TD-LTE AND MIMO BEAMFORMING - Spirent/media/white papers/mobile/td-lte_and_mimo... · The...

Rev. A 08/12

TD-LTE anD MIMO BEaMfOrMIng Principles and Test ChallengesAugust 2012

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Spirent white paper • i

TD-LTE and MIMO Beamforming Principles and Test Challenges

Contents

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

MIMo Beamforming - exploiting the spatial Domain . . . . . . . . . . . . . . . . . . . .3

How the spatial Domain Facilitates MIMo Beamforming . . . . . . . . . . . . . 4

A Brief Review of Beamforming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

MIMo and Beamforming in a single system . . . . . . . . . . . . . . . . . . . . . . . 7

tD-Lte – exploiting the time Domain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10

testing MIMo Beamforming Receivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12

the Challenges of RF testing in tD-Lte MIMo Beamforming . . . . . . . . . 12

Phase Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Antenna techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Channel Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15

Acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .16

1 • sPIRent wHIte PAPeR

TD-LTE and MIMO BeamformingPrinciples and Test Challenges

IntRoDuCtIon

Why TD-LTE?

time-Division Long term evolution (tD-Lte) is

one of two variants of 3GPP Lte technology .

Development of the tD-Lte standard has been

spearheaded by China as an evolution path

for its tD-sCDMA 3G technology . However,

the popularity of tD-Lte is growing rapidly

in other markets, thanks to its high level of

commonality with FDD Lte (the other Lte

variant), with the resulting economies of

scale, as well as the compelling economics

of the unpaired spectrum needed by tD-Lte .

Instead of duplexing uplink and downlink

stream in the frequency domain, tD-Lte (as well as tD-sCDMA) duplexes the uplink and

downlink in the time domain .

wiMAX technology has also been deployed in single-band spectrum rather than in

unpaired bands . the global momentum of Lte technology makes it highly likely that it

will also form the 4G evolution path for many wiMAX operators, with the tD-Lte variant

being ideally suited to deployment in unpaired wiMAX spectrum .

Why MIMO Beamforming?

MIMo beamforming is a combination of two related but different antenna techniques:

MIMo, which enables increased data rates in a given spectral bandwidth and

beamforming, which helps operators increase system coverage . A variation of MIMo

called Mu-MIMo can share the higher available data rates among multiple subscribers,

further increasing network efficiency .

The Relationship Between TD-LTE and MIMO Beamforming

technically, MIMo beamforming is not exclusive to tD-Lte systems, but there are

distinct advantages to deploying beamforming alongside a time-Domain-Duplexed

(tDD) technology . these advantages will be discussed in detail in this paper .

cORREspOnDIng LITERaTuRE

PosteR

tD-Lte and Beamforming

weBInAR

understanding Beamforming in tD-Lte Deployments

http://www.spirent.com/OnDemand/Networks_and_Applications/TD-LTE_and_MIMO_Beamforming

sPIRent wHIte PAPeR • 2


the business drivers for tying MIMo beamforming to tD-Lte are a function of tD-Lte’s

initial markets . Both China and India are planning to deploy tD-Lte on a staggering

scale; to give one reference point, a Chinese tD-Lte trial includes planned deployment

of over 200,000 tD-Lte base stations by the end of 2013 . these countries must

optimize coverage due to pockets of incredibly high subscriber density . while much

of the initial focus for tD-Lte is on Asia, the technology will be adopted worldwide by

operators with unpaired spectrum (wiMAX and tD-sCDMA) who are looking to get in on

the growing Lte ecosystem .

this white paper provides:

• A brief review of MIMo and beamforming antenna techniques

• A description of the tD-Lte technology being deployed

• An overview of the advantages of deploying MIMo beamforming in tD-Lte and the corresponding testing challenges to ensure success in these markets



MIMo BeAMFoRMInG - eXPLoItInG tHe sPAtIAL DoMAIn

traditional radio technologies have used the frequency and/or time domains in which to

differentiate between streams of data . these differentiated data streams could be used

for:

• Multiplexing – differentiating between users

• Duplexing – differentiating between uplink and downlink communications

• Flexibility in data rates – modifying data rates by re-allocating resources in the time or frequency domains

other domains (e .g . the code domain used in CDMA multiplexing) have been

implemented but all were limited by the availability of finite time and frequency

resources .

MIMo technology exploits space as a domain in which to increase data rates or share

time/frequency resources between users .

Figure 1: Legacy wireless technologies separated data streams in the time domain (e.g. TDMA), the frequency domain (AMPS), or both (GSM).



