Wireless Link Using OFDM Modulation

8/10/2019 Wireless Link Using OFDM Modulation

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Wireless Link using OFDM Modulation:Performance Prediction, Modeling

and ImplementationAdrian Bohdanowicz, Chris van den Bos, Maarten Ditzel,

Wouter A. Serdijn, Gerard J.M. Janssen, Ed F.A. Deprettere

Delft University of TechnologyFaculty of Information Technology and SystemsMekelweg 4, 2628 CD Delft, The Netherlands

E-mail: [email protected]

Abstract The Ubiquitous Communications program(UbiCom) at Delft University of Technology aims at the real-ization of a wireless communication system for the transferof audiovisual data, meant to provide augmented reality tomobile users. In this paper, the design and simulation of a high-speed wireless data link for the UbiCom program ispresented. The design (strawman prototype) uses an infra-red link for data transmission, whereas the simulationmodelsimulates a 17 GHz radio link.

The main difculty in the design is the fading multipathcommunication channel, which makes high data-rate com-munication hard to achieve with conventional single-carriermodulation schemes. By using orthogonal frequency divi-sion modulation (OFDM) as modulation scheme, multipatheffects have less inuence. In OFDM, which is a multi-carrier modulation scheme, many low bit-rate channels aremultiplexed in the frequency domain. The data rate per sub-carrier is chosen such that inter symbol interference (ISI) isno longer a problem.

The OFDM modulationis used in the strawman prototypeas well as in the simulation. For the design of the strawmanprototype, a custom infrared transmitter and receiver havebeen designed. For the simulation, a model of the physicalchannel is used.

It is expected that OFDM is capable of using a infra-redchannel efciently. In that case, a high bit-rate link is feasi-ble. It is argued that a Rician channel model is appropriatefor the simulation of the 17 GHz radio link, however, furthermeasurements are necessary. The results are a suitable sim-ulation of the radio link and a design for an infrared link,which will be implemented in hardware and demonstrated.

Keywords orthogonal frequency division multiplexing,OFDM, multi carrier modulation, radio channel model-ing, multipath fading, frequency selective fading, infra-redtransceiver, infra-red link, capacity estimation

The authors are members of the Ubiquitous Communications pro-

gram

I. INTRODUCTION

The Ubiquitous Communications program (UbiCom) isa multi-disciplinary research program at Delft Universityof Technology. The goal is to arrive at a system for wire-less visual communications, meant for augmented real-ity. The Ubiquitous Communications program consists of three projects: Base station and personal transceiver (P1), Visual information processing and application (P2), and System and application specication, emulation and

evaluation (P3).Within the program many challenging research topics

are covered. Key issues of the program include: low power design at all levels of the system i.e. at the

device, circuit, system and application level wearable and distributed computing quality of service management in a rapidly changing en-

vironment high performance computing due to perceptual con-

straints of augmented reality multi-level design space exploration and performance

analysis high quality imaging by means of a retinal scanning

display combined with an liquid crystal display for itsblocking capabilities

high performance image processing for identication of real world objectsWireless visual communication demands a mobile high

bit-rate communication system. This topic of the Ubiq-uitous Communications program is covered by the P1project.

The aim of the P1 project is to design a fourth gener-ation communication system, suitable for wireless visualcommunications. The eventual bit-rate to be attained is

155 Mbit/s. A radio link at 17 GHz is envisioned for out-

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44 Adrian Bohdanowicz et al.

door applications. This link may also be used for indoorapplications or alternatively, be replaced by an infra-redlink. The focus of the P1 project lies at:

Characterization and modeling of the wireless broad-band multipath fading channel

Suitable modulation and multiple access techniques for

high data-rate wireless communications Design techniques for high-frequency radio communi-

cation systems

As the UbiCom system is targeting the 17 GHz wirelessindoor and outdoor environment, the 17 GHz channel hasto be characterized and modeled thoroughly. The outdoorchannel is a hostile, multipath environment where due torefraction, reection and scattering the transmitted signalreaches the receiver via many different paths. Each pathsignal is received with a different amplitude attenuation,

phase shift and time delay. Multipath reception causes am-plitude uctuations in the frequency domain at the receiverantenna. This phenomenon is known as a frequency selec-tive fading channel.

