A Baseband Receiver for Optical OFDM Systems

Chen-Hung Peng, Kai-Ting Shr, Ming-Hung Lin, and Yuan-Hao Huang

Institute of Communications Engineering and Department of Electrical Engineering,

National Tsing-Hua University, Hsinchu, Taiwan, R.O.C.

Email: yhhuang@ee.nthu.edu.tw

Abstract—Orthogonal frequency division multiplexing(OFDM) technique has been widely adopted in wirelesscommunication systems. However, the study of OFDM techniquefor optical transmission system is still emerging in the researchfield. In this paper, we propose a baseband receiver architecturefor the optical OFDM system. The baseband receiver containsframe detection, carrier frequency offset (CFO) estimation andcompensation, channel estimation, and equalization. This paperalso proposes a fast Fourier transform (FFT) processor withhighly parallel architecture for the high-throughput requirementin the optical system. Finally, the FFT processor is designedand implemented using 90nm UMC CMOS technology. Themeasurement result shows that this chip achieves 2.67GS/sthroughput for the optical OFDM system.

I. INTRODUCTION

Recently, communication techniques are widely studied

and developed due to the growing demand for high-quality

and wide-band services. The popular technique of orthogonal

frequency division multiplexing (OFDM) has been very ma-

ture for wireless wideband communication systems. On the

other hand, in order to provide a higher spectrum efficiency

for the back-bone optical transmission, several studies [1]–

[5] have investigated the employment of OFDM technique

in the optical transmission system. Since OFDM technique

can efficiently combat the chromatic and polarization mode

dispersion in the fiber, the OFDM technique provides superior

spectral efficiency and transmission quality for the optical

transmission system. However, the realization of OFDM tech-

nique over optical fiber faces some difficulties. The main

issue is the requirement of very high throughput Fast Fourier

Transform(FFT), inverse fast Fourier transform (IFFT) pro-

cessor, and other circuits. Therefore, this paper investigates

architecture design of the OFDM receiver for the optical

system and presents an FFT processor that can support the

high-throughput requirement in the OFDM receiver.

The remainder of this paper is organized as follows. Section

II presents the systematic specification of the optical OFDM

system. Section III shows the architecture of the proposed

optical OFDM receiver. Section IV shows the simulation

results of the OFDM receiver and the implementation result of

the FFT processor. Finally, Section V summarizes this work.

II. OPTICAL OFDM SYSTEM

Fig. 1 depicts the experimental architecture of the optical

OFDM system, including a baseband transmitter, optical chan-

nel, and a baseband receiver. The transmitted frame structure in

Fig. 2(a), where the preamble is used to detect the transmitted

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data frame from the received signals and the data field carries

the transmitted data information. Fig. 2(b) shows that the

subcarrier symbol includes the data subcarrier, pilot subcarrier

and guardband subcarrier in the proposed system. The system

specification is defined in Table. I.

978-1-4244-8499-7/11/$26.00 ©2011 IEEE

TABLE I: Transmitter parameters.Parameters Value Unit

Data rate 4 GHz

Chip duration 0.25 ns

FFT size 512 points

Data/Pilot/Guard/DC 432/50/29/1 sub-carriers

CP length 16 samples

Sub-carrier spacing 7.8125 MHz

Utilized data BW 3.375 GHz

RF central frequency 9.5 GHz

Optical central frequency 193.1 THz

CFO (fc=9.5GhZ) ±1/±5/±10/±20 ppm

SCO (fs=4.0Ghz) ±1/±5/±10/±20 ppm

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Fig. 3: Baseband receiver architecture.

III. RECEIVER ARCHITECTURE

Fig. 3 shows the baseband receiver architecture including

frame detection, carrier frequency offset estimation and com-

pensation, channel estimation, and equalization.

A. Frame Detection

According to the property of circular convolution of FFT,

±8 are randomly allocated on both real and imaginary parts of

specific sub-carriers xn as indicated in Eq. 1. The subcarrier

signals results in the periodical signal in the time-domain.

Thus, the frame boundary is easily detected using delay

correlation [6] and cross correlation [7].

xn = (±8) + j(±8), n = 32k + 1, k = 1, 2, ..., 15 (1)

The delay correlator calculates the normalized received signal

energy as follows:

mn = |

15∑

k=0

r(k+16n)r∗

(k+16n)−L|/

15∑

k=0

|r(k+16n)|2, (2)

where the L=16 is the number of parallel processing data

paths for hardware consideration. A frame is identified if the

normalized received energy grows above the peak threshold

Pth for a while. Since the preamble has the property of PN-

code, we calculate matched filtering for frame boundary as

0 1 2 3 4 5 6 7 8 9 10 11

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0.98

1

SNR (dB)

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ate

Probability of detection success

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500

1000

boundary index

nu

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er

boundary index distribution by modified method with 0dB AWGN

0 100 200 300 400 500 6000

1

2

3

detected index

norm

ali

zed

pea

k

Frame detection

Fig. 4: (a) Detection rate under different SNRs, accuracy of

detection result at 0dB SNR, and (c) detected peak values by

delay correaltion in 1000 symbols.

follows.

Φn = |15∑

k=0

rnq∗w| , w = (k+n) mod 16, (3)

where qw is the filter coefficient. If the magnitude Φn exceeds

the threshold Dth, the start of the frame is located and the

matched filter outputs numerous peaks and averages the peak

intervals to determine the final frame boundary. Fig. 4 shows

the detection results with normalization threshold Pth = 0.3

and Dth = 0.1. The detection success rate excesses 96% even

if the signal-to-noise ratio (SNR) is 0 dB. The accuracy of

the located frame position is very high because the noise

fluctuation is eliminated by averaging peak intervals.

