3G HSDPA evolution: MIMO and 64QAM Performance in Macrocellular

Deployments

Santiago Tenorio, Yannick Le Pezennec and Manuel Sierra

3G Radio Product Vodafone Group Networks

Madrid, Spain santiago.tenorio@vodafone.com, yannick.lepezennec@vodafone.com, manuel.sierra@vodafone.com

Abstract— This paper provides an overview of the methodology used in the performance assessment of the 64QAM and MIMO HSDPA features in a macro-cellular environment. The paper describes how the geometry experienced by end users could be measured in a live HSPA network, and how this could be used together with link level simulations to perform a first assessment of performance expectation of both MIMO and 64QAM.

Keywords-component;HSPA+; MIMO; 64QAM;Geometry; Abbreviations:

- CPICH: Common Pilot Channel (UMTS) - Ec/No: Chip energy to Noise ratio - RSCP: Received Signal Code Power. - HSPA: High-Speed Packet Access. - HSDPA: High-Speed Downlink Packet Access. - MIMO: Multiple Input Multiple Output - QAM: Quadrature Amplitude Modulation. - Nt: Thermal noise - OMC: Operation and Maintenance Centre. - UE: User Equipment - RNC: Radio Network Controller - UTRAN: UMTS Terrestrial Radio Access Network. - G Factor: Geometry Factor - îor: average received carrier power from the best serving

cell, measured in the UE antenna. - îoc: average received carrier power from all cells different

than the best serving cel, measured in the UE antenna.

I. INTRODUCTION

The evolution of HSDPA in 3G Networks consists of several different features permitting higher data rates than at present. This package of features is very often referred to as “HSPA+”. Two such features are 64QAM (higher order modulation) and MIMO which strive to bring the possibility of

increased peak data rates up to 16.2 Mbps and 21.6 Mbps respectively on the downlink.

In order to understand the overall achievable radio performance for any downlink feature in a given network, it is necessary to determine the typical user experience/environment in a live radio network.

At any point in time in mobile networks a large proportion of data users are located indoors, an environment in which the radio conditions are known to be dramatically different from the typical outdoor radio conditions. Whilst a valid user scenario, drive testing is not considered as typical as the indoor case. Determining accurately radio conditions as experienced by the UEs is the only way of gauging the customer experience for any service and in particular 64QAM and MIMO..

A useful measurement to characterise the quality of the radio conditions within the coverage area in a live network – regardless of the type of terminal and irrespective of receiver performance - is the geometry (“G Factor”) corresponding to the ratio of own to other cell interference at the user terminal antenna reference point. This metric is commonly used in the industry not only in simulations but also in UE compliance testing [1,2].

A good approximation of G Factor can be calculated by using measurements from the network sent by the users’ UEs and such calculations in conjunction with simulations of MIMO and 64 QAM performance will permit an appreciation of what improvements these two features may provide.

II. GEOMETRY MEASUREMENTS

A. Difficulties in measuring the geometry

Given the maturity of the HSDPA+ features in question, geometry calculations can only be performed either by simulations in controlled environments i.e. lab environment. In addition, there is no existing agreed or defined method to

measure geometry as perceived by the end user in a live network. In a live network, it is not possible to measure the interference (Ioc) from other cells as perceived by the end user because such a measurement is not supported by the UE (this is not included within the set of measurements defined in 3GPP). Therefore, given that Ioc cannot be measured one must proceed in determining geometry as experienced by a user via already standardised and available measurements in the UE.

B. Calculating the Geometry Factor

Geometry is calculated based upon CPICH RSCP and CPICH Ec/No as measured by the UE and on the transmitted carrier power Ior as measured by the serving base station(s) in the network. The calculation of the geometry is made as a function of the aforementioned measurements in addition to the CPICH power setting in the network and the thermal noise generated within the user equipment itself..

Using a network-centric approach with respect to measurements also permits the measurement of geometry by remotely collecting the required measurements for the different users at the OMC thus no in the field measurements are required to be performed.

The theoretical description of the method used to measure the geometry is explained next.

What we seek to measure is

oc

or

IIGGeometryˆ

)( = (1)

As mentioned previously, Ioc is not measurable by an end UE hence a method of deriving the Ioc from standard measurements already available in any UE such as CPICH Ec/No and CPICH RSCP measurements in UMTS should be considered.

