LTE Technology and TEMS™ Products - Ascom

LTE Technology and TEMS™ Products

LTE Technology and TEMS™ Products

© Ascom 2009. All rights reserved.

TEMS is a trademark of Ascom. All other trademarks are the property of their respective holders.

No part of this document may be reproduced in any form without the written permission of the copyright holder.

The contents of this document are subject to revision without notice due to continued progress in methodology, design and manufacturing. Ascom shall have no liability for any error or damage of any kind resulting from the use of this document.

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2009-03-18 LTE Technology and TEMS™ Products

Contents

1. Overview......................................................................1

2. Achieving High Bit Rates ...........................................1 2.1. Shannon’s Channel Capacity Limit .........................................1 2.2. Using Higher-order Modulation ...............................................3 2.3. Using Higher Bandwidths........................................................3 2.4. Improving C/I ..........................................................................3 2.5. Spatial Multiplexing .................................................................4 2.6. Bit Rate Increase Using Some LTE Techniques......................5 2.7. Other Considerations ..............................................................6

3. The LTE Radio Access Technology ..........................7 3.1. Downlink Radio Access: OFDMA............................................7

3.1.1. Time-domain Structure of OFDMA .........................................................7 3.1.2. Keeping Symbols Apart: The Cyclic Prefix .............................................9 3.1.3. Signaling Overhead in the Downlink.......................................................9

3.2. Uplink Radio Access: SC-FDMA...........................................10 3.2.1. Signaling Overhead in the Uplink .........................................................11

3.3. Multi-antenna Technologies .................................................. 11 3.3.1. Pre-coding.............................................................................................12 3.3.2. Feedback of Channel State Information ...............................................13 3.3.3. Open-loop vs. Closed-loop Spatial Multiplexing ...................................14 3.3.4. The Bottom Line....................................................................................14

3.4. Bandwidth Flexibility .............................................................16 3.4.1. Terminal Capabilities ............................................................................17

3.5. FDD and TDD Harmonization ...............................................17 3.6. Scheduling ............................................................................18

4. General Comments on LTE Radio Network Planning.....................................................................19

4.1. Antenna Configuration ..........................................................19 4.2. Power....................................................................................19 4.3. Signal-to-interference Ratio ..................................................19

5. Using the TEMS CellPlanner LTE Module for Accurate Radio Network Planning ..........................21

5.1. Load-based Downlink Predictions.........................................21 5.2. Traffic-based Predictions ......................................................23 5.3. Statistics................................................................................24 5.4. Cell Capacity.........................................................................25 5.5. Inter-cell Interference Coordination.......................................26 5.6. Other Aspects .......................................................................26

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6. Using TEMS Investigation for LTE Radio Network Tuning........................................................................27

7. Conclusion ................................................................28

8. Abbreviations and Acronyms ..................................29

9. References.................................................................29


1. Overview This document describes briefly the radio access technology behind LTE/eUTRAN and the support that TEMS provides for planning and tuning of mobile packet data networks based on LTE (Long Term Evolution) technology.

The TEMS Products portfolio from Ascom is leading the way with tools for this new technology. For nearly two decades, TEMS products have had a solid track record of industry-leading solutions across all global wireless standards. LTE is the next big step beyond HSPA in the development of 3GPP technologies, and TEMS relies on its experience to support operators moving into this exciting next phase of wireless communication. Already, we are among the first to market with LTE functionality, with planning capabilities in TEMS CellPlanner and tuning support in the globally renowned TEMS Investigation.

Among the many factors driving the development of LTE is the need to push bit rates even higher than what can be achieved with today’s established technologies. To fully appreciate what LTE brings to this scenario, it is helpful to have an understanding of the fundamental performance limitations inherent in wireless communication, as well as techniques for boosting bit rates to bring them closer to the theoretical limits. A discussion of these technical issues can be found in chapter 2, below. Chapter 3 provides details on the LTE radio access technology more specifically. This is not a full treatment of the LTE technology; rather, it is a survey focusing particularly on those aspects that are relevant for LTE radio network planning using TEMS CellPlanner, and LTE radio network tuning using TEMS Investigation. The LTE functionality in those products is discussed in more detail in chapters 4, 5, and 6.

2. Achieving High Bit Rates This chapter discusses some fundamental performance limitations of wireless communication, as well as techniques for boosting bit rates to bring them closer to these theoretical limits. The aim here is to give a clearer appreciation of the challenges any new radio access technology has to address if the target is to deliver higher bit rates than today’s established technologies.

2.1. Shannon’s Channel Capacity Limit

As is well known from Shannon’s famous formula (ref. [1]), the maximum theoretically achievable bit rate under certain conditions for an additive white noise communication channel is:

(1) )logICbandwidthratebit ⋅= 1(2 +

This is also known as the channel capacity.

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The maximum achievable bit rate is thus proportional to the bandwidth and logarithmically dependent on the signal-to-interference ratio (C/I1). Note that in this formula, C/I is linear and not logarithmic (as it is most commonly presented).

This relationship is illustrated in Figure 1 below:

0 5 10 15 20 25 30 35

C/I (linear)

0

Bit

rate

(kbi

t/s)

60008000

100001200014000160001800020000

Shannon bit rate vs. linear C/I

40002000

Figure 1. Theoretical maximum Shannon bit rates (no margins or overheads) for a bandwidth corresponding to 3.84 Mcps.

It follows that in order to increase the bit rate, the options below exist:

• Use higher-order modulation (for bit rates larger than the bandwidth).