B. Carrier Frequency Offset Estimation and Compensation

Considering Φe as the estimated variable and rn as the n-th

received OFDM symbol, the maximum likelihood estimation

algorithm [6] is given as follows:

Φe =

Nr−1∑

q=0

L−1∑

r=0

r(q)n+r(r

(q)n+r−N )∗ (4)

= e−j2πfΔNTs

Nr−1∑

q=0

L−1∑

r=0

|sn+r|2, (5)

where Nr denotes the number of OFDM symbols used to esti-

mate phase error and L represents the data path number. After

deriving the estimated CFO ε, the phase error passes through

a loop filter to eliminate the noise and then the filtered phase

error is compensated using numerically controlled oscillator

(NCO) table and a complex multiplier to derotate the carrier

frequency offset.

C. Fast Fourier Transform

Fig. 5 shows the block diagram of the proposed sixteen-

path 512-point FFT processor for optical OFDM receiver. The

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Fig. 5: Block diagram of the proposed five-stage mixed-radix

512-point FFT processor.

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Fig. 6: Architecture of N-point quadrature phase SDF FFT

processor.

stage 0 executes radix-2 algorithm based on multi-path SDF

architecture [8], as shown in Fig. 7. The radix-4 is decomposed

into four phases by Eq.6. Thus, the parallel architecture

called quadrature-phase single-path delay feedback can be

constructed by the components from the stage 1 to stage 4

which implement radix-4 algorithm as shown in Fig. 6, where

the intertangle circuit merges the same phase from all paths

to obtain the final result. The modified FFT architecture pro-

vides butterfly processing with 100% utilization and achieves

sixteen times throughput of the radix-2 single delay feedback

architecture.

X[k] =∑N−1

n=0 x(n) · WnkN

= {∑N/4−1

i=0 x(4i) · W ikN/4}

+ {∑N/4−1

i=0 x(4i + 1) · W ikN/4}W

kN

+ {∑N/4−1

i=0 x(4i + 2) · W ikN/4}W

2kN

+ {∑N/4−1

i=0 x(4i + 3) · W ikN/4}W

3kN

(6)

D. Channel Estimation

Finally, we estimate and interpolate the channel frequency

response using the pilot sub-carriers and then recover the

received data from channel effects using a simple one-tap

equalization.

IV. SIMULATION AND EXPERIMENT RESULTS

A. System Simulation

This study utilizes VPI software and Matlab interface to

simulate optical signal simulation environment, as shown in

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Fig. 8: VPI software environment for optical channel simula-

tion.

TABLE II: Optical OFDM system parameters.Item Parameter

Modulation type 16/64/256 QAM

Optical channel model standard single-mode fiber

fiber length 25km

Attenuation over fiber 0.2dB/km

Chromatic dispersion 16(ps/nm-km)

Carrier frequency offset 10ppm

Fig. 8. Table. II lists the optical channel specification in our

simulation. Since the BER test requires an extremely large

number of test patterns in optical system, the bit error rate

(BER) performance is calculated by measuring error vector

magnitude (EVM) [9]. Fig.9 shows the wordlengths of the

signals in the OFDM receiver and the fixed-point simulation

results of different modulations in the optical OFDM system.

TABLE III: Comparison result for pipelined FFT.This work [10] [11] [8] [12]

Technology 90-nm 90-nm 90-nm 0.18-um 0.18-um

FFT size 512 2048 2048 128 128

Core voltage (volt) 1 1 1 1.8 1.8

Core area (Normalized area·10−3mm2) 3.802 0.566 0.473 6.05 7.54

Memory (complex words) 1024 2044 2040 288 288

Complex multiplier 8 12 12 2 N/A

Wordlength 13 9 9 10 16

Average butterfly utilization 100% 66.70% 61.10% 71.40% N/A

No. of data paths 16 8 4 4 8

Max. clock rate (MHz) 166.67 300 300 250 275

Normalized power consumption (mW) 204 159 117 50 46.3

Throughput rate (GSample/s) 2.67 2.4 1.2 1.0 2.2

Normalized Power = Average Power/(V oltage/1.0V )2

Normalized Area = Average/(FFT Size)/(Technolgy/90nm)2

−26 −24 −22 −20 −18 −16 −1410

−12

10−10

10−8

10−6

10−4

10−2

100

Received Optical Power (−dBm)

BE

R

Optical OFDM System Simulation with cfo 10ppm over 25 km fiber

16QAM fixed−point−simulation

16QAM floating point simulation

64QAM fixed−point−simulation

64QAM floating point simulation

256QAM fixed−point−simulation

256QAM floating point simulation

Fig. 9: Fixed-point and floating-point simulation results for

16-QAM, 64-QAM, and 256-QAM.

Fig. 10: Photograph of the FFT processor chip.

B. Chip Implementation

The FFT processor was designed and fabricated using UMC

90nm CMOS technology. This chip occupies 4.1 mm2 chip

area including 1.9 mm2 core area. The maximum clock fre-

queny reaches 166.6MHz. Table. III shows that the proposed

FFT processor achieves a throughput up to 2.65 GS/s and

outperforms other FFT processor chips in the literature. The

primary reason of larger area and power consumption is that

the FFT processor adopts 13-bit signal wordlength for 256-

QAM OFDM transmission. This size is generally larger than

9-bit wordlength of the FFT processor for the ultra-wide band

(UWB) system.

V. CONCLUSION

This study proposes the 16-way parallel processing receiver

architecture for the optical OFDM system. A high-throughput

FFT processor chip for the optical OFDM receiver is also

presented to achieve up to 2.67GS/s throughput. Through the

optical system simulation, the propose OFDM receiver can

successfully demodulate the optical OFDM signals with a high

data-rate.

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