CPICH Ec/No is defined in [3], and here it can be expressed as follows:

tocoroc

NIIRSCPCPICH

RSSIUTRARSCPCPICHNECPICH

++== ˆ/ (2)

The UTRA RSSI corresponds to :

- to Îor, the total power of the signal received in the operating band (5 MHz for UMTS) which can be expressed as the sum of power coming from the serving cell itself

plus

- the power Ioc coming from neighbour cells (i.e. other than the serving one)

plus

- interference from other systems (including the thermal noise generated within the equipment (Nt).

Note:

The latter is not a measurement that can be reported to the network, hence it is necessary to take into account a typical value for Nt. Laboratory measurements of many end user equipment show that an empirical value of 7 dB can be taken for the noise factor (Nt =KTBF, where F=7 dB). However it is reasonable to neglect Nt as this quantity is for a majority of scenarios negligible with respect to Îo and Ioc. In any case the above empirical value is sufficient to refine the calculation for the scenarios where the geometry is very low (e.g. cell edge).

Hence Ioc can be expressed as follows

NtINoEcCPICH

RSCPCPICHI oroc −−= ˆ/ (3)

îor can be expressed as follows

losscouplingIorIor =ˆ

(4)

And the coupling loss experienced by the user in its present location through the CPICH RSCP measurement based on the knowledge of the CPICH Tx power in the network (available at the OMC), hence

RSCPCPICHpowerTxCPICHlosscoupling =

(5)

Which leads to

powerTxCPICHRSCPCPICHIorIor

.ˆ = (6)

The geometry can then be derived as follows:

RSCPCPICHpowerTxCPICHNtI

NoEcCPICHpowerTxCPICH

IGor

or

./

−−=

(7)

Where orI is the average transmitted carrier power of a cell serving said user equipment as measured by the serving base station and tN is the thermal noise generated within the user equipment.

This expression permits the calculation of geometry based on known parameters and available measurements to the end user.

The calculation of one individual geometry sample for one given user in the live network requires therefore a sample of each of the above measurements (referred hereafter as a geometry measurement sample). In order to ensure an acceptable margin of error in the determination of the geometry it is important to ensure that CPICH RSCP, CPICH Ec/No and Ior measurements are synchronised to a sufficient level, i.e. these measurements should happen at the same time, where typically the measurement period should be synchronised to within at least +/- 500 ms.

RNC

UE

Tracing system

Tx carrierpower (Ior)

measurements

Node B

Trace set-up over UTRAN(including IMSI’s, cell ID’s,

measurement setup)

UTRAN

IMS

I tra

ce

cell

trace

RNC

UE

Tracing system

Tx carrierpower (Ior)

measurements

Node B

Trace set-up over UTRAN(including IMSI’s, cell ID’s,

measurement setup)

UTRAN

IMS

I tra

ce

cell

trace

Fig 1.

In order to derive the distribution of geometry in a live network, the OMC will collect the geometry measurement samples over a defined cluster of cells such that the way that the derived geometry distribution is meaningful. The OMC – specifically the tracing function(ality)– should permit the tracing of user sessions on a per RNC basis thereby ensuring a large sample of traced cells and users. Figure 1 provides an overview of the collection of the geometry measurement samples via the tracing system.

The RNC reports the transmission Tx carrier power measurements Ior coming from the base station, and the CPICH Ec/No and CPICH RSCP coming from the user equipment(s) to the tracing system.

The accuracy of the derived geometry distribution depends upon:

- the size of the target cluster of cells (it is likely to be more useful that any cluster of neighbour sites contain

a sufficient number of cells, typically in the region of at least 5 cells),

- the target number of users traced per cell,

- the target number of samples taken per user.

Variations of the same sampling/tracing over the cluster should be repeated plus/minus one cell to ensure that results obtained for the geometry distribution are representative and not skewed due to the local environment in one cell i.e. the results obtained show negligible differences e.g. median value affected by less than 1%.

Select target cell or cluster

of cells

Select target user(s)

(identify IMSI´s to be traced)

Configure traces

Activate traces via OMC

Post-processing of traces to derive

geometry G of user(s)Geometry statistics of a

given user

Geometry statistics experienced by users in a given cell or cluster of

cell

1 2 3

45

5a

5b

Select target cell or cluster

of cells

Select target user(s)

(identify IMSI´s to be traced)

Configure traces

Activate traces via OMC

Post-processing of traces to derive

geometry G of user(s)Geometry statistics of a

given user

Geometry statistics experienced by users in a given cell or cluster of

cell

1 2 3

45

5a

5b

Fig 2.

Figure 2 describes an example of the overall process that a mobile operator would have to follow for performing such a measurement of the geometry in a live network.