• Use larger bandwidths

• Improve C/I, for example by the following means:

− TX/RX diversity

− Beam-forming

− Interference reduction techniques, which include:

More complex receivers, such as GRAKEs, reducing self-interference

New radio access technologies, such as OFDMA/SC-FDMA, which reduce self-interference (to a near-zero level)

• Make smarter use of C/I (spatial multiplexing, a.k.a. MIMO).

1 Although “C” in fact means “carrier”, it is here used simply to represent the useful signal.

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LTE/eUTRAN uses nearly all of the above strategies and technologies. They are elaborated on in subsections 2.2−2.7 as well as in chapter 3.

2.2. Using Higher-order Modulation

In addition to 16-QAM and QPSK, LTE supports 64-QAM modulation. The latter method encodes six (= log2 64) bits in each transmitted symbol.

2.3. Using Higher Bandwidths

Bandwidth allocation in LTE is highly flexible. How this works will be dealt with in describing the LTE radio access technology; see section 3.4.

2.4. Improving C/I

With some degree of simplification, the C/I experienced by a mobile phone can be calculated as follows:

(2) )( thifother

kkTOTk

kk

k NIgPgP

IC

++⋅⋅

⋅=⎟

⎠⎞

⎜⎝⎛

α

=

=M

kcchTOT P

1

I +

Here, k is an index labeling an individual mobile phone and the parameters specific to it. The quantities involved are:

• Pk = base station transmit power allocated to this mobile’s connection

• gk = linear attenuation along the signal path from base station to mobile2

• αk = coefficient modeling the amount of self-interference

• PTOT = total base station power consumption, given by ∑+ kPP ,

i.e. the sum of the power allocated to common control channels and the powers allocated to each individual connection

• Ikother = other-cell interference

• Iif = any other interference, e.g. other-system interference

• Nth = thermal noise

2 The linear attenuation gk is related to the path loss Lp as Lp = −10 log10(gk), provided that the

same reference points are used.

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When a technology such as HSPA is used and the path loss is not excessive, the achievable C/I is typically limited by self-interference caused by multipath propagation (modeled in equation (2) by the term including αk). In order to address this, more advanced receivers (such as GRAKEs) are needed.

OFDMA, on the other hand, reduces self-interference almost to zero. This means that for limited path losses the C/I becomes limited by other-cell interference (Ikother in equation (2)), and it becomes easier to achieve high signal-to-interference ratios without the need for complex receivers. Indeed, compared to HSPA, the LTE downlink can make do with less complex receivers. For more information on OFDMA, see section 3.1.

2.5. Spatial Multiplexing

As Figure 1 indicates, if the C/I is already high, raising the C/I further does not pay off very well in terms of achievable bit rate, due to the logarithmic nature of the bit rate vs. C/I relationship.

To circumvent this limitation, one can use spatial multiplexing, also known as MIMO: “multiple input, multiple output”. It is illustrated in Figure 2.


10000

15000

20000

25000

30000

35000

40000

45000

50000

5000

00 5 10 15 20 25 30

C/I (linear)

Bit

rate

(kbi

t/s)

1x12x24x4

Figure 2. Boosting bit rates with spatial multiplexing (MIMO). (No margins and overheads taken into account.)

The default case with a single stream of data transmitted is represented by the blue curve. If the (linear) C/I is doubled from 10 to 20, the maximum achievable bit rate increases no more than 30%, from 13 Mbit/s to 17 Mbit/s.

On the other hand, if the available C/I is split on two or more antennas, each transmitting its own stream of the data, then with the total C/I remaining at 10, the maximum achievable bit rate becomes 20 Mbit/s (with two transmit antennas) or 27

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Mbit/s (with four transmit antennas). If the total C/I is doubled to 20, the corresponding bit rates become 27 Mbit/s and 40 Mbit/s – an increase of 35% and 50% respectively.

The reason that the spatial multiplexing yields an improvement is the fact that

(3) )//log CICIC ⋅<+⋅<+4

1(log4)2

1(log2)/1( 222I

+

or more generally

(4) nm <≤ ; n

ICnm

ICm +<+ 1 ),/1(log)/1(log 22

that is to say, dividing the data into several streams makes the maximum achievable total bit rate larger. Compare equation (1).

Thanks to this property, spatial multiplexing techniques are becoming increasingly important as a means of achieving high bit rates in favorable radio conditions. Naturally, the task of separating multiple data streams presents a challenge to the receiver; a minimum requirement is for the terminal to be equipped with at least as many antennas as there are parallel data streams.

Spatial multiplexing techniques are built into the LTE standard from the beginning. Section 3.3 takes a closer look at how they are employed.

2.6. Bit Rate Increase Using Some LTE Techniques

Figure 3 below illustrates the impact of bandwidth allocation and spatial multiplexing on the expected maximum achievable bit rates in LTE. (This time, C/I is plotted in dB, which is more practical when the range of C/I values is large.)

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Bit

rate

(kbi

t/s)


350000

250000

200000

150000

100000

50000

0

300000

–10 0 10 20 30C/I (dB)

5 MHz

20 MHz MIMO 4x420 MHz MIMO 2x220 MHz

5 MHz MIMO 2x25 MHz MIMO 4x4

Figure 3. Theoretical maximum LTE bit rates as functions of C/I. Note that this is still based on Shannon, not on simulations; a fixed (25%) overhead is assumed, with no margins whatsoever and no inter-stream interference. The maximum bit rate is thus limited solely by the channel rate.

Even though the C/I-to-bit rate mappings given here are exaggerated (since no attempt is made to model the properties and effects of the radio channel, and since no exact overheads are calculated), the diagram shows the importance of bandwidth as well as the potential improvements obtainable with spatial multiplexing techniques.