The difference in the arrival times of the paths also causeinter symbol interference, which seriously degrades theperformance of wireless conventional single carrier com-munication systems at high bit-rates. The changes in thepropagation conditions due to moving objects (e.g. vehi-cles) in the vicinity of the receiver or the transmitter alsodegrades the performance. Furthermore, random effects

such as noise and co-channel interference cause an evenworse reception of the transmitted signal.

To conquer the effects of frequency selective fading inhigh data-rate wireless communications OFDM is chosento be the modulation technique for the UbiCom system.OFDM is a promising technique for the transmission of high bit-rates in parallel over a number of sub-carriers,thus effectively increasing the symbol period. In this way,it can tolerate much larger delay spreads in the channel.Hence, a sophisticated equalization unit as needed in sin-gle carrier systems becomes obsolete.

In section II, the strawman prototype and the simulationmodel are discussed. First, the principle of OFDM is ex-plained. Then the infra-red link capacity is evaluated todetermine the maximum bit-rate that is theoretically pos-sible. Finally, the radio channel modeling is discussed.

In section III, the implementation of the strawman pro-totype is discussed. It is explained how the OFDM mod-ulator and demodulator are implemented. Then the imple-mentation of the infra-red receiver and transmitter is de-scribed.

Finally in section IV, conclusions are presented.

0 0 0 0 00 0 0 0 00 0 0 0 00 0 0 0 00 0 0 0 00 0 0 0 01111111111111111111111111111110 0 0 00 0 0 00 0 0 00 0 0 00 0 0 00 0 0 0111111111111111111111111OFDM symbolcyclic prefix

time

Fig. 1. OFDM signal with cyclically extended guard interval

II . S TRAWMAN PROTOTYPE AND SIMULATION MODEL

The Ubiquitous Communications program plans the re-alization of a strawman prototype of the whole system inDecember 1998. Parallel to the realization a simulationmodel is implemented as well.

The purpose of the strawman prototype is twofold: tosupply a test environment, which can easily be extendedor modied and to serve as a demonstrator towards peoplewho are not directly involved in the program. From thetest environment valuable information can be obtained forthe design of the nal UbiCom system.

The purpose of the simulation model is to do perfor-mance analysis at each level of the system and of the sys-tem as a whole.

As the modulation scheme of the nal UbiCom systemis chosen to be OFDM, the prototype will also apply thisscheme. Initially infra-red light is chosen as the infor-mation carrier. Already at an early stage this choice willgive valuable information for the design of the nal indoorcommunication system, in which infra-red is an option.

A. Orthogonal frequency division multiplexing

In a conventional single carrier system, data symbolsare transmitted sequentially. In high data-rate communi-cations the symbol period becomes smaller than the delayspread of the channel and inter symbol interference oc-curs. In multi-carrier systems a number of data symbolsare transmitted at different sub-carriers in parallel thus in-creasing the symbol length.

Another advantage of transmitting the data symbols in

parallel is that the complete frequency band available isdivided into many narrow sub-bands. To increase thebandwidth efciency, an orthogonal multi-carrier schemeis used, in which the sub-bands are overlapping. Everysub-band only covers a small part of the total availablefrequency band and as a consequence channel equaliza-tion becomes much simpler than in a single carrier system.Also burst errors caused by fading do not distort severaladjacent symbols severely, but only distort many symbolsslightly.

To obtain orthogonality between the sub-carriers the

data-symbols are mapped on the sub-carriers using an in-

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Wireless Link using OFDM Modulation: Performance Prediction, Modeling and Implementation 45

symbolmapping

serialto

parallel

parallelto

serial

inversediscretefourier

transform

add cyclic prefix

Fig. 2. OFDM modulation

timingrecovery

inversesymbol

mapping

serialto

parallelparallel

toserial

discretefourier

transform

remove cyclic prefix

Fig. 3. OFDM demodulation

verse discrete Fourier transform (IDFT). To reduce ISIthe last part of the OFDM symbol is copied and put asa preamble, which serves as a cyclically extended guardinterval, which is called a cyclic prex (see gure 1).

The use of a cyclic prex instead of a plain guard inter-val, simplies the channel equalization in the demodulator.Also it is advantageous to maintain carrier synchronizationin the receiver [1].

OFDM demodulation consists of three steps: locate the starting point of an OFDM symbol, separate all sub-carriers by applying the discrete Fourier

transform (DFT), and map the symbols into bits.The complete modulation and demodulation schemes aredepicted in gures 2 and 3 respectively.