How the spatial Domain Facilitates MIMo Beamforming

a Brief Review of MIMO

Imagine a 2x2 MIMo system deployed in a “rich scattering” environment… one in which

there are a large number of reflections causing fading on radio signals . If two separate

data streams are transmitted from separate antennas, each will encounter different

fading effects en route to a pair of receiving antennas .

If the receiver is able to use those differences in fading to distinguish between streams

and disaggregate them from each other, the system should be able to transmit and

demodulate two independent data streams in the same frequency band and at the

same time . the process is analogous to solving two equations for two unknown

variables . . . neither of the receiver’s antenna elements has enough information on its

own to demodulate multiple streams, but the combination of information from multiple

antenna elements does include sufficient information .

since signal fading is a function of distance and location (i .e . a function of spatial

parameters) space can be treated as a domain in which data streams can be

disaggregated… even when neither stream is giving up resources in the time and

frequency domain .

Figure 2: MIMO enables the use of space as an “extra” domain in which data streams can be differentiated



Intuitively the resulting MIMo system can be thought of as a pair of data “pipes” known

as eigen channels (since the channels are based on the eigenvalues of the MIMo

channel’s characteristic transfer matrix) . the eigen channel capacity, or “sizes” of the

pipes are proportional to the eigenvalues, and will therefore almost never be identical .

In practice the two “pipes” can be allocated to a single user (increasing data rates) or,

in the case of Multi-user MIMo (Mu-MIMo), divided between two separate users to

increase capacity .

one other concept that must be understood intuitively is the idea of correlation .

Doubling the capacity of a 2x2 MIMo channel requires that the four radio links (shown

in Figure 3 as h11

, h12

, h21

and h22

) exhibit a high degree of difference from each other

based on experiencing different fading . this is called a low correlation between links . In

a more rigorous discussion, correlation would be quantified as a scalar value between 0

and 1 (sometimes expressed as a percentage) . Figure 4 depicts the concept of high and

low correlation (based on fading) of two radio links .

Figure 3: 2x2 MIMO channel (conceptual)



since a MIMo system depends on fading differences experienced by separate data

streams, it can best increase capacity when the channel (all four radio links) exhibits a

low degree of correlation .

A Brief Review of Beamforming

Beamforming, on the other hand, relies on a high degree of correlation . In beamforming,

multiple antennas transmit radio signals that are identical except for one thing: a beam

is created and steered by adjusting the phase angles of the transmissions so that they

are in phase (delivering high signal-to-noise Ratios, or snRs) where good reception

is desired . In this case the eigen channels are such that the system delivers one large

data pipe alongside one or more very small data pipes . the latter go unused by the

system as shown in Figure 5 .

Figure 4: High (top) and low (bottom) degrees of correlation



Critical points:

• Beamforming is not necessarily characteristic of a MIMo system or a time-domain-based system . It can be and has been used in frequency-division based systems .

• In order for the system to successfully create a beam, it has to have “knowledge” of the downlink RF channel . In a frequency-division based system this requires a complicated measurement-and-feedback process, making it a less attractive option .

MIMo and Beamforming in a single system

It was noted earlier that a MIMo system can most effectively increase data rates and

capacity when there is a low degree of correlation in the MIMo channel . In the earliest

MIMo systems, low correlation was created by physically separating antenna elements .

one MIMo “rule of thumb” is that a system can deliver low-correlation channels

when antenna elements on both the transmitter and receiver sides of the system are

separated by a distance of more than half the signal wavelength . this is not an option

in cellular systems; at 700 MHz, for example, half a wavelength is greater than 20 cm…

much too large to be implemented in a mobile phone form factor .

Another way of ensuring low correlation in a MIMo system is to cross-polarize antenna

elements on both the transmitter and receiver sides of the system… in other words, to

physically orient antenna elements at right angles to each other .

this not only enables MIMo in the cellular world, it enables the addition of beamforming

to MIMo systems .

Figure 5: Beamforming



Transmission Modes

Just as a non-beamforming MIMo system can deliver multiple modes (i .e . increasing

data rates to a single user or splitting data “pipes” so they are used by different users)

so can a MIMo beamforming system .

Figure 7: MU-MIMO and SU-MIMO

In Figure 6, four antenna elements at the transmitter (shown in orange in the left side of

the figure) are designed and placed to create high correlation between their transmitted

signals . By adjusting the phase characteristics of each of their signals, a beam is

formed, creating areas of high snRs .

A second set of four antenna elements (shown in blue) are cross-polarized in relation to

the first four . they also create a beam, but the two beams exhibit low correlation with

each other . the result is a MIMo beamforming system that can deliver multiple data

streams to a specific physical location .