In fact, Figure 3 shows that for high C/I values the bit rate becomes channel rate limited if multiple stream transmission is not used.

2.7. Other Considerations

So far, this chapter has been dealing with fundamental performance limits. There are also practical limitations on the bit rate that can be offered to the end-user, such as protocol overheads and latencies (delays). It is important to keep the round-trip time short, that is, to minimize delays between network elements, as this directly improves the performance of time-critical activities.

The round-trip time also affects the achievable application-level throughput in less obvious ways. Application throughput depends on the behavior of the involved higher-layer protocols, and a reduced round-trip time typically improves the application bit rate. This is because the most commonly used internet protocol, TCP, is interactive, meaning that the sender buffers sent packets until it gets an acknowledgement from the receiver. As the buffer size is limited, the sender may be forced to stop sending until acknowledgements have been received and the corresponding buffered data can be removed. However, the shorter the round-trip time, the less likely this is to happen.

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3. The LTE Radio Access Technology In January 2008, 3GPP confirmed that the LTE specifications had been approved and had been placed under change control, leading to their inclusion in the forthcoming 3GPP Release 8. The 3GPP March 2009 release, including change requests, is estimated to include the minimum needed for commercial launch.

Figure 4 presents some key aspects of the LTE radio access technology as standardized by 3GPP. Each of these will be dealt with in this chapter.

Frequency

Frequency

Flexible bandwidth– Possible to deploy in bandwidths from 1.4 MHz to 20 MHz

UL: SC-FDMA, dynamic bandwidth (pre-coded OFDM)– Low PAPR higher power efficiency– Reduced UL interference (enables intra-cell orthogonality)

DL: Adaptive OFDM– Channel-dependent scheduling and link adaptation

in time and frequency domains

Multi-antennas, both RBS and terminal– MIMO, TR and RX diversity, interference rejection– High bit rates and high capacity TXTX RXRX

Time

Time

Harmonized FDD and TDD concept– Maximum commonality between FDD and TDD

20 MHz1.4 MHz

Figure 4. Key aspects of the LTE radio access technology.

3.1. Downlink Radio Access: OFDMA

The access technology used in the LTE downlink is called orthogonal frequency division multiple access (OFDMA).

3.1.1. Time-domain Structure of OFDMA

The fundamentals of the OFDMA time-domain structure appear from Figure 5:

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Time domain structure:– 10 ms frame consisting of 10 subframes of length 1 ms– Each subframe consisting of 2 slots of length 0.5 ms– Each slot consisting of 7 OFDM symbols (6 symbols in case of extended CP)

Resource blocks:– 1 resource block consists of 12 subcarriers during one slot– Assigned to user in pairs: 2 consecutive resource blocks = 1 scheduling block

One subframe (1 ms)

One slot (0.5 ms)

One frame (10 ms)

One resource element

12 subcarriers

TCP Tu

One resource block = 12 × 7 = 84 resource elements

Figure 5. OFDMA time-domain structure.

As Figure 4 and Figure 5 both illustrate, data in OFDMA is transmitted on many subcarriers in parallel. At the point of transmission there is no interference3 between subcarriers, and subcarriers can therefore in principle be allocated freely to users. However, for practical reasons, the allocation to a single user is always an integer number of blocks consisting of 12 consecutive subcarriers. Such a block allocated in one 0.5 ms slot is called a resource block (RB) and has a bandwidth of 180 kHz.

Subcarriers in OFDMA are spaced 15 kHz apart, seemingly allowing for 15 symbols per subframe. However, as shown in Figure 5, there are typically 14 OFDM symbols per millisecond. This discrepancy is explained by the addition of a “cyclic prefix”, used to guarantee orthogonality in time-dispersive environments; see section 3.1.2. The overhead is close to 7% in the shown configuration.

It follows that the channel symbol rate per RB is 168 ksps (12 × 14). The maximum bit rate depends on the choice of modulation scheme, the choice of antenna transmission scheme (use or non-use of MIMO), the number of RBs allocated, and the overhead in terms of reference symbols, synchronization symbols, etc. In practice, it can generally (with some exceptions) be assumed that the total RBS power available is shared equally across all RBs, whether they are used or not.

Note that for a given resource block there is little or no inter-cell interference, provided that the RB in question is not used by any of the neighboring cells.4 The probability of an RB being interfered by other cells thus depends on the average downlink load in the network.

3 This is due to the fact that the symbol length is set equal to 1/(subcarrier spacing) and that

the subcarrier frequency is chosen such that an integer number of wavelengths fit into the symbol time.

4 There may be some interference from reference symbols and other overhead symbols (to be discussed in section 3.1.3), even if there is no traffic

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3.1.2. Keeping Symbols Apart: The Cyclic Prefix

Due to multipath propagation, delayed copies of the transmitted signal will arrive at the receiver, as illustrated in Figure 6 (left). If no special action is taken, the tail of a time-delayed copy of a symbol will overlap with the beginning of a less-delayed copy of the next symbol. The resulting inter-symbol interference is a kind of self-interference.

In order to prevent inter-symbol interference, a cyclic prefix is added to the end of each symbol. The cyclic prefix consists of the last few samples of the symbol inserted before the symbol starts. With the cyclic prefix in place, a delayed symbol copy will not intrude upon the following symbol, unless the difference in delay exceeds the length of the cyclic prefix. Therefore, as long as the length L of the cyclic prefix is at least equal to the time dispersion τ of the channel, no inter-symbol interference will occur, as shown in the right-hand part of Figure 6.

