## 3 Experimental Verification and Discussions  
An IMDD OFDM transmission system over an SSMF (standard single mode fiber) as illustrated in Figure 2 is employed to experimentally evaluate the performance of the proposed scheme [24]. Detailed transceiver and system key parameters can be found in Table 1. In this system, all DSP procedures for both transmitter and receiver are achieved by an offline approach. At the transmitter side, the input pseudo random data (PRBS15) is first mapped into parallel complex data with five modulation formats from 4-QAM to 128-QAM. A 64-point inverse fast Fourier transform (IFFT) module is then applied for the generation of OFDM time-domain symbols, in which 30 of them can be used to allocate user data to satisfy the Hermitian symmetry for a real-valued IMDD signal approach. Next, an arbitrary waveform generator (AWG) is employed to generate analog signals at a sampling rate of 2 GSa/s. The analog OFDM signals are then fed into the preamplifiers to adjust the signal amplitude before directly driving a DFB laser at 1550 nm with bandwidth of 2 GHz. Subsequently, the DFB laser converts the electrical signals to optical signals and sends them to the 25 km SSMF. At the received side, a 12 GHz PIN (positive intrinsic-negative) with trans-impedance amplifier (TIA) is utilized for O-E conversion by directly detecting the optical OFDM signals. The received optical power (RoP) can be adjusted by a variable optical attenuator (VOA). The received signals are then captured by the digital storage oscilloscope (DSO) with 10 GSa/s sampling rate ADC to convert analog signals to digital signals for offline DSP processing. During the offline DSP processing, the received data is converted to complex data after symbol synchronization, cyclic prefix (CP)/training sequence (TS) removal, FFT, and channel equalization, as shown in Figure 2. The model of KNN is obtained by training, and then the modulation format is predicted by this model. Once the modulation format is realized using the proposed scheme, the complex data can be decoded to get the original transmit data and to calculate the BER (bit error rate). Meanwhile, OSNR is predicted based on the corresponding modulation formats. The specific recognition and prediction algorithm based on KNN is explained in detail in Section 2. To investigate the feasibility of the proposed scheme, subcarrier bit loading profiles corresponding to a total bit rate of 4.28 Gb/s shown in Figure 3 are employed for the measurements, including five different mixed QAM modulation formats from 4-QAM to 128-QAM. In this paper, we intentionally chose the bit loading profiles to ensure that every type of modulation format was introduced in the experiment. In fact, in practical application, the proposed algorithm will certainly be used with an adaptive bit-and-power-loading algorithm. The constellations and corresponding abstracted \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Modulation format & 128/64/32/16/4-QAM \\ IFFT/FFT size & 64 points \\ CP length & 16 points \\ Bit rate & 4.28 Gb/s \\ OFDM symbols per frame & 100 symbols \\ SSMF length & 25 km \\ DFB modulation bandwidth & 2 GHz \\ DFB wavelength & 1550 nm \\ PIN detector bandwidth & 12 GHz \\ AWG sampling rate & 2 GS/s \\ DSO sampling rate & 10 GS/s \\ DSO/AWG resolution & 8 bit \\ Training set sample size & 30 sample \\ Data points per sample & 3000 points \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Transceiver and system parameters. Figure 2: The experimental setup of intensity modulation and direct detection (IMDD) orthogonal frequency division multiplexing (OFDM) system. representative AHs when the RoP is \(-11\) dBm are shown in Figure 4a. The Figure suggests that different peak profiles can be observed for different modulation formats. We can see from Figure 4a that the constellation maps of 4-QAM and 16-QAM have good performance, and that the modulation formats can be easily distinguished.