For evaluation purposes, both schemes are simulated us-ing the Ptolemy simulation environment [2]. A simpliedmodel of the multipath channel is incorporated in the sim-ulations.

B. Infra-red link capacity estimation

The infra-red link capacity (the maximum error-lessbit-rate) is given by Shannons formula:

C = B log2 1 + S N

where S is the total signal power, B is the bandwidth, andN is the noise power. The ultimate link will exhibit mul-tipath fading which necessitates the lowering of the signalbandwidth with respect to the single-path link. Hence, theperformance of a single path LOS channel gives an upper

bound.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

-1.5 -1 -0.5 0 0.5 1 1.5

r e

l a t i

v e

i n

t e n s

i t y

angle in radians

cos(x)

Fig. 4. Lambertian pattern

In case of a Lambertian radiation pattern (see gure 4),the signal light power at the receiver is given by [3]

P rec = P s

2Arec

(r )2 cos()

where P s is the transmitted power, r is the distance be-tween receiver and transmitter, is the angle between thenormal to the transmitter and the beam, and A rec is the ef-fective infra-red detector area. If the detectors responsive-ness is given by R (in A/W ), the resulting signal currentfrom the receiver photodiode is

is = RP s2

Arec(r )2

cos()

and the received signal power is proportional to:

i2s = P 2s R2 Arec

2(r )2 cos()

2

Now a noise current is generated by incoming ambientlight:

i2n = 2qRP amb B = 2qRE amb Arec B

where q = 1 .60 10 19 C and E amb is the irradiance of the ambient light on the receiver photodiode. Thus, the

maximally attainable signal to noise ratio (SNR) is givenby

SNR = P 2s R8qE amb B

Arec cos2 ()(r )4

in case of a receiver amplier noise gure of 0dB, whichcorresponds to a noiseless amplier.

The capacity of an additive, white Gaussian noise(AWGN) communication channel is given by [4]

C = B log2

1 + S

N 0B

B S

N 0 ln(2)bits/s

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where S is the signal power and N 0 is the noise spectraldensity. The capacity of the channel approaches a maxi-mum limit value when for a given S N 0 the bandwidth goesto innity. Thus, if the available channel bandwidth is un-limited, the necessary SNR to attain a given capacity ap-proaches a lower limit if B . For an infra-red channel

the available bandwidth is not restricted by governmentalregulations, so that the necessary signal level can be mini-mized by maximizing the bandwidth.

Example calculationFor innite bandwidth, the capacity is given by

C B = P 2s R

8qE amb ln(2)Arec cos2()

(r )4

Now, assume the infra-red communication link has thefollowing parameters:

P s = 100 mW R = 0 .5 A/W (typical value) E amb = 10 W/m 2 (no optical ltering, indoor environ-

ment) = 45 o r = 3 m Arec = 100 mm 2

then C 3.6 Mbit/s for B . For r = 2 m, C maxis already 18 Mbit/s. These gures are in accordance withthe experimentally found channel capacitance in [5].

If the bandwidth is restricted to for example 10 MHz,

as is the target for the rst strawman prototype, the ca-pacities for r = 3 m and r = 2 m reduce to 3.2 Mbit/sand 16 Mbit/s , respectively. It is seen that the actual re-duction is moderate, only 11 percent. It should be noted,though, that the actual maximally attainable bit-rates arelower, as the capacity is only attainable by using the idealtransmission scheme. OFDM will introduce an additionalperformance loss, but it is expected to be small.

C. Modeling of the radio channel

For the purpose of simulations, characterization and

modeling of the radio channel is needed. The linear l-ter approach based on the discrete multipath model is usedto characterize the behavior of the radio channel. In thisapproach, its impulse response function gives the full char-acterization of the radio channel. The complex basebandimpulse response h(t) is given by:

h(t) =L

k =0

k (t k )e j k

where k , k and k are the amplitude, phase and time

delay of the kth path and L is the number of multipath

components. The major difculty of modeling the radiochannel impulse response is that in event of motion eachparameter becomes random and time variant. If the chan-nel is assumed to be constant for a short period, this equa-tion can be applied for each point in a three dimensionalspace (for example see gure 5).