Minimizing self-interference serves to increase the probability of a high signal-to-interference ratio, but it clearly comes at a price: the cyclic prefix increases the overhead. Still, in most, though not all, radio environments the use of the cyclic prefix yields a gain in spectrum efficiency (capacity).

Time

Channel profile

RX window

τ

CP

CP

CP

Channel profile

RX window

L

Timeτ τ

Figure 6. Multipath propagation: without cyclic prefix (left); with cyclic prefix (right). The impulse response of the channel is graphed at the top, and the bottom part shows successive time-delayed and attenuated copies of the transmitted signal. Without a cyclic prefix, parts of a contiguous symbol (green, dashed) intrudes into the RX window. On the other hand, when a cyclic prefix of length L ≥ τ (red, dashed) is used, the prefix appears at either end of the symbol, and there is no interference from a different symbol within the RX window.

3.1.3. Signaling Overhead in the Downlink

Not only the downlink shared channel, but also various control bits and signaling are mapped on the downlink physical resource. These include:

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• Cell-specific reference signals (used for channel estimation, CQI measurements, and mobility measurements)

• Layer 1/Layer 2 control signaling (used for downlink scheduling, HARQ info, uplink scheduling grants, and power commands)

• Primary and secondary synchronization signals (used for cell search)

• Broadcast channel and paging channel

The reference signal is of particular significance, since it corresponds to some extent to the common pilot channel (CPICH) in WCDMA. The reference symbol mapping in the case of one antenna is shown in Figure 7.

Figure 7. Reference signal mapping (one transmit antenna).

These reference signals, as well as the control signaling, constitute overhead that will occupy some of the available downlink resources and reduce the effective maximum bit rate (compare Figure 3). In the configuration shown in Figure 7, the overhead from the reference symbols alone is approximately 4.8%.

3.2. Uplink Radio Access: SC-FDMA

From a radio network planning perspective, one can treat the uplink as if it used the same resource block structure as the downlink. It is, however, important to minimize the peak-to-average-power ratio (PAPR) in order to reduce power amplifier complexity. Since the PAPR becomes quite high with so many subcarriers being modulated independently, a pre-coding is performed in the uplink whereby subcarriers are “spread out” to form a single (broader) carrier. This reduces the PAPR, while adding some complexity in the receiver; but receiver complexity is not as critical in the radio base station as in the terminal.

In practice one can operate at the same channel rate per RB of 168 ksps (12 × 14) as in the downlink. Furthermore, just as for the downlink, the maximum payload rate depends on the modulation scheme, the number of RBs allocated, and the amount of overhead from various sources. It should be noted, however, that in the uplink the terminal can allocate all its available power to the resource blocks it is using, so when the bandwidth use is increased, the available power per RB will go down.

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3.2.1. Signaling Overhead in the Uplink

Just as in the downlink, the uplink physical resources are used not only for the uplink shared channel but also for various kinds of signaling and control channels, such as:

• Uplink reference signals for uplink channel estimation

• Sounding signals for timing and channel quality (CQ) estimates for the scheduler (in case of zero transmission and/or to obtain CQ across the whole frequency band)

• Uplink control signals: downlink CQI, scheduling requests, and ACK/NACK of downlink shared channel data

The uplink reference symbol corresponds to the embedded pilot in the WCDMA uplink. The mapping is shown in Figure 8:

One slot (0.5 ms)

One sub-frame (1 ms)

Reference signalData

User #1 User #2

Figure 8. Reference signal used for uplink channel estimation.

The overhead consumed by the uplink reference signal alone in this configuration is thus always 1/7 of the total resources available.

3.3. Multi-antenna Technologies

To meet the extreme performance targets of LTE in terms of peak data rates, coverage, and capacity, advanced multi-antenna solutions are crucial. Different solutions are called for depending on the precise nature of the targets and how they are prioritized. In broad outline, we may state the following (see also Figure 9):

• For improved coverage, use beam-forming and/or diversity techniques.

• For higher peak data rates, use multi-layer transmission (spatial multiplexing).

• For higher capacity, use beam-forming and multi-layer transmission in combination.

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DiversityFading reduction

Spatial multiplexingData rate multiplication

S/PDelay

DirectivityAntenna/beam-forming

gain

Channel knowledge (average/instant)

Improve link budget Increase bit rate

Track channel and obtain array gain

Know nothing – go for robustness

Utilize “excess” C/I in a clever way

Transmit signal in best Transmit signal in best directiondirection

Transmit signal in all Transmit signal in all directionsdirections

Transmit several signals Transmit several signals in different directionsin different directions

Figure 9. Multi-antenna technologies.

It should be noted that these technologies make different assumptions about channel knowledge at the receiver and transmitter. Many of them also provide benefits in more than one respect. The size of the improvements achieved depends on the properties of the channel (including antennas and antenna spacing) as well as on interference conditions.

In order to address the diverse needs that may arise, LTE employs a generic antenna concept, adaptable to a wide range of scenarios and prioritization schemes (large vs. small cells, high peak data rates vs. good coverage, etc.). Multi-antenna support is mandatory for LTE terminals. In the 3GPP specifications seven different semi-statically configured downlink transmission modes are described, six of which are multi-antenna related. These transmission modes include (but are not limited to):

• TX diversity

• Open-loop spatial multiplexing

• Closed-loop spatial multiplexing

3.3.1. Pre-coding

Pre-coding is a generic framework for mapping symbols to antenna ports. See Figure 10. The transmission mode is controlled by the antenna setup as well as by the set of pre-coding matrices chosen; it also depends on what type of feedback the terminal provides. By varying the pre-coding, therefore, any transmission mode compatible with the given number of antennas can be selected, such as TX diversity, beam-forming5 or spatial multiplexing, and combinations thereof.