Figure 6: Antenna element orientation in a MIMO beamforming system



the left side of Figure 7 depicts a MIMo beamforming system being used to serve

multiple user signals at the same time, from the same cell and in the same frequency

space . on the right side a single user MIMo (su-MIMo) system delivers multiple data

streams or “layers” to a single user . note that in cases where beamforming is used by

the receiver rather than the transmitter, the “nulls” between lobes can be steered to

reject interfering signals from known sources .

the 3GPP has defined several downlink physical channel “transmission modes” to

support different types of beamforming . table 1 lists the 3GPP transmission modes (7,

8 and 9) that support beamforming along with relevant Downlink Control Information

(DCI) and port assignments .

Table 1: 3GPP beamforming transmission modes

Transmission Mode

DCI Format Antenna Ports

7 1A port 0 or tX diversity

7 1 port 5 (virtual port)

8 1A port 0 or tX diversity

8 2B ports 7 and 8 (2-layer su-MIMo); port 7 or 8 (1-layer Mu-MIMo)

9 1A port 7

9 2C port 7 or 8



tD-Lte – eXPLoItInG tHe tIMe DoMAIn

Just as MIMo beamforming can exploit the spatial domain to create multiple data

streams, tD-Lte itself exploits the time domain to perform duplexing .

the introduction to this paper noted that one original driver for tD-Lte was the lower

cost and global availability of single-band (unpaired) spectra as opposed to the dual-

band spectra required by Frequency-Division Duplexed (FDD) systems . However, time-

division duplexing is not just a matter of necessity; it offers several advantages over

FDD systems, especially when paired with MIMo beamforming .

By sharing a single frequency band for uplink and downlink, and by adjusting the

number of time slots available in each direction, tDD-based systems offer a degree of

flexibility in uplink/downlink resource allocation . For example, tD-Lte profiles include

seven different frame structures (shown in Figure 8) . theoretically, tDD systems can

dynamically re-allocate uplink/downlink resources on the fly, though initial tD-Lte

deployments are unlikely to include this feature (due to technical considerations beyond

the scope of this paper) .

Figure 8: Seven frame structures available in TD-LTE systems.



As a result, channel estimation of the uplink can be used to make reasonable

assumptions regarding downlink channel characteristics . Channel reciprocity in a

single uplink/downlink frequency lends itself to a way of improving both coverage and

system quality: MIMo beamforming .

early tD-Lte deployments plan to combine MIMo and beamforming, offering the

advantages of higher data rates as well as capacity and quality improvement . A typical

MIMo beamforming configuration can be thought of as a 2x2 MIMo system, except

that each of the two transmitted “layers” is actually a steered beam formed by four

transmitting antenna elements . this has led to growth in the study of 8 × n systems,

where each base station is equipped with eight antenna elements, as a cost-efficient,

spectrally-efficient alternative to the addition of cell sites or additional carriers . All of

this creates an incredibly complex RF environment with significant development and

test implications that must be addressed to ensure success in the rapidly emerging

tD-Lte markets .

Figure 9: The reciprocal channel in TDD systems

Another advantage that eases the implementation of MIMo beamforming in a tDD

system, is the concept of channel reciprocity . It was noted earlier that FDD systems

can implement beamforming as long as there is a feedback loop from the terminal that

informs the transmitter about the state of the downlink channel .

tDD systems do not require that feedback loop; the RF channel state is a function of

frequency, space and time . In tDD the uplink and downlink channels share the same

frequency, occupy the same physical space and are separated by relatively insignificant

slices of time . the tD-Lte uplink and downlink are “characteristically identical” . Figure

9 displays a close-up view (in terms of time) of a faded tDD radio channel . while the

overall range of the faded signal can be fairly substantial, the differences in channel

state from one time slot to the next are not .

Time

Channel State

t

Channel State



testInG MIMo BeAMFoRMInG ReCeIveRs

the Challenges of RF testing in tD-Lte MIMo Beamforming

Given this fundamental understanding of the processes required in a tD-Lte MIMo

beamforming system, some of the potential pitfalls in testing become obvious:

1 . the number of radio links involved

2 . the creation of a realistically-reciprocal channel

3 . Phase accuracy

4 . Accurate replication of advanced antenna techniques

The number of Radio Links

the tD-Lte MIMo beamforming systems that are being developed and tested in Asia

and elsewhere today are 8x2 systems . A plan exists to ramp up to 8x4 systems in the

relatively near future . Release 10 includes provisions for 8x8 beamforming .

An 8x2 system creates 16 separate radio links in each direction; an 8x4 system doubles

that; a bi-directional 8x8 system of the future will require 128 . each link must not

only be faithfully created on the test bench, the links must be managed so that test

operators can set specific values of correlation .