0

2

4

6

8

10 0

1

2

3

4

5

0

10

20

30

40

Distance [cm]

Time delay [ns]

P o w e r

[ d B ]

Fig. 5. Power delay prole of adjacent impulse responses

To simulate the variation of the channel model, the char-acteristic parameters are obtained from measurements andimplemented in the model. In this case the channel is as-sumed to have a dominant, line-of-sight path. Then theinstantaneously received signal power can be described by

the Rice distribution. The one-value characterization of this property of the channel is the Rice K-factor dened asthe ratio of the power of the dominant path to the averagepower of the scattered paths:

K = P dominant pathP reected paths

The small-scale fading effect is implemented in the chan-nel model by variations of the Rician K-factor, which,based on the measurements, is assumed to follow a Gaus-sian [6] distribution as depicted in gure 6.

The time dispersive nature of the channel is representedby a root mean square (rms) of the delay spread, givenby the square root of the second central moment of thepower delay prole (PDP), where the PDP is given by|h(t)|2 . Caused by the multipath environment, the rms de-lay spread species the maximum obtainable rate of sym-bols that can be transmitted without serious distortion overthe channel. As far as obstacles are located with com-plete randomness, a standard Poisson process describes thetime sequence of the components. The envelope of the im-pulse response is assumed to be exponential [7], which is

in agreement with measurements.

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10 5 0 5 10 150

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Kfactor [dB]

P r o

b ( K < a b s c

i s s a

)

simulationtheory

Fig. 6. Cumulative distribution function of Rician K-factor

III. S TRAWMAN PROTOTYPE IMPLEMENTATIONISSUES

In the strawman prototype, low power consumption isnot an issue. There are two reasons for this. First, theprototype must be available soon, so time is limited. Sec-ond, the strawman prototype must provide an environmentfor experiments. For the P1 project, the focus is on theevaluation of the OFDM system performance. Without aconstraint on the power consumption, an indication can beobtained on how good OFDM can be. By applying the

power constraint on later prototypes, it becomes possibleto see how far away that prototype performance is from theoptimum.

A. OFDM (de)modulation

As the available time is limited for the implementationof the strawman prototype, a straightforward implementa-tion of OFDM is chosen. The selected scheme uses theproperties of the cyclic prex, which effectively reducesISI. The main problems of this scheme are related to syn-chronization, i.e.: frame synchronization : recovery of the timing of a single

OFDM frame, i.e. an OFDM symbol preceded by thecyclic prex;

carrier synchronization : loss of carrier synchronizationcauses the loss of orthogonality of the sub-carriers andthus degrades the performance of the system [8].

Additional problems are related to channel estimation andequalization.

Frame synchronizationThe frame synchronization is based on the principle that

the cyclic prex contains a copy of the last part of the

,

, @

@

,

, @

@

A

A

A

A

A

A

A

A

-

? ?

6

- - - - FFT

I

f f eq

M 1

M y

s

g

Fig. 7. Channel estimation and equalization

OFDM symbol. A simplied least square error algorithmis applied to estimate the start of an OFDM frame [9].

The algorithm calculates the power of the differencesbetween the input samples r (n) spaced N samples apart,where N is the number of sub-carriers. The results arethen summed over an interval of length S . The minimumof this squared error gives an estimate of the starting timeof the frame:

() =S

i=0

|r ( + i) r ( + i + N )|2

min=0 ..m

{()}

in which m = N + L S with L the number of samplesin the cyclic prex.

Channel estimation and equalizationThe channel estimation algorithm uses a single trainingframe to estimate the channel characteristics. This esti-

mate g(n) is continuously updated using the received data(see gure 7, species a unit delay):

f eq (n) = f (n) g(n)

g(n) = s(n 1) I f (n 1)

s(n) = M ( y(n))

y(n) = M 1 f eq (n)

with

I

x0x1...

xn

=

1x 01

x 1...1

x n

in which f (n) is the result of the fast Fourier transform(FFT), f eq (n) is the equalized FFT result, g(n ) is the in-verse channel estimate, s(n) is an estimation of the re-ceived symbols, y(n) is the decoded data stream and Mand M 1 stand for the symbol and inverse symbol map-

ping respectively.

