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Tiêu đề Mimo/Smart Antenna Development Platform
Tác giả Florian Kaltenberger, Gerhard Humer, Georg Pfeiffer
Trường học ARC Seibersdorf Research GmbH
Chuyên ngành MIMO/Smart Antenna Development
Thể loại Bài báo
Năm xuất bản 2004
Thành phố Vienna
Định dạng
Số trang 5
Dung lượng 200,74 KB

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MIMO_Smart Antenna Development

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MIMO/Smart Antenna Development Platform

Florian Kaltenberger, Gerhard Humer, Georg Pfeiffer

ARC Seibersdorf research GmbH Tech Gate Vienna, A-1220 Vienna, Austria, Donau-City-Straße 1, 4thFloor

phone: +43(0)50550/4149, fax: +43(0)50550/4150 email: <firstname.lastname>@arcs.ac.at, web: www.arcs.ac.at/IT/ITS

Abstract— Smart Antennas (SA) and Multiple

In-put Multiple OutIn-put (MIMO) systems are considered

as one of the key technologies for the third generation

mobile communication systems and are now even being

included in the UMTS standard [1] With those

tech-nologies it is possible to improve the signal-to-noise

ra-tio at the receiver and increase capacity in mobile radio

systems.

To test and evaluate new algorithms for those

sys-tems a MIMO/SA development platform has been

de-veloped It comprises a MIMO real-time channel

ulator and a receiver unit The real-time channel

sim-ulator uses a geometry based stochastic channel model

(GSCM) proposed by COST 259 [2] to simulate MIMO

channels accurately and in real-time The MIMO/SA

receiver allows rapid prototyping and real-time

evalu-ation of MIMO/SA algorithms.

The hardware of the development platform is made

up of an expandable architecture of up to ten parallel

processing boards The DSP-boards combine the

versa-tility of a DSP with the raw power of a FPGA and offer

a performance of up to 12000 MIPS Together with an

analog I/O board for RF and IF signals, the DSP-board

is ideally suited for software defined radios (SDR).

Index Terms— Smart Antennas, MIMO, Channel

Modelling, Real-time Simulation, Software Defined

Ra-dio

Smart antennas use antenna arrays to reject

inter-ference and to improve system capacity in mobile

communication systems Multiplying the signals

re-ceived at the different antenna elements with complex

weights ω and summing them up (combining) results

in the characteristic beamforming pattern By using

adaptive algorithms to compute the weighting factors

in the direction of the desired signal and nulls out the

interferer signals For a good overview of smart

an-tennas see [3]

MIMO Systems employ antenna arrays on the

sender as well as on the receiver side They can

in-crease the capacity of mobile communication systems

by using spatial multiplexing of signals If the number

of antennas is the same on the sender and the receiver side, it can be shown that the capacity increases with the number of antennas [4]

To simulate smart antennas as well as MIMO sys-tems in real-time, a MIMO/SA development platform has been developed The whole system is formed by

an expandable architecture of eight parallel process-ing boards (DSP-boards) for channel simulation, and

by one or two receiver boards, which operate with up

to eight antenna signals The development platform is subject of section III

The DSP-boards were designed especially for the use in software defined radios (HW/SW co-design)

the raw power of a FPGA The DSP is capable of handling complex algorithms at high speeds while the FPGA can accelerate many tasks using parallel computations and handle fast external data I/O eas-ily Each DSP-board can be equipped with its own analog I/O-board with separate inputs for digital, ana-log, RF and IF signals and thus forming an ideal SDR transceiver A detailed description of the hardware architecture can be found in section II

The testing and evaluation of MIMO/SA algo-rithms requires a very accurate channel model The geometry based stochastic channel model (GSCM) proposed by COST 259 [2] for MIMO systems shows promising results when compared to real world mea-surements A brief description of the model and its implementation on the DSP-boards will be given in section IV-A

Finally, in section IV-B the implemented receiver algorithms and the optimized distribution of these al-gorithms to the hardware resources is explained This implementation can also be used as a framework for the rapid prototyping of new MIMO/SA algorithms

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II THEPROCESSINGBOARDS

At the heart of the MIMO/SA development

plat-form are the DSP-board and its analog I/O board

They will be described in the following sections

A The DSP Board

The DSP-board uses two main computational

com-ponents: A Texas Instruments TMS320C6416 DSP

(Digital Signal Processor) and a Xilinx Virtex2

XC2V2000 FPGA (Field Programmable Gate Array)

block diagram of the DSP-board can be found in

fig-ure 1

Xilinx Virtex 2

XC2V2000

DSP

TMS320C6416

(600 MHz)