The Reciprocal channel

Figure 10 depicts a live tDD channel, which is naturally reciprocal for reasons already

discussed . However, test equipment must deliver a level of control beyond that

of the live environment, which means that uplink and downlink channels must be

implemented separately . this implies that test equipment cannot deliver an accurate

reproduction of the live environment unless it can deliver nearly identical channel states

in both directions, at all times and on all the radio links being emulated .

Figure 10: The reciprocal TDD channel

DL UL



Phase Accuracy

the beamforming aspect of MIMo beamforming is entirely dependent on phase

characteristics of the transmitted radio links . therefore, accurate testing must include

a high degree of phase accuracy . this is an important distinction between MIMo

beamforming testing and testing non-beamforming MIMo receivers .

Antenna techniques

As was discussed, polarization is highly critical in MIMo beamforming systems . the

low correlation required by the MIMo aspect of the system is dependent on cross-

polarization of the beams . Furthermore, since space is now a multiplexing domain, the

angles at which the emulated links arrive at the receiver and are delivered from the

transmitter are now critical parts of the RF environment .

Another aspect that must be accurately replicated in a spatially-oriented system is the

antenna pattern . As shown in Figure 11, this is far from uniform and is critical to system

performance .

Figure 11: Typical antenna pattern in a MIMO beamforming system



Channel Models

GsM, CDMA and most wireless technologies employed RF channel models known as

“classical models” . they served for many years as accurate ways to replicate a radiated

signal as seen by a radio receiver .

Figure 12 shows why the classical model is insufficient for testing in MIMo or

beamforming scenarios . As seen by a receiver’s antenna element, the field surrounding

the element is uniform . since a single-antenna narrow-band receiver can not make use

of spatial information, this model is as good as any other .

A wide-band MIMo system, on the other hand, must make use of spatial information in

order to work . For the RF emulation to realistically reflect the real world the system must

replicate all relevant angles of departure, angles of arrival and angle spreads, (i .e .,

geometric channel model in Figure 12) .

noise

A by-product of the polarization needed to reduce signal correlation is that it also

reduces the power of the received signal . In addition, the directivity resulting from a

realistic antenna pattern and the gain provided by beamforming must be accounted for

as well .

this has an effect on adding noise for testing purposes . unlike an sIso environment,

noise levels for testing are not simply a matter of adding a fixed value to the emulated

inherent noise from the transmitter . Instead, additive noise used in testing must be

based on:

• the actual power as measured at each transmitting antenna element

• the calculated loss between each transmitting antenna element and each receiving antenna element

For MIMo beamforming testing, the calculated virtual output power must be used as

the basis for adding noise .

Figure 12: Classical (left) and geometric (right) channel models



ConCLusIon

tD-Lte technology is an ideal upgrade wherever network operators own single-band

spectrum originally intended for tD-sCDMA or wiMAX, or where lower-cost unpaired

spectrum is available .

operators who intend to deploy tD-Lte have resolved to use MIMo techniques to

exploit space as a domain in which to multiplex data streams . these MIMo systems

also employ beamforming, a technique which optimizes coverage by concentrating

power where coverage is needed most . this is especially important in Asian markets,

where operators must optimize coverage due to pockets of high population density .

this paper discussed the drivers behind MIMo beamforming . At a conceptual level this

paper examined the techniques involved and included information intended to help

developers ensure success in deploying MIMo beamforming base stations and ues .

Receiver test requirements for MIMo beamforming present a series of unique technical

challenges as outlined in this paper . these challenges must be considered in the

development and testing phases of a product’s lifecycle . with the goal of isolating

performance issues as early as possible in research and development, device engineers

must have the ability to replicate the complete real-world spatial channel conditions

of even the most complex environments in MIMo beamforming . Automatic phase

calibration, accurate creation of spatial channel models and support for

8 x n bi-directional MIMo, including Mu-MIMo, are essential features for testing MIMo

beamforming .

spirent’s MB5 MIMo Beamforming test system is specifically designed for this purpose .

with years of experience in creating realistic RF environments, spirent is well positioned

to provide a test solution that addresses all areas required to ensure the successful

deployment of tD-Lte and MIMo beamforming .



ACRonyMsAMPs Advanced Mobile Phone system

CDMA Code Division Multiple Access

DCI Downlink Control Information

FDD Frequency-Division Duplexing

GsM Global system for Mobile Communications

MIMo Multiple-Input Multiple-output

Mu-MIMo Multi-user MIMo

RF Radio Frequency

sIso single-Input single-output

snR signal-to-noise Ratio

su-MIMo single-user MIMo

tDD time Division Duplexing

tD-Lte time Domain Long-term evolution

tDMA time Division Multiple Access

tD-sCDMA time Domain synchronous Code Division Multiple Access

ue user equipment

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