ASCO-OFDM based VLC system throughput improvement using PAPR precoding reduction techniques

Visible light communication (VLC) has recently taken the interest of the research community, industry, and academia owing to its legendary notability of simultaneously ensuring lighting and high data rate communication by using cost-effective optoelectronic devices such as light emitting diodes (LED) to transmit data, and photodetector (PD) to receive optical signals and convert them to electrical signals (Hameed et al. 2022). VLC has become the most advanced method of transmitting light via optics. It is an enhanced form of free-space optical communication, particularly for indoor areas. Several optoelectronic/photonic devices/platforms, including Mach Zehnder interferometers, Fiber Bragg gratings, and semiconductor optical amplifiers, started to concentrate and move some of their applications to keep up with the visible broad use of VLC technology, particularly in indoor optical communication settings (Mohammed et al. 2021). Moreover, several studies show the widespread use of many applications using VLC that need high data demands such as high-speed video streaming, localization, high bit rate data broadcasting in interior structures, the development of the physical layer for 5G, and underwater VLC. It is also favored in electromagnetic interference-sensitive applications, such as airplanes and hospitals (Ahmad et al. 2020; Li et al. 2020; Mohammed et al. 2021; Valluri et al. 2020). This aggressive data demand depletes the available radio frequency (RF) spectrum, causing it to become overcrowded. The rapid development of LED promotes the use of VLC as a solution to the problem of insufficient bandwidth (Sharan et al. 2022). Due to the benefits of license-free available spectrum, low power consumption, and safety, as VLC uses light as a medium to convey data, and light signals cannot pass through barriers, a high level of secure communication may be assured (Valluri et al. 2020). So, VLC is seen as a viable complement to radio frequency communications (Wang and Ren 2020). Moreover, due to LED non-coherent emission properties, VLC depends on intensity modulation (IM) forms at the transmitter end and direct detection (DD) at the receiver end. Also, due to LED restricted modulation bandwidth, VLC must rely on multicarrier modulation techniques such as orthogonal frequency division multiplexing (OFDM). OFDM was incorporated for VLC because of its inherent nature of being resistive to multipath fading scenarios and overcoming inter-symbol interference (ISI) (Vappangi et al. 2018). But the OFDM method used in RF cannot be used directly in VLC, since IM/DD systems are a big rudimentary work that requires much effort as it can’t work with the bipolar and complex OFDM signal as in RF. Thus, the time domain signal must be both unipolar, and real to be applicable in VLC systems. Moreover, the input to the Inverse Fast Fourier Transform (IFFT) must meet Hermitian symmetry conditions to produce a real-valued signal. Even if the aforementioned limits result in a real generated signal, it is still in a bipolar form. So, to convert this bipolar signal to a unipolar signal, different optical OFDM (OOFDM) modulation techniques should be used as suggested in the literature (Ahmad et al. 2020; Alrakah et al. 2021; Farid et al. 2022a, b; Wu et al. 2015). Some of these optical modulation techniques are direct current biased optical OFDM (DCO-OFDM) (Li et al. 2020), asymmetrically clipped optical OFDM (ACO-OFDM) (Ahmad et al. 2020), asymmetrically and symmetrically clipping optical OFDM (ASCO OFDM) (Wu et al. 2015), enhanced ASCO OFDM (E-ASCO OFDM) (Farid et al. 2022a, b), pulse amplitude modulated discrete multitone modulation (PAM-DMT) (Alrakah et al. 2021), unipolar OFDM (U-OFDM) and various additional hybrid types like asymmetrically clipped DC-biased optical OFDM (ADO-OFDM) (Hameed et al. 2021). Despite the VLC numerous benefits, a VLC-OFDM-based system has some difficulties that must be resolved. Peak to average power ratio (PAPR) is the most harmful problem, resulting from the superposition of a large number of subcarriers, whose constructive combination may result in high peak values in the time domain. In addition, the restricted dynamic range of LED demands addressing the PAPR problem in VLC. For an LED with a restricted dynamic range, that is, with a very small linear region in its current-voltage (I–V) characteristics, a low PAPR signal is required. Because, if the PAPR signal is large, the peaks that lie beyond the linear region will be clipped and more distortion will be applied to the signal. LED is the primary source of nonlinearity in VLC (Abd Elkarim et al. 2020). So, to reduce LED-induced nonlinear distortions, it is necessary to either linearize the nonlinear transfer characteristics of LED or emphasize PAPR reduction approaches. Much significant research dealing with the linearization of LED transfer characteristics uses digital pre-distortion techniques to compensate for the nonlinear LED features (Abd Elkarim et al. 2020; Elgala et al. 2009); ; . In this research, PAPR reduction methods are used to accommodate the restricted dynamic range of LED. So, to achieve optimal system performance with increased spectral efficiency and high power efficiency, as well as effective use of the available optical spectrum, the PAPR issue in VLC must be solved.

