsFebruary 202320Billy Hogan joined Ericsson in 1995,and has worked in many areas of core and RAN design and systemization,including as the Senior Specialist for Enhanced Uplink in WCDMA.Today he is a Principal Engineer working in Product Development Unit 4G5G,where he drives the overall strat

94、egy and solutions for AAS in 4G and 5G.He holds a B.E.in electronic engineering from the National University of Ireland,Galway,and an M.Eng.in electronic engineering from Dublin City University,Ireland.Jonas Karlsson joined Ericsson in 1993.Since then he has held various positions in Ericsson Resear

95、ch and in product development.He is currently an Expert in Multi Antenna Systems at Product Development Unit 4G5G.He holds an M.Sc.in electrical engineering and engineering physics from Linkping University(Sweden)and a Ph.D.in in electrical engineering from the University of Tokyo,Japan.Massive MIMO

96、 for 5G networksAuthorsFebruary 202321Erik Larsson joined Ericsson in 2005.He is currently a researcher at Systems and Technology working with concept development and network performance for NR with a focus on advanced antenna systems.He holds both an M.Sc.in engineering physics and a Ph.D.in electrical engineering,specializing in signal processing,from Uppsala University,Sweden.