Overview of COST 273 Part I: Overview of COST 273 Part I: propagation modeling and channel propagation modeling and channel

characterizationcharacterization

Irina Sirkova

Microwave remote sensing Lab., IE-BAS

ICEST 2006

ICEST 2006 2

Contents

Brief summary of COST Action 273

Activities related to propagation modeling and channel characterization

Description of the two major achievements in Action 273:• MIMO channel model;• reference scenarios for radio network simulation

and evaluation.

ICEST 2006 3

What is COST? - Cooperation in Science and Technology, http://www.cost.esf.org

COST 207 “Digital Land Mobile Radio Communications”, Mar. 1984–Sep. 1988, contribution to the GSM development;

COST 231 “Evolution of Land Mobile Radio (Including Personal) Communications”, Apr. 1989–Apr. 1996, contribution to the development of GSM1800, DECT, HIPERLAN 1 and UMTS;

COST 259 “Wireless Flexible Personalized Communications”, Dec. 1996–Apr. 2000, contribution to the development of DECT, UMTS, HIPERLAN 2;

COST 273 “Towards Mobile Broadband Multimedia Networks”, May 2001-May 2005, www.lx.it.pt/cost273.

ICEST 2006 4

COST 273 “Towards Mobile Broadband Multimedia Networks” - Main objectives

to increase the knowledge on the radio aspects of mobile and wireless broadband multimedia networks;

to explore and develop new methods, models, techniques, strategies and tools that will give inputs to the development of systems beyond the 3rd generation mobile and wireless communication systems;

to contribute to the deployment of systems that are more or less standardized, like UMTS and WLANs.

ICEST 2006 5

Structure and activities of COST 273

WG1: RADIO SYSTEM ASPECTS

WG 2: PROPAGATION AND ANTENNAS• SWG 2.1: MIMO channel model• SWG 2.2: Antenna performance of Small Mobile

terminals • SWG 2.3: Channel Measurements

WG3: RADIO NETWORK ASPECTS• SWG 3.1: Mobile Radio Networks Reference Scenarios

ICEST 2006 6

Activities related to propagation modeling

Propagation modeling activities (done essentially in WG 2 and SWG 3.1) have tried to reduce two gaps characterizing the former Actions:

• low use of accurate deterministic propagation methods;

• lack of accurate databases (inputs) for them.

ICEST 2006 7

Activities related to propagation …

Some of the well known deterministic methods have been applied to solve problems arising in antennas design and propagation modeling, among them:

• moment methods, physical optics and modal expansion;

• differential equation methods (FDTD and Parabolic Equation (PE));

• ray methods (tracing/launching and Gaussian beams).

ICEST 2006 8

Activities related to propagation …Ray tracing

The most appropriate physical-deterministic models for radio propagation, at least in urban areas, are ray tracing (RT) models. RT models use the theory of geometrical optics to treat reflection and transmission on plane surfaces and diffraction on rectilinear edges.

Ray tracing provides several advantages over traditional prediction methods:• accurate site-specific field strength prediction; • possibility to incorporate 3D antenna patterns; • possibilities to obtain wide-band characteristics such as DoA and multipath

time delay.

The ray tracing based prediction techniques have some weaknesses: they are unreliable under specific tropospheric conditions (ducting), suffer difficulties when transiting from one type of region/cell (say, rural) to other (urban). Some of these difficulties could be overcome using even more complicated differential equation based methods as the PE method.

ICEST 2006 9

Advantage of accurate radio coverage prediction: Figs. 1 and 2 taken from COST TD(01)041, M. Coinchon, A.-P. Salovaara, J.-F., Wagen, “The impact of radio propagation predictions on urban UMTS planning”

Fig. 1 Signal strength from empirical propagation predictions: COST231-Hata model.

Fig. 2 Signal strength with ray tracing propagation prediction.

ICEST 2006 10

Channel characterization

COST 273 dealt with “traditional” topics characterizing the variability of power received through the mobile radio channel such as:

• path loss, its distance dependence and small- and large-scale fluctuations;

• temporal and angular dispersion;

• fading prediction techniques;

• experimental channel characterization techniques;

• statistical processing of measurements.

ICEST 2006 11

MIMO channel

( )

( ) ( ) ( )( ) ( ) ( )

( ) ( ) ( )

=

τττ

ττττττ

τ

, ... , ,...

, ... , ,, ... , ,

,

21

22221

11211

ththth

thththththth

tH

nmnn

m

m

Schematic illustration of a MIMO system with multiple transmit and receive antennas:

A linear, time-variant MIMO channel is represented by an n × m channel matrix:

( ) ( ) ( ) ( ) ( ) ϕφτττϕφϕφτττ φ ϕ

dddfGGtrrhth ijij ′′−′= ∫ ∫ ∫

′RxTxRxTx ,,,,,, rr

with double directional impulse response including antenna pattern (GTx, GRx) and pulse shaping (f):

Here τ, Φ, φ denote the excess delay, direction of departure (DoD) and direction of arrival (DoA).