5 In this document, no distinction is made between “classical” beam-forming (with highly

correlated antennas) and “non-classical” beam-forming.

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As a simple example, consider Figure 10:

w1

w2

sh2

h1

y = (h1w1 + h2w2)s + e

Figure 10. Pre-coding.

The signal to transmit is s. If the effects of the radio channels, h1 and h2, are known, then in principle the pre-coding vectors w1 and w2 that maximize the signal-to-noise ratio can be determined.

The optimal pre-coding vectors (weights) can be shown to be

(5) 22

2 h+ ; 1*22

22

21

*11 , hhwhhhw =+=

the received signal then becomes

(6) esh 22 hy ++= 2

1

and the achieved signal-to-noise ratio becomes proportional to 22

21 hh + .

3.3.2. Feedback of Channel State Information

As Figure 11 illustrates, the UE feeds back channel state information (CSI) to assist link adaptation and scheduling. The terminal reports both a rank indicator, RI (recommends how many different data streams in parallel the UE should be able to receive) and one or several channel quality indicators, CQIs (which indicate the recommended transport format given a certain BLER). For closed-loop spatial multiplexing, one or several precoder matrix indicators (PMIs) are also reported.

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Coding & Modulation

Serial/Parallel Receiver

CSI feedback

Mapping to Layer

& Precoding

Coding & Modulation

Figure 11. Feedback mechanism for channel state information.

3.3.3. Open-loop vs. Closed-loop Spatial Multiplexing

To enable a better intuitive understanding of the various options, a high-level comparison of open-loop and closed-loop spatial multiplexing is carried out below. It is assumed that four antennas are available both to the base station and to the UE.

3.3.3.1. Closed-loop Spatial Multiplexing Mode

Simply put, in this mode, the pre-coder may be said to focus its transmission in “strong” directions towards the UE; the pre-coder matrix is selected from a finite codebook. The aim is to track channel characteristics in time as well as in frequency.

This mode is intended for scenarios with accurate CSI available at the eNode-B, normally requiring that the terminal is moving slowly, or in other words that the mobility is low.

3.3.3.2. Open-loop Spatial Multiplexing Mode

In this mode the transmission takes place “in all directions”, and a sequence of four different pre-coders is cycled through during the transmission of a single subframe. If the transmission rank is one (i.e. only one data stream is sent), transmit diversity is utilized.

This mode targets scenarios with inaccurate CSI at the eNode-B, typically corresponding to terminals with high mobility.

3.3.4. The Bottom Line

At the end of the day, the goal is to adapt the spatial properties of the transmission to match the current channel conditions and/or increase the signal-to-interference ratio by striving for coherent addition of the transmitted signals at the receiver. Figure 12 below compares the performance of some of the options.

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Single layer + beam-forming, 4x2

Coverage

Thro

ughp

ut

Single layer, 1x1

Two layers + beam-forming, 4x2

Single layer, 2x2

Two layers, 2x2

Single-layer, 1x2

Figure 12. Different downlink antenna solutions imply different capacity/coverage trade-offs.

Throughout the diagram, N×M means N transmit antennas and M receive antennas. The number of “layers” is the number of parallel data streams.

• Single layer, 1×1 corresponds to the traditional downlink configuration with one TX and one RX antenna.

• Single layer, 1×2: One data stream is transmitted, using one antenna, but the receiver has two receive antennas, improving coverage compared to the Single layer 1×1 case.

• Single layer, 2×2: One data stream is transmitted, using two antennas also for transmission, which further improves coverage.

• Two layers, 2×2: Two data streams are transmitted, potentially doubling the bit rate in areas with good C/I (low path loss) but providing poorer coverage in areas with poor C/I. In practice, we can switch to Single layer 2×2 at the point where the two curves intersect in order to increase robustness in difficult radio conditions.

• Single layer + beam-forming, 4×2: A single data stream is transmitted, but using four TX antennas in order to “focus” the transmission. In this way coverage can be substantially extended.

• Two layers + beam-forming, 4×2: Two data streams are transmitted, again allowing a doubling of the bit rate if the C/I is good (low path loss). In practice, we may combine this configuration with the preceding one, thus operating at the envelope of the two curves and switching between the two configurations as dictated by the radio conditions. (Compare the pairing of Single layer 2×2 and Two layers 2×2 discussed above.)

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3.4. Bandwidth Flexibility

LTE supports a variety of different channel bandwidths. As seen in section 2.1, the bit rate scales linearly6 with the bandwidth. Figure 13 tabulates the bandwidths supported by current 3GPP specifications.

Channel bandwidth (MHz) 1.4 3 5 10 15 20

Transmission bandwidth configuration NRB 6 15 25 50 75 100

Channel bandwidth (MHz)

Transmission bandwidth configuration (RB)

Transmission bandwidth (RB)

Resource block

Figure 13. Channel bandwidths with RF requirements supported by 3GPP TS 36.101 and 3GPP TS 36.104 at present. This diagram illustrates only transmission of user data; the six center RBs are always used for some of the control channels.

Note that at any instant in time, the downlink transmission can take place in any subset of RBs within the transmission bandwidth. In the uplink the same is true, except that to conform to single-carrier properties, the RB allocation has to be contiguous.

