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ZTE Communications

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S pecial Topic<br />

Greater than 200 Gb/s Transmission Using Direct-Detection Optical OFDM Superchannel<br />

Wei-Ren Peng, Itsuro Morita, Hidenori Takahashi, and Takehiro Tsuritani<br />

10 GHz passbands targeting one of the carriers and the<br />

desired signal band. Because of the power loss of DPF, an<br />

EDFA and an 80 GHz optical bandpass filter (OBPF) raise the<br />

signal power before the signal enters the photodiode. In this<br />

experiment, the first to fifth bands are demodulated with the<br />

left carrier (carrier 1), and the sixth to ninth bands are<br />

demodulated with the right carrier (carrier 2). After the<br />

photodiode, the desired band is down-converted to its<br />

baseband via an electrical I/Q demodulator. This I/Q<br />

demodulator comprises one splitter, one synthesizer, one<br />

power amplifier, two mixers, and two electrical low-pass<br />

filters (3 dB bandwidth = 3.7 GHz). The I/Q output signals are<br />

recorded by a real-time scope operated at 20 GSa/s.<br />

Synchronization, cyclic prefix removal, channel estimation,<br />

and equalization are performed offline using MATLAB. The<br />

BER is evaluated with an error-counting method, and for each<br />

BER analysis, 2 million sampling points are considered.<br />

Fig. 3(a) shows the optical spectra of the transmitter output<br />

(resolution = 20 MHz); Fig. 3(b) shows the DPF output<br />

(targeting the 5th band); and Fig. 3(c) shows the digital<br />

spectrum of the 5th band after the real-time scope (where the<br />

band index is defined in Fig. 3a). In Fig. 3(c), the power<br />

ripples on top of the signal come from the power reflection, at<br />

the RF ports, of the mixers in the I/Q demodulator. These<br />

ripples are a function of frequency and introduce some OSNR<br />

penalty to the system, that is, implementation penalty.<br />

Here, we highlight several points about the experiment<br />

setup. First, at the transmitter, the length of the optical paths<br />

between the sideband and carrier branches should be<br />

controlled so that they are as similar as possible. A significant<br />

difference in length would lead to strong phase incoherency<br />

between the carrier and sideband, and this would cause<br />

dramatic phase noise after the photodiode. In this experiment,<br />

we not only equalized the optical lengths of the carrier and<br />

sideband paths, but we also used a zero-overhead phase<br />

noise compensator at the receiver (section 5). Second,<br />

6.5 GHz and 19.5 GHz frequencies for the 9-comb generator<br />

are phase-locked in order to maintain the orthogonality and<br />

reduce linear crosstalk between the adjacent bands [13].<br />

However, because of the sufficiently large band spacing, the<br />

performance is hardly degraded, even if we remove the phase<br />

locking between the synthesizers. Third, to obtain a<br />

broadband bandwidth, we assemble the I/Q demodulator with<br />

discrete components rather than use an integrated I/Q mixer,<br />

which would introduce I/Q imbalances into the signal. This<br />

would mean I/Q imbalance estimation and compensation<br />

would be critically necessary in our system. In section 5, we<br />

introduce a low-overhead I/Q imbalance estimation approach<br />

that uses only two training symbols, that is, the same symbols<br />

for channel estimation.<br />

5 Low-Overhead Signal Processing<br />

Methods<br />

To compensate for I/Q imbalance and phase noise, we<br />

propose a low-overhead training method to estimate I/Q<br />

imbalance and introduce a zero-overhead decision-directed<br />

14<br />

<strong>ZTE</strong> COMMUNICATIONS<br />

March 2012 Vol.10 No.1<br />

phase noise compensator (DD-PNC) [19].<br />

5.1 I/Q Imbalance Training Method<br />

For each frame, the proposed method uses only two<br />

consecutive training symbols (the same as those for channel<br />

estimation). The first symbol is randomly generated, and the<br />

second symbol simply copies the first one and inverts the<br />

signs of the data symbols on negative subcarriers. The two<br />

consecutive training symbols are denoted [ak, b-k] and<br />

[ak, -b-k], where ak and b-k are the data symbols on k th<br />

and -k th subcarriers, respectively, and k is a positive integer<br />

ranging from 1 to Nd/2, with Nd being the data subcarrier<br />

number. At the receiver, the received training symbols<br />

disrupted by I/Q imbalances are denoted [pk, q-k] and [rk, l-k]<br />

for the first and second training symbols, respectively. Then,<br />

the input and output symbols can be expressed in 2 × 2<br />

mutually coupled matrixes [20]:<br />

pk<br />

q-k<br />

and<br />

rk<br />

l-k<br />

H 11 H 12 ak<br />

= (4)<br />

H 21 H 22 b-k<br />

H 11 H 12 ak<br />

= (5)<br />

H 21 H 22 -b-k<br />

The four elements in the 2 × 2 channel matrix H (Hij, which<br />

should contain both the channel response and I/Q<br />

imbalances) can be easily derived with H11 = (pk + rk)/(2a k),<br />

H12 = (pk-rk)/(2bk); H 21 = (q-k + l-k)/(2a k ); and<br />

H 22 = (q-k-l-k)/(2bk), for which the estimation accuracy can be<br />

further improved using the intrachannel frequency-domain<br />

average method [15].<br />

After obtaining the four elements, the inverse matrix of H<br />

can be derived for subsequent equalization. Because this<br />

technique uses the same training symbols (two per frame) for<br />

both channel and I/Q imbalance estimation, the training<br />

overhead is relatively lower than that in [20].<br />

This data-aided adaptive approach is simple, has low<br />

overhead, and is a better way to estimate and compensate for<br />

I/Q imbalance. In the offline I/Q estimation proposal in [21],<br />

the I/Q imbalance in each individual receiver needs to be<br />

customized; however, using this new approach, the I/Q<br />

imbalances of each individual receiver can be handled<br />

adaptively using only two training symbols (which can the<br />

same ones for channel estimation). In particular, the adaptive<br />

method is suitable for lab experiments where I/Q imbalances<br />

vary over time because of the replacement of any component<br />

or the slow bias drift of the optical modulators.<br />

Here we briefly discuss the computational complexity of this<br />

I/Q imbalance estimation method. At the training stage, to<br />

obtain the channel matrix for all subcarriers, 2Nd complex<br />

multiplications are needed for each OFDM symbol, and the<br />

matrix inversions for equalization need an additional 3Nd<br />

multiplications. Therefore, at the training stage, 5Nd<br />

multiplications are needed, which is 4Nd more multiplications<br />

than in regular channel estimation. At the equalization stage,<br />

two subcarriers are jointly equalized via a 2 × 2 matrix so that<br />

the number of multiplications for each OFD symbol is 2Nd,

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