dig Out or

LVDS

USB 1.1 Transceiver

Ethernet Transceiver

RS232 Transceiver

Motorola Coldfire MCF5272

16 MByte SDRAM

2 MByte Flash ROM

4 MByte

Flash ROM

32 Bit Memory Bus

Fig 1 Block diagram of the DSP-board

The DSP uses 4 MByte Flash-ROM to store its own

applications and the configuration files of the FPGA

In addition to its internal 1 MByte Cache/RAM it is

equipped with 32 MByte external RAM (expandable

to 512 MByte using a standard SO-DIMM) Clocked

at 600 MHz it is capable of executing up to 4800

MIPS and offers hardware-support for problems

com-monly found in signal processing, most notably a

Viterbi Decoder and a Turbo Decoder

The FGPA contains 2 million system gates and

56 dedicated 18-bit x 18-bit multipliers that provide

computing power roughly equivalent to 3200 MIPS

(measured using the UMTS channel simulator

pre-sented in section IV-A)

It also features a total of 624 I/O pins, that can be

configured to comply to different interface standards,

and can be used in pairs for LVDS (Low Voltage

Dif-ferential Signaling) at up to 400 Mbit/sec/pair, or as

general, high speed I/O pins Although the FPGA

is the centerpiece of the board design and many of

its I/O pins are used for internal purposes (data- and

address-busses to the DSP and CPU, various control

signals), it still offers enough freely usable pins to

implement six external LVDS links (usable as input

or output; compliant to the ChannelLink standard,

each using six LVDS pairs for data transmission and

one LVDS pair for synchronization, for up to 2400 Mbit/sec/link) Two of these links are implemented

as standard ChannelLink connectors and accessible at the front panel while the remaining four are linked to the 96 pin connector at the back panel, which also provides pins for synchronization, power supply, and detection of logical board position

It is worth noting that every LVDS channel can pro-vide its own clock that doesn’t need to be synchro-nized with any other LVDS clocks The FPGA con-tains eight clock managers, making it possible to re-ceive each LVDS channel with its own timing

In addition to the two chips dedicated to data pro-cessing a Motorola XCF5272VF66 ‘Coldfire’ CPU is available It is clocked at 66 MHz and provides sup-port for Fast Ethernet, USB 1.1 and RS232 and is thus used as a communication subsystem to exchange data with the controlling PC without burdening the com-putation components with the overhead and complex-ity of external interfaces The Coldfire is equipped with 2 MByte of Flash-ROM and 16 MByte of RAM Since the FPGA and the DSP do not run any op-erating system, any communication would have to

be hand coded by the application programmer The Coldfire on the other hand, runs a copy of µClinux, a slim edition of Linux, that has been trimmed down to fit the needs of embedded devices (low memory foot-print, low processing capacity, no MMU (Memory Management Unit)) Even though the entire µClinux

is just a few hundred KByte in size, it still retains its communication subsystem, so writing TCP/IP based applications for data exchange with external systems

is very convenient

Both the DSP and the Coldfire have their own, sep-arate Flash- and RAM-Memory It is not possible for the Coldfire to directly access the DSPs memory

or vice-versa Communication between the compo-nents takes place by means of a dual-ported RAM (DPRAM), that is implemented in the FPGA and that can be accessed via separate busses from the DSP and the Coldfire

The components are mounted on a 12-layer printed circuit board (PCB) Great care has been taken to en-sure proper shielding of high frequency signal and compatibility with relevant EMC (Electro Magnetic

layer is used after two signal layers

B The Analog I/O Boards

To make the DSP-board usable with a broad range

of signal sources and receivers, we also plan to equip

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each DSP-board with a analog I/O board for input and

3020 Digital Generator can be used as a transmitter,

the AEROFLEX PXI 3030 RF Digitizer as a receiver

and the AEROFLEX PXI 3010 RF Synthesizer as an

oscillator for both modules The AEROFLEX PXI

modules provide real time LDVS digital IQ or IF

out-put resp inout-put and are thus ideally suited for use with

the DSP-board

The signal generator provides a frequency range

from 250 MHz to 2.5 GHz and an output level range

of -120 to +5 dBm The digitizer provides a frequency

range from 300 MHz to 3 GHz, a digitized bandwidth

of 15 MHz and a 14 bit A/D-conversion with 61,44

MHz sampling rate

The hardware of the MIMO/SA development

plat-form is plat-formed by a real-time MIMO channel

simu-lator comprising eight DSP-boards, and by a receiver

unit comprising two DSP-boards and two extension

boards that can handle up to eight antenna signals

Both units can be integrated in one rack that also

pro-vides power supply and cooling

The development platform is controlled over Fast

Ethernet by a Graphical User Interface (GUI)