The maximum channel rate for any channel bandwidth can easily be calculated. As an example, take the channel bandwidth 20 MHz corresponding to a transmission bandwidth configuration of 100 RBs. The maximum channel rate is then:

100 (RBs) × 12 (subcarriers/RB) × 14 (symbols/ms) × 6 (bits/symbol; assumes use of 64-QAM) × 4 (assumes that 4×4 MIMO is possible) = 403,200 kbit/s = 403.2 Mbit/s.

6 In reality the relationship is not exactly linear, since the percentage of overhead goes down

when the bandwidth increases.

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Assuming a typical DL overhead of around 25% (see section 3.1.1 for more details), the maximum achievable bit rate in 20 MHz becomes approximately 300 Mbit/s.

3.4.1. Terminal Capabilities

The bit rate may be limited not only by the channel rate, the C/I, and the antenna configuration; it may also be limited by the terminal capabilities. Figure 14 gives a list of LTE terminal categories, taken from ref. [2]:

Category 1 2 3 4 5

DL peak rate 10 50 100 150 300

UL peak rate 5 25 50 50 75

Max DL mod. 64-QAM

Max UL mod. 16-QAM 64-QAM

Layers for spat. multiplexing 1 2 4

Figure 14. LTE terminal categories.

Since terminals supporting four antennas are not expected to be available at the launch of early LTE networks, it can be gathered from the table that initially the maximum downlink bit rate in LTE will be 150 Mbit/s and the maximum uplink bit rate 50 Mbit/s.

3.5. FDD and TDD Harmonization

LTE supports both Frequency Division Duplex (FDD) and Time Division Duplex (TDD), so these can be seen as two different modes within the same technology. Two frame structures are defined, one for FDD and one for TDD, but the frame and subframe lengths are the same. See Figure 15. The physical layer and procedures are essentially the same, including coding, modulation, and sequences; the only major difference is the different timing for Layer 1/Layer 2 control. Of course, from a network planning perspective, FDD and TDD are quite different.

TDD

fULDL

FDD

fUL

fDL

Figure 15. FDD and TDD harmonization.

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3.6. Scheduling

The scheduler in LTE has access to both the time domain and the frequency domain. This means that if frequency-dependent channel quality information is available (from CQI reporting), the scheduler can optimize the resource block allocation so as to achieve the best possible utilization of the resources.

Consider Figure 16. Assuming the absence of other constraints, at the beginning of the time interval the yellow terminal has the best channel in RBs 2 and 5, whereas at the end of the interval the best allocation is to give the yellow terminal RBs 2, 3, 5 and 6. (In this diagram the RBs are seen as traveling from left to right along the Time axis, so the earliest time is represented by the RBs closest to the Frequency axis).

180 kHz

1 ms

data1data2data3data4

Time

Frequency

User 1 scheduled

User 2 scheduled

Time-frequency fading, user 1

Time-frequency fading, user 2

Figure 16. Scheduling in time and frequency domains.

Similar principles can be used for the allocation of uplink resources to the terminals, the difference being that the allocation must be contiguous in order to preserve the single-carrier properties.

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4. General Comments on LTE Radio Network Planning

From the foregoing it should be clear that the following aspects are of key importance for the performance of LTE:

4.1. Antenna Configuration

The antenna configurations in terminal and base station are both important, because they determine the coverage and capacity properties as well as the maximum achievable bit rates. For example, with a single RX antenna in the terminal, dual-stream (MIMO) transmission is not possible, but open-loop TX diversity can still be used if the base station has two transmit antennas. On the other hand, if the terminal has two RX antennas, RX diversity gain is still available even if the base station does not support two transmit antennas.

4.2. Power

Generally speaking, the more power that is available to share across the resource blocks, the greater the improvement in coverage and/or capacity. Of course, in some situations, the C/I itself does not change if more power is allocated, because the interferers also grow proportionately stronger; but in general more power means better performance.

4.3. Signal-to-interference Ratio

In the absence of inter-system interferers, the signal-to-interference ratio achievable in OFDMA for an individual terminal at position k is given by

(7) th

kother

k

k NIIC

+⋅

=⎟⎠

⎞⎜⎝

⎛

kother

th

kg k

kgP

In this expression, zero self-interference is assumed, while the other-cell interference term ( I ) is the sum of all other transmissions that interfere with the wanted signal. The thermal noise level is given by N .7 The wanted signal is dependent on the path gain ( ) as well as on the available power ( P ). It is clear that the C/I is maximized if the other-cell interference can be kept to a minimum, and this is indeed one of the more critical activities during radio network planning.8

7 Since sub-carriers are orthogonal, calculations can be done per RB, and the thermal noise

in that case is the thermal noise integrated over 180 kHz (168 ksps). 8 Of course, some inter-cell interference must always exist, since LTE is a 1:1 re-use system

and some overlap must exist for mobility reasons.

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A similar expression for the signal-to-interference ratio applies to the uplink, but there the sum is naturally to be taken over all interfering terminals.

The most important aspect of estimating the performance of an LTE system about to be deployed is to obtain good estimates of the signal-to-interference ratio distribution. Since this distribution depends heavily on the signal attenuation, which in turn depends on the environment, it is best computed using a radio network planning tool. This is the subject of chapter 5. Of course, for dimensioning purposes, signal-to-interference ratio distributions can be obtained with propagation models (for example homogenous Okumura-Hata type models); but in chapter 5, only the use of a radio network planning tool such as TEMS CellPlanner is discussed.

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5. Using the TEMS CellPlanner LTE Module for Accurate Radio Network Planning

Ascom already has the know-how to make accurate LTE performance predictions, as well as a tool for computing them (TEMS CellPlanner 8.1). This chapter presents some of the vital LTE functionality offered by TEMS CellPlanner.