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The initial estimation of the channel g(0) is the all onesvector. The initial values of the estimated symbols s(0) arethe training symbols from the training frame S training :

g(0) =

11...1

s(0) = S training

ImplementationThe Fourier transforms are the most computational in-tensive parts of an OFDM modulator and demodulator.For implementing the Fourier transforms required by theOFDM link several options are available: design and implement a dedicated IC:

Since the demonstrator is to be completed in December1998 there is too little time to design and implement adedicated IC for the FFTs as the development of a com-plete chip takes much longer. The resulting hardwarecannot be modied at all.

buy a dedicated IC (off the shelf):Several dedicated ICs are available for FFTs and evencomplete OFDM modulators. The advantage of this ap-proach is that it is possible to implement a completeOFDM system before December 1998.However, using an existing design will not give much

insight in the problems encountered when designing andimplementing an OFDM system.

use programmable devices as complex programmablelogic devices (CPLDs) or eld programmable gate ar-rays (FPGAs):It is possible to use programmable devices like a CPLDor an FPGA for the modulator and the demodulator.Then the hardware has to be designed using a hard-ware description language such as VHDL, which is atime consuming extra step in the trajectory. The result-ing hardware is less exible and more difcult to modify

than for instance the software for a digital signal proces-sor.

use a general purpose processor:If the processor has enough processing power it is pos-sible to implement the FFTs and also the entire OFDM(de)modulator completely in software.

use a dedicated digital signal processor (DSP):Several digital signal processors are available to imple-ment the Fourier transforms and the symbol mapping.Complete boards and development tools are available,including a C-compiler with additional optimized run-

time libraries (including FFTs).

Fig. 8. Overview of the infra-red link system

As the rst two options do not t the requirementsof a demonstrator and the third option has some draw-backs, only the last two are suited for the demonstrator.In both options the OFDM (de)modulation is implementedby writing software for a processor. If a programming lan-guage is chosen that is supported by both processors (forinstance C) the complexity of the two options is practicallythe same.

Implementing the modulator and demodulator in soft-ware has several advantages: exible (software is easily modied in contrast with

hardware); simple hence robust; low learning curve (no new techniques have to be

learned).Therefore the OFDM modulation and demodulation is im-plemented in software on a dedicated digital signal pro-cessor. This processor is mounted on a standard PC-card(ISA/PCI). For the prototype the evaluation boards of the

Texas Instruments C6000 xed point processor are used.

B. Infra-red transmitter and receiver

For the generation of infra-red light, a choice must bemade from two devices. These are the laser diode and theLight Emitting Diode (LED).

The laser diode is a device whose light output powercan be modulated very fast, so high data-rate transmissionis possible. Further, the power efciency of a laser diodeis higher than that of a LED. However, a laser diode pro-duces a very narrow beam of light with a high intensity. If

this beam strikes the human eye directly, the retina may be

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0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01111111111111111111111111111111111ceiling

Fig. 9. Laser diode and diffuser

damaged quite quickly. Therefore, the beam width shouldbe enlarged by some means. Some options are diffraction(lenses or roughly-surfaced transparent materials), and re-ection (curved mirrors or roughly-surfaced white materi-als). A reector of rough, white material is simple, cheap

and safe [5]; a layer of plaster would do the job [10] (seegure 9 for a possible setup). Other disadvantages of laserdiodes are the high price and the poor availability.

Light Emitting Diodes cannot be modulated as fast aslaser diodes. The power efciency is also lower, typically10% or less [3]. However, the light is spread over a wideangle, so the danger of permanently damaging the retinais small. They are cheap and can be bought within a week typically. Therefore, IR LEDs will be used as light emit-ters in the rst UbiCom demonstrator.

For the detection of infra-red light, there are two devices

to be considered. One is the PIN diode, the other one is theAvalanche Photo Diode (APD). Although the latter maybe useful in case of very weak received signals, it has twomajor disadvantages: it is expensive and it usually requiresvery high voltages (up to 200V) for proper operation. Thismakes the use of PIN diodes unavoidable.

To reduce the inuence of ambient light, optical lter-ing may be used. The noise current, generated by the PINphotodiode, is caused by the ambient light. As the inci-dent ambient light has a broad frequency range, its inu-ence can be reduced by the application of lters which only

transmit light with the same wavelength as the light emit-ting diode.

There are two main classes of lters: absorption ltersand interference lters [3].