run-ning on a PC or laptop Input signals can either be

generated on the DSP-boards or they can be feed in

the DSP-boards directly Up to now, the development

platform only has in- and outputs for digital baseband

signals, but an extension to RF and IF signals is under

development as pointed out in section II-B Figure 2

shows a picture of the development platform

A MIMO Channel Simulator

In a n → m MIMO scenario, n · m DSP-boards are

needed One board is used for each channel,

comput-ing the signal distortion (effects of fadcomput-ing, phase shift,

multi- path propagation) for one sender-receiver pair

For the channel simulator, the two ChannelLink

connectors at the front side of the DSP-boards are

used for digital baseband input (BB-in) and output

(BB-out) respectively The DSP-boards are connected

to a backplane (via the 96 pin connector) that supplies

global synchronization signals and a LVDS daisy

chain (2400 MBit/sec) for board-to-board

communi-cation

Channels leading to the same output have to be

cal-culated by adjacent boards The output signals of

1 http://www.aeroflex.com

Fig 2 Development Platform

Fig 3 MIMO 2 → 4 scenario and the corresponding configu-ration of development platform.

each of board in this group are routed through the LVDS daisy chain of the backplane to the the last board of the group, where they are combined and out-put to the BB-out connector at the front side

In addition to the LVDS daisy chain, the backplane features two LVDS-channels (one input, one output) accessible at the rear side of the rack using standard ChannelLink connectors Those connections have to

be used, if the user wants to provide his own digital baseband input signals By connecting outputs and inputs at the rear side of the rack it is possible to con-figure different MIMO scenarios (8 → 1, 4 → 2, 2 →

4, 1 → 8 with eight boards)

The user input signals are replicated at the BB-out connectors at the rear side, so that the input signal can be looped through to all the boards that simulate

a channel originating at the same antenna So to con-figure a 4 → 2 MIMO scenario, for example, the in-and outputs at the rear side of the rack have to be con-nected like depicted in figure 3

Larger MIMO scenarios: The total system size

of the development platform is not limited by the

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capacity of a rack Larger systems can be built by

using stacks of up to eight racks, where up to 64

(8·8) DSP-boards form a uniform pool of computing

resources (with completely transparent rack-to-rack

boundaries) With those systems it is possible to

sim-ulate MIMO scenarios with up to eight transmit and

receive antennas (8 → 8)

It is worth to point out, that such a cluster of

64 DSP-boards provides a total peak performance of

0.75 TeraOP/sec and a total communication peak

per-formance of 450 GBit/sec

B Receiver Unit

For the receiver unit, the two DSP-boards are

com-plemented with two extension boards providing

ad-ditional LVDS input channel connectors at the rack’s

front Both the DSP-boards and the extension boards

are connected to the backplane The input signals

from the extension boards are directly routed to the

receiver board without any processing

The software consists of the implementation of the

channel model and the receiver At the moment only

the GSM standard is supported Extension of the

soft-ware for systems like EDGE, UMTS, W-LAN and

Bluetooth standards is currently under development

For the channel model in the MIMO/SA

develop-ment platform the geometry based stochastic

chan-nel model (GSCM) proposed by COST 259 [2] was

chosen, since only a geometrical channel model can

simulate MIMO scenarios realistically However, it is

also possible to implement other channel models or

even use channel sounder measurements for channel

simulation

Section IV-A outlines the principles of the GSCM

and its real-time implementation on the DSP-boards

[6] Section IV-B shows a framework how receiver

algorithms can be implemented on the development

platform

A MIMO Channel Simulator

According to COST 259, scatterers are arranged in

clusters, comprising a Near Cluster (NC) representing

the immediate Mobile Station (MS) surrounding, and

several Far Clusters (FC) Clusters are uniformly

dis-tributed within a radio cell as well as scatterers within

a cluster Assuming specular reflection at the

scatter-ers, raytracing is used to compute the multipath

com-ponents created by the scatterers (see Figure 4)

Near Cluster

Far Cluster

Far Scatterer

Near Scatterer Base

Station

Macro cell Mobile Station

Fig 4 Modelling of signal propagation for GSCM

The signal at the output of each channel simula-tor can be calculated as superposition of the weighted multipath components (MPC) A special FPGA mod-ule, called Channel Engine, performs the ‘core’ tasks

of the channel simulation (phase shifts and fading for each propagation path, summation of the partial re-sults) efficiently by using extensive parallelism Calculation of phase delays and fading factors as well as the position of the scatterers is done by the DSP The calculation is not carried out for each sym-bol (3.67µs for GSM and 260ns for UMTS), be-cause this would drastically exceed available com-puting power even of todays fastest processors As

a consequence, the calculation is split in a small scale update and a large scale update

The large scale update updates the positions of the scatterers according to the stochastic properties of the channel model and thus simulates long term fading Since those values are varying significantly only af-ter a MS movement of some wave lengths they are refreshed every 40 timeslots

The small scale update updates the phase delays and fading factors for all MPCs and thus corresponds

to the geometrical part of the channel model It oc-curs every timeslot, since those values are varying very fast even when the MS is moving only a frac-tion of a wavelength To simulate short term fading, linear interpolation between the computed values is performed