5.1. Load-based Downlink Predictions

As mentioned earlier, estimating the signal-to-interference ratio is critically important for making good LTE performance predictions. TEMS CellPlanner uses highly accurate macro cell propagation models taking into account topography, land usage (“clutter”), earth curvature, and other relevant factors. If a building database exists, even more accurate predictions become available.

Figure 17 shows the C/I distribution from a prediction where the average load is set to 0.5. This means that the average probability of a given RB being utilized is 50%, or put differently, the impact of the interference is 3 dB lower than its maximum.

Figure 17. TEMS CellPlanner plot showing downlink signal-to-interference ratio plot for an average load of 50%.

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The sector joints, where the impact of inter-cell interference is at its worst, can be clearly seen in this snapshot. It is up to the radio network planner to shrink the areas of low C/I as far as possible, or at least to try to place them where traffic is scarce.

These predictions are designed for fast computation. They are not Monte Carlo based; that is, no users are present and the traffic profile is not used. Rather, the level of traffic is specified simply in terms of average load.

A bit rate distribution can be derived from the C/I prediction. TEMS CellPlanner uses C/I-to-bit-rate mappings based on the latest research data. These mappings take symbol overhead into account, and different mappings exist for different channel models and different assumptions about antenna configurations. The bit rate distribution below (Figure 18) was obtained from the C/I distribution in Figure 17, assuming 2×2 MIMO configuration, 10 MHz bandwidth, and a Pedestrian A type of channel model with low terminal speed.

Figure 18. TEMS CellPlanner plot of downlink bit rate distribution (10 MHz, MIMO 2×2, Pedestrian A).

Again, these predictions are very fast to do, since no modeling of the traffic is involved; yet they provide a good understanding of potential performance under a specified load condition. Of course, changing the load assumptions gives a different C/I distribution, and hence also a different bit rate distribution.

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5.2. Traffic-based Predictions

In certain situations, load-based predictions such as the ones described in section 5.1 are not sufficient. One can then proceed to more sophisticated predictions which simulate traffic from individual mobile phones.

There are two main reasons to undertake such traffic-based calculations. First is the fact that the uplink performance is very sensitive to where the terminals are positioned. Also, the uplink interference depends on the UE transmit power and the position of the terminal with respect to neighboring base stations. Hence, Monte-Carlo simulations are necessary to be able to spread these terminals in a pseudo-random manner (“pseudo” because the probability that a terminal at a given location is trying to connect typically depends on land-use/clutter). A large number of simulations are usually performed in order to make the prediction statistically significant.

The second reason is that realistic modeling of terminals and traffic demand (which of course does require good input data) also makes it possible to obtain statistics on blocking (served traffic versus non-served traffic). If the result is unsatisfactory, then modification of the network, for example addition of more sites, may be called for.

Figure 19. TEMS CellPlanner plot showing maximum uplink C/I.

Figure 19 shows the average of the maximum uplink C/I predicted by ten Monte Carlo simulations. (Thanks to parallel processing, these simulations execute very fast.) Close to the site, the terminal is already achieving a C/I corresponding to the maximum bit rate and hence is in “power regulation mode”. However, further out the

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terminal would need to transmit at full power in order to achieve the C/I displayed in the figure, and the C/I can therefore be said to be path loss limited.

Note that the inter-cell interference comes from the terminals spread out across other cells and depends heavily on the amount of data they are trying to upload.

Figure 20 shows the corresponding uplink bit rate plot:

Figure 20. TEMS CellPlanner plot showing achievable uplink bit rate given a certain traffic demand.

5.3. Statistics

Once the simulations are complete, statistics can be generated and presented in spreadsheets and plots.

In Figure 21 are collected some uplink statistics from Monte Carlo simulations for a number of cells. The number of users connected is shown as well as served traffic versus non-served traffic. We note that there is no blocking in this relatively lightly loaded scenario. All the data in this spreadsheet can alternatively be displayed in plots.

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Figure 21. TEMS CellPlanner: Uplink statistics from Monte Carlo simulations.

For the downlink a similar set of statistics can be obtained, as shown in Figure 22. Here, the offered and served traffic are the same; in other words, there is no blocking.

Figure 22. TEMS CellPlanner: Downlink statistics from Monte Carlo simulations.

Notice that the uplink and downlink figures are slightly different. The reason in this case is not that the uplink and downlink traffic demands are different (although typically they are). Rather, the explanation is that the uplink statistics come from the Monte Carlo simulations, whereas the downlink statistics are generated directly from the traffic density map itself; that is to say, the actual terminal positions from the Monte Carlo simulations are not taken into account. This approach is fast, since it allows generation of downlink statistics without doing Monte Carlo simulations. In a future release of TEMS CellPlanner, it will be possible to use terminal distributions from Monte Carlo simulations for the downlink statistics as well.

5.4. Cell Capacity

The cell capacity (average bit rate) is an important output from the radio network planning, since it determines whether or not the network will be able to handle the forecasted traffic. If it will not, the network design must be improved, for instance by the addition of more sites. From the numbers in section 5.3 one can estimate the cell capacity as served rate divided by utilization. Note, however, that this estimate depends on the assumption that the neighboring cells have the load they received from this particular traffic distribution. The actual cell capacity would of course be lower if all surrounding cells had 100% load.