Absorption lters are made of materials that absorblight with a wavelength shorter than some specic value.These lters have a broad bandwidth (several hundreds of nanometers). They can only moderately attenuate lightwith an undesired wavelength. However, they are cheapand transmit light no matter what the angle of incidence is.

Interference lters are built of many thin layers of trans-

parent material (dielectric slabs). In and between these

layers, reection and transmission of light occurs. Onlyat very particular frequencies, constructive interference of light occurs in all layers, so that light is transmitted. Theselters are very narrow-band (tens of nanometers) and cantherefore greatly reduce the inuence of ambient light.However, they are directionally sensitive, so that a set of

photodiodes would be necessary, each pointing in a dif-ferent direction, to cover a wide range. Further, they arevery expensive and hard to obtain. Therefore only absorp-tion lters will be used in the rst demonstrator. It shouldbe noted however that the use of interference based lterscould greatly enhance the overall system performance.

The infra-red transmitter consists of an infra-red emitter(a light emitting diode) and an amplier to drive the lightemitting diode. The diode transfer is very linear, so themain source of distortion in the system is the driver ampli-er.

The infra-red receiver consists of a PIN photodiode anda current-to-voltage converter. As the signal photo cur-rent is very small (typically < 1 A) and the output voltagemust be large ( > 1 V) the overall gain is large. Therefore,the infra-red receiver amplier consists of two stages: alow-noise preamplier, and a second amplier to boost thesignal.

IV. C ONCLUSIONS

In this paper, the designs of a wireless infra-red link,and a simulation framework are presented, for evaluation

of the OFDM transmission link in the Ubiquitous Commu-nication system.

To ensure good modulation performance, proper choiceof OFDM parameters (e.g. cyclic prex) is needed.

It was found that the wireless infra-red link was suit-able for high bit-rate transmission (up to 18Mbit/s). Thethe maximum channel capacity, given the bandwidth of 10MHz, was approximated within 11 percent (3.2 Mbit/svs. 3.6 Mbit/s). This means that the OFDM modulationscheme may be capable of attaining a signaling speed thatis close to the theoretical maximum. The ambient light

was shown to be the major limiting factor on the maxi-mum bit-rate. By using interference-based optical lteringand using multiple photodetectors, the bit-rate could be in-creased further.

To come up with useful simulation results, a channelmodel is needed. In this paper, a Rician channel model isused. The important characteristic parameters are incor-porated in the presented model. As the channel model be-havior depends on the characteristic parameters, the propervalue of each must be determined. In order to obtain thesevalues, further measurements on the target 17 GHz outdoor

environment should be conducted.

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R EFERENCES

[1] William Y. Zou, Yiyan Wu, COFDM: an overview, IEEE trans-actions on broadcasting , vol. 41, no. 1, pp.18, March 1995.

[2] J.T. Buck et al, The Almagest, Vol. 1 - Ptolemy 0.7 Users Manual ,University of California at Berkeley, 1997.

[3] R. Otte, Low-power wireless optical transmission , Ph.D. thesis,Delft University of Technology, The Netherlands, 1998.

[4] J.G. Proakis, Digital Communications, 3rd ed . New York:McGraw-Hill 1995[5] D.C. Lee, J.M. Kahn, Experimental 25Mb/s Infrared Link Us-

ing 4-PPM with Scalar Decision-Feedback Equalization, ICC98 conference record , 1998.

[6] G.J.M. Janssen, Robust receiver techniques for interference-limited radio channels , PhD Thesis, Delft University Press, 1998.

[7] H. Hashemi, Impulse Response Modeling of Indoor Radio Propa-gation Channels, IEEE J. Selected Areas on Communication , vol.11, no. 7, pp. 967978, September 1993.

[8] Ferdinand Classen, Heinrich Meyr. Frequency synchronizationalgorithms for OFDM systems suitable for communication overfrequency selective fading channels, IEEE transactions on ve-hicular technology , vol. 3, pp. 16551659, 1994.

[9] Michael Speth, Ferdinand Classen, Heinrich Meyr. Frame syn-chronization algorithms of OFDM systems in frequency selec-tive fading channels, IEEE transactions on vehicular technology ,vol. 3, pp. 18071811, 1997.

[10] C.R. Lomba a.o., Experimental characterization and modellingof the reection of infrared signals on indoor surfaces, IEE proc.optoelectronics , vol. 145, pp.191197, June 1998.

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Wireless Link Using OFDM Modulation