ICEST 2006 12

Fig. 4 Application of the COST 259 directional channel model.Fig. 4 taken from: M. Steinbauer, A. Molisch, P. Mogensen et al., “Directional channel modeling in COST259 SWG 2.1”, in: "Millenium Conference on Antennas & Propagation (AP2000)", Davos, Switzerland (2000), Paper ID p0062.

COST

273

MIMO

channel model

ICEST 2006 13

COST 273 MIMO channel model

The above algorithm is based on Macrocell radio environments as defined in COST 259 and used in 273:• GTU: Generalized Typical Urban• GBU: Generalized Bad Urban• GRA: Generalized Rural Area• GHT: Generalized Hilly Terra

Definitions of the parameters describing a radio environment:• External parameters: parameters that characterize a radio environment, and that stay

fixed for the whole duration of a simulation (Examples: carrier frequency, building height, BS antenna height,…);

• Global parameters: sets of probability density functions and/or statistical momentscharacterizing a specific environment (e.g., the number of scatterers is characterized by a Poisson distribution). (The determination of the global parameters is partly geometric, and partly stochastic.) The randomly generated realizations of the global parameters are called local parameters and describe the instantaneous channel behavior.

Further information may be found in http://www.lx.it.pt/cost259/

ICEST 2006 14

COST 273 MIMO channel model

Improvement of COST 273 over 259:• the chosen parameters have been updated, based on new

available measurement campaigns;

• the modeling of the distribution of DoAs and DoDs is different, compared to the COST 259 model: one cluster is split up into two representations of itself: one that representsthe cluster as seen by the BS and one as it is seen by the mobile terminal. The two cluster representations are linked via a stochastic cluster link delay, which is the same for all scatterers inside a cluster. The cluster link delay ensures realistic path delays as, for example, derived from measurement campaigns.

ICEST 2006 15

COST 273 MIMO channel model - key features not included in present models

Physical and geometry-based models up to now do not reproduce keyhole effects. (A theoretical analysis revealed that for rank-one MIMO channel matrices the channel capacity is quite low, i.e., comparable to the capacity of single-antenna systems. Such channels have been termed “keyhole channels.”)

Diffuse Multipath Components: geometry-based approaches model the radio channel via the superposition of a finite numberof specular propagation paths that are typically characterized by their temporal and spatial statistics (these statistics usually are derived from channel measurements).

Much more conclusive measurements will be needed to incorporate time-variance into MIMO channel models in a realistic manner.

ICEST 2006 16

Reference scenarios

In general: scenario consistent set of parameters.

Goal: definition of common reference scenarios to be used in the assessment/comparison of different Radio Network Planning techniquesand Radio Resource Management strategies.

COST 273 introduced the Spatial Propagation Scenario as a set of parameters, defining the spatial and multiuser situation and the environment, with direct consequences on the propagation channelproperties.

Within COST 273 it is agreed that two types of scenario elements will be provided:• synthetic scenarios, based on simple and regular geometrical lay-outs and

simplified models, which make easy the interpretation of the results;• real-world based scenarios, where some data is taken from the real world, thus

making their use more complex but providing the possibility to test radio network algorithms under more realistic conditions.

• The classification of scenarios still needs to be motivated(MORANS).

ICEST 2006 17

References and follow on

[1] http://www.cost.esf.org/[2] Final report. http://www.lx.it.pt/cost273.

[3] L. M. Correia (Ed.), Mobile Broadband Multimedia Networks (Techniques, Models and Tools for 4G), Elsevier, 2006, 600 p.[4] Memorandum of understanding and Technical Annex, http://www.lx.it.pt/cost273. [5] M. Coinchon, A.-P. Salovaara, J.-F., Wagen, “The impact of radio propagation predictions on urban UMTS planning”, COST TD(01)041, http://www.lx.it.pt/cost273.[6] WaveSight. http://www.wavecall.com[7] I. Sirkova, “Overview of COST 273 Part II: Parabolic equation method application”, XLIICEST, Sofia, Bulgaria, 2006. [8] J.-M. Conrat, P. Pajusco, “A Versatile Propagation Channel Simulator for MIMO Link Level Simulation”, COST 273 TD(03)120, http://www.lx.it.pt/cost273. [9] H. Hofstetter, G. Steinbock, “A Geometry based Stochastic Channel Model for MIMO Systems”, ITG Workshop on Smart Antennas, Munich, Germany, March 2004.

COSTxxx: “Pervasive Mobile and Ambient Wireless Communications”.

Thank you for the attention!