B MIMO/SA Receiver

Various algorithms for MIMO and smart antenna receivers have been proposed in literature See, for example [7] for a MIMO algorithm and [8] for a

Trang 5

smart antenna algorithm Most of the algorithms are

computationally expensive, since they include a lot of

matrix operations and filters The special

HW/SW-codesign of the DSP-board makes it ideally suited

for these kinds of algorithms The following

para-graphs outline how a MIMO/SA receiver can be

im-plemented on the DSP-board

The digitized baseband signals are feed in the

DSP-board over LVDS, where they are received by the

FPGA and stored in a buffer Optionally the FPGA

can also perform pre-processing like AGC (automatic

gain control) or complex derotation One FPGA can

handle up to six LVDS channels If more channels are

necessary a second DSP-board has to be employed

The DSP transfers the data from the FPGA’s buffer

via direct memory access (DMA) over the EMIF-B

memory interface in its local memory Then it

exe-cutes the MIMO/SA algorithms to calculate the

com-biner weights and the combined impulse response of

the channel The combining of the signals (complex

multiplication and addition) is also done in the DSP

Finally the DSP detects the data out of the combined

signal with the help of one of its powerful

coproces-sors (e.g the Viterbi coprocessor for GSM)

The detected data is then made available for the

CPU, which sends it to the PC over Fast Ethernet On

the other hand the CPU receives parameters and

con-trol commands from the PC and passes them to the

DSP

Due to the flexible design of the DSP-board the

de-velopment platform can also be used for a broad range

of other software defined radio applications In this

section, we will outline some of those concepts

Together with the HF-frontend the development

platform can also be used as a channel sounder

Therefore the external RAM of the DSP boards has

to be expanded to the maximum of 512MByte The

digitized baseband signals are received in the same

way as pointed out in section IV-B, but are stored in

the external RAM When the RAM is full, the

chan-nel sounder has to stop recording and transfer the data

over Gigabit Ethernet to a PC As a signal source the

PXI 3020 Digital Generator can be used

The communication subsystem and the Fast

Ether-net connections on the DSP-board makes it easy to

in-terconnect the DSP-boards to a cluster Such a cluster

could be used as a number cruncher for signal

pro-cessing or general purpose applications As already

pointed out at the end of section III-A, the aggregated

computing power of such a cluster of 64 DSP-boards

reaches 0.75 TeraOPS

We have presented a development platform for MIMO systems and smart antennas, which contains

a MIMO channel simulator and a MIMO/Smart An-tenna receiver unit This tool eases the design process for MIMO systems and smart antennas from the algo-rithm development to the end product

The hardware of the development platform is made

up of highly flexible and scalable DSP-boards, that combine the versatility of a DSP with the raw power

of a FPGA and offer a performance of up to 12000 MIPS Equipped with an analog I/O board the DSP-boards can also be used as an software defined radio (SDR) transceiver

Future plans include the development a Matlab/ Simulink interface for the development platform The interface makes it possible to develop MIMO/smart antenna algorithms in Matlab or Simulink and evalu-ate them with the MIMO channel simulator The en-tire process is fully transparent to the user who is not forced to change his accustomed workflow, but will enjoy significant speedups in the computation of his simulations

[1] H Chuang (Rapporteur), “Status report for work item to

Hawaii, Dec 2003 [Online] Available: www.3gpp.org

[2] Louis M Correia, Ed., Wireless Flexible Personalised

Com-munications, Wiley, 2001.

[3] W Sch¨uttengruber, A.F Molisch, and E Bonek, “Smart antennas for mobile communications,” Internet Tutorial,

mobile/research/

[4] G J Foschini and M J Gans, “On limits of wireless commu-nications in a fading environment when using multiple

anten-nas,” Wireless Personal Communications, vol 6, no 3, pp.

311–335, 1998.

[5] G Humer and G Pfeiffer, “Hardware platform for software

enabled radio and smart antennas,” in Colloquium on

DSPen-abledRadio, ISLI, Schottland, GB, Sept 2003.

[6] G Humer, R Kloibhofer, G Pfeiffer, and G Steinb¨ock,

“COST 259 channel model implementation for real-time

Prague, Sept 2003.

[7] P Wolniansky, G Foschini, G Golden, and R Valenzuela,

“V-BLAST: an architecture for realizing very high data rates

over the rich-scattering wireless channel,” in Proceedings

URSI International Symposium on Signals, Systems, and Electronics, IEEE, New York, NY, USA, 1998, pp 295–300.

[8] C.F Mecklenbr¨auker, R.R M¨uller, A.I P´erez-Neira, and

M Lenger, “On simplified space-time receiver structures for

GSM,” in Proc 4th European Personal Mobile

Communica-tions Conference (EPMCC), Wien, Feb 2001.

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