The process has been split into five different phases. The whole process can be done remotely from a computer. For example within Vodafone, a Vodafone employee (with the required rights for security purposes) can access from his own computer the OMC (via the IP network).

The tracing system typically resides within the OMC and allows to perform traces of specific cells and specific user equipment through their IMSI.

The mobile operator sets the target cell or cluster of cells (phase 1) and the target end users –each user is identified by its IMSI– (phase 2). It also configures the measurement settings in the tracing system (phase 3). The traces are activated via the OMC for all selected IMSI’s (phase 4), and the measurements are collected and stored into files which can then be post-processed to obtain geometry statistics (phase 5).

C. .Results: Geometry distribution The aforementioned scenario has been carried out in

Madrid, and all measurements (traces) came from HSDPA users.

The results of the calculation based on these measurements are shown in Figure 3.

Macrocell geometry distribution (cdf)

0

20

40

60

80

100

120

-3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Geometry (dB)

cdf (

%)

Fig .3

The conclusion from Figure 3 is that approximately 30% of the current 3G users have better Geometry than 10 dB.

III. MIMO AND 64QAM PERFORMANCE The expected performances of these features very much

depend on the given radio conditions i.e. the Geometry Factor. Taking into account the results obtained from the measurements in a real network, it is possible to extrapolate/calculate the percentage of users that will benefit appreciably from introducing the features, and also the gain in terms of throughput.

Many different 3G product suppliers have simulated the performance of MIMO and 64QAM for different values of Geometry – and all revealed results are broadly similar. The difference between 16QAM and 64QAM becomes noticeable when the G factor is greater than 10 dB. It is this “break” point where 64QAM becomes beneficial.

MIMO is more promising from a practical point of view given that its two modes - Single Stream and Dual Stream – permit it to be able to handle a wider range of radio conditions, particularly Single Stream mode. Whilst for the full benefit of Dual Stream better radio conditions are required in comparison to Single Stream, a break point G Factor at 8 dB means an improvement over 64 QAM.

A. Results: Throughput improvement compared to Rel’6 HSDPA performance

3GPP Release 6, besides many other improvements, allows

HSDPA connections to reach 10.7 Mbps due to the introduction of 16QAM modulation and 15 Codes.

Some link level simulations performed by different vendors show the performance expectations of 3GPP release 7 HSPA

related features, in particular the throughput using MIMO and/or 64QAM depending on the geometry. Taking into account this simulations and the Geometry Factor distribution measured in real network with the method described before,, it is possible to calculate the throughput gain corresponding to different percentages of users. The figure 4 below shows the throughput improvements of MIMO and 64QAM with respect to the Rel’6 HSDPA “baseline” in a real network.

Fig 4.

These results show significant improvements of for MIMO over 64QAM and the Rel’6 baseline in a macrocellular environment for improving throughput. MIMO should be viewed as a set of two techniques: single stream MIMO (10.8 Mbps peak rate) and dual stream MIMO (21.6 Mbps peak rate).

These two techniques are complementary: dual stream improving significantly the user throughput in good radio conditions whilst single stream improves substantially user throughput in a range of radio conditions experienced by subscribers when compared to a Rel´6 system (the latter is more robust in bad radio conditions). The network switches between the two techniques according to the conditions of the user. Based on Vodafone’s estimations today, MIMO could deliver up to 9 Mbps throughput to 50% of the users in a urban macrocellular network (up to 17 Mbps throughput could be achieved in 10% of the network).

Note that the evolution of HSPA should not be restricted to only these two sole features as other features have been introduced and agreed at 3GPP which are expected to support the improvement of the mobile broadband user experience. Features such as HSPA+ bring key improvements through the support of Continuous Connectivity for packet users (CPC) as do improved Layer 2 functionalities (not elaborated upon in this document).

Also, Interference Cancellation techniques limit interference generated from high rate users thereby improving the overall system capacity. All these enhancements make HSPA+ an indisputable contender in the pursuit of mobile broadband provision.

Note also that in parallel to user experience improvement via these and all the 3GPP agreed HSPA+ techniques,

advanced terminals are required that can sustain high throughput without draining batteries.

REFERENCES [1] 3GPP; TS 25.101, “User Equipment (UE) radio transmission and reception (FDD)”.

[2] 3GPP; TS 34.121, “User Equipment (UE) conformance specification – Radio transmission and reception (FDD))”

[3] 3GPP; TS 25.215, “Physical Layer – Measurements (FDD) (Release 7)”