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5.5. Inter-cell Interference Coordination

Inter-cell interference coordination (ICIC) is a method that promises to improve the uplink performance in many traffic scenarios and therefore constitutes an important aspect of the LTE uplink. Within 3GPP, a number of different schemes have been studied which do not utilize signaling between base stations across the X2 interface. All these schemes will be possible to model in future versions of TEMS CellPlanner (the current version does not yet support them). However, for most operators, the downlink is the primary concern, and the downlink modeling in today’s TEMS CellPlanner is already exceptional in its accuracy.

5.6. Other Aspects

In chapter 4, a number of factors impacting LTE performance were discussed. These too can be modeled with TEMS CellPlanner: choice of antenna configuration, power amplifier power, bandwidth, and others. TEMS CellPlanner furthermore enables the user to explicitly compare different LTE configurations in order to make the most cost-efficient choice for a particular network and environment.

Historically, neighbor cell optimization has been a major activity undertaken by tuning and optimization teams. To reduce such operational costs for LTE radio access networks, operators have compiled a set of requirements called Self-organization Network (SON). As part of that concept, “automated” neighboring cell relations are available from some vendors. This means that a neighbor which is detected by a terminal but has not yet been defined as such is “automatically” added as a neighbor. This causes a small delay in the handover process, but once the detected neighbor is defined, it will of course be available to other terminals without any further handover delays being caused.

The SON concept does not eliminate the need to study neighbor cell relations, but it does allow engineers to focus more of their attention on end-to-end performance during the tuning and optimization phases.

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6. Using TEMS Investigation for LTE Radio Network Tuning

As has been discussed in previous chapters, the signal-to-interference ratio distribution is of vital importance for the performance of an LTE-based radio access network. Indeed, unless coverage-limited cells are discussed, the signal-to-interference ratio is limited by inter-cell interference, and hence the same RF tuning practices can be adhered to as for WCDMA radio networks: that is, to minimize cell overlap and overshooting (minimize “pilot pollution” in the WCDMA terminology) but at the same time provide enough overlap to ensure good mobility.

TEMS Investigation 9.1 introduces LTE drive test support by allowing connection of a DRT4301A+ LTE MISO scanner. Some key RF measurements captured with this scanner are:

• RSRP: Reference Signal Received Power

• RSSI: Received Signal Strength Indicator

• RSRQ: Reference Signal Receive Quality. Defined as N × RSRP / RSSI, where N is the number of resource blocks across which RSSI was measured

Comparing with WCDMA, RSRP is similar to RSCP (Received Signal Code Power) measured on the WCDMA common pilot, while RSRQ is similar to WCDMA Ec/N0. Therefore (although the details differ slightly between the technologies) it can be said generally that RSRP measurements tell whether the cell is interference or coverage limited, while RSRQ measurements give indications of excess interference in unloaded or loaded cells.

Drive tests measuring the above parameters are essential after infrastructure installation to enable the necessary antenna adjustments, such as tilting and changing of azimuths. Such drive tests can now be done with TEMS Investigation.

In the TEMS Investigation application, the LTE data is extracted to information elements just like other data. These elements can be presented in map, chart and status windows of the user’s choice. A number of predefined LTE presentation windows are also provided, including the following bar chart for monitoring RSRQ:

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Figure 23. TEMS Investigation: Bar chart showing snapshot of Reference Signal Es/Io (i.e. RSRQ). The x-axis is labeled with the Physical Cell Identity of each channel scanned.

Naturally, as user terminals for LTE become available, TEMS Investigation will add support for connecting such terminals, enabling service testing, optimization of handover parameters, and so on.

7. Conclusion The development of LTE technology is being driven to a large degree by the need to push bit rates ever higher. With a full understanding of this need, as well as other aims including bringing down latency and reducing complexity, it is easier to understand the need for LTE technology, and for the tools that will make LTE implementation successful. The TEMS Products portfolio from Ascom is well-positioned to fulfill this need. Current releases of TEMS CellPlanner and TEMS Investigation are already available with LTE functionality for the preliminary stages of the LTE lifecycle. Other TEMS products will include LTE support as this exciting new technology matures.

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8. Abbreviations and Acronyms 3GPP 3rd Generation Partnership Project BLER Block Error Rate CFO Carrier Frequency Offset CINR Carrier to Interference-plus-Noise Ratio CPICH Common Pilot Channel CQI Channel Quality Indicator CR Change Request CSI Channel State Information DL Downlink eUTRAN Evolved UMTS Terrestrial Radio Access Network FDD Frequency Division Duplex GRAKE Generalized RAKE receiver, a.k.a. Advanced Receiver Type 2 HARQ Hybrid Automatic Repeat Request ksps Kilosymbols per second LTE Long Term Evolution Mcps Megachips per second MIMO Multiple Input Multiple Output MISO Multiple Input Single Output OFDMA Orthogonal Frequency Division Multiple Access PCI Physical layer Cell Identity PCIG Physical layer Cell Identity Group PMI Precoder Matrix Indicator P-SCH Primary Synchronization Channel QAM Quadrature Amplitude Modulation RB Resource Block RF Radio Frequency RS Reference Signal RSRP Reference Signal Received Power RSRQ Reference Signal Received Quality RSSI Received Signal Strength Indicator SC-FDMA Single Carrier Frequency Division Multiple Access SCH Synchronization Channel S-SCH Secondary Synchronization Channel TCP Transaction Control Protocol TDD Time Division Duplex UL Uplink

9. References [1] Any standard text on information theory will contain a discussion of this topic,

such as Cover, Thomas M. and Thomas, Joy A., Elements of Information Theory, 1991, Wiley, ISBN 0-471-06259-6.

[2] 3GPP 36.306, User Equipment (UE) radio access capabilities.

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