In this research, according to the best author's knowledge on reducing the PAPR for VLC systems, this is the first time a PAPR reduction technique is introduced to the E-ASCO OFDM system. The distinctive feature behind E-ASCO OFDM is it has a high spectrally efficient, high data rate, and power-efficient system with good system BER performance compared to other existing optical modulation techniques (Li et al. 2020); Ahmad et al. 2020). But, unfortunately, the E-ASCO OFDM system has a PAPR problem. So, in this research, a new modified system named precoding E-ASCO OFDM (PE-ASCO OFDM) system is investigated to overcome such PAPR problem. PE-ASCO OFDM is based on introducing different PA such as DHT, DST, DCT, and VLM to the conventional E-ASCO OFDM system to overcome the PAPR problem and taking into consideration their effects on the system BER performance since there is a tradeoff between reducing the PAPR and improving the system BER performance. The main contributions of this paper are as follows:

The rest of the paper is organized as follows, Sect. 2, describes the conventional E-ASCO OFDM system, and the mathematical description for the PAPR and different PRT in OOFDM are introduced in Sect. 3. Section 4 describes the proposed PE-ASCO OFDM system model and parameters. Finally, the results of the simulation and the comparison between the proposed plans are discussed in Sect. 5.

The E-ASCO and the ASCO OFDM systems have the same transmitter but differ in the receiver as explained in detail in Farid et al. (2022a, b), and since the PAPR is measured at the transmitter side so, the PAPR is the same for ASCO and E-ASCO OFDM systems. But in this work, the aim behind studying the PRT in E-ASCO OFDM rather than ASCO OFDM is that the E-ASCO OFDM has more features as low receiver complexity by O (\({N\mathrm{log}}_{2}N\)) with better overall system BER performance than the ASCO OFDM (Farid et al. (2022a, b). The ASCO OFDM system was to boost a high data rate while maintaining an acceptable BER performance. The E-ASCO OFDM system increases the data rate by using \((3N/4)\) subcarriers containing data, where \((N)\) is the FFT size. However, since the samples are split into two frames during transmission, the data rate spectrum efficiency ratio is reduced to 37.5% (Wu et al. 2015). ASCO OFDM system is a mixture system whereas odd subcarriers carried an asymmetric time domain signal as ACO-OFDM (Mohammed et al. 2021), and symmetric time domain signal for even subcarriers (Wu et al. 2015). Figure 1 shows the E-ASCO OFDM transmitter and receiver block diagram. The input data is modulated by M-ary quadrature amplitude modulation (M-QAM) at the transmitter, and the generated modulated symbols have complex values. The modulated symbols are then translated from serial-to-parallel (S/P) form, and Hermitian symmetry is applied to obtain the real signal. In addition, the output of Hermitian symmetry is applied to an Inverse fast Fourier transform (IFFT) block that provides a real bipolar signal. Then, a clipping technique is taken to acquire a suitable signal for transmission through the VLC system. The data is then applied to a parallel to serial (P/S) block to convert it into a serial data bit stream, and a cyclic prefix (CP) is appended to the start of each time-domain OFDM signal. Moreover, a detailed analysis and description of the E-ASCO receiver were introduced by Farid et al. (2022a, b).

The mathematical description for the PAPR and different PRT in OOFDM are introduced and discussed in this section.

The proposed PE-ASCO OFDM incorporates different PAPR precoding reduction techniques such as DCT, DST, DHT, and VLM for reducing the PAPR of the PE-ASCO OFDM system to enhance the system power efficiency and reduce LED-induced nonlinear distortions. Figure 2 represents the block diagram for the transmitter and the receiver of the PE-ASCO OFDM. The proposed PE-ASCO differs from the conventional E-ASCO OFDM represented in Fig. 1 in inserting a precoding block and inverse precoding block after the \((S/P)\) block at the transmitter, and before the \((P/S)\) block at the receiver respectively as marked by red rectangles in Fig. 2.

Also, Figs. 3 and 4 show a flowchart to summarize the PE-ASCO OFDM transmitter and receiver processes respectively.

The transmitted data bit stream is applied to a mapper followed by a S/P block that generates parallel data symbols which are applied to one of the previously mentioned proposed precoding techniques that are mathematically represented in Sect. 3. The output data symbols from the precoder \(X\left(k\right)\) is represented in (8).

The \(X\left(k\right)\) symbols are separated into three components \(\left[{X}_{L}\left(k\right), { X}_{M}\left(k\right), {X}_{{N}^{ }}(k)\right]\) as represented in (9), and (10).where \(k\) is the symbol index that ranges as,

Then, \({X}_{L}(k) , {X}_{M}(k), {and X}_{{N}^{ }}\left(k\right)\) data symbols are applied to Hermitian symmetry and data arrangement block (Farid et al. 2022a, b) as shown in Fig. 5 and following (11).where \(1\le k\le \frac{N}{4}\), and \(X\left(0\right)\) = 0.

The Hermitian symmetry outputs are \({X}_{odd i}\left(\mathrm{k}\right),{X}_{odd j}(k)\), and \({X}_{{even}^{ }}(k)\) corresponding to \({X}_{L}(k) , {X}_{M}(k), {and X}_{{N}^{ }}\left(k\right)\) data symbols respectively, where, \({X}_{odd i}\left(k\right),\) and \({X}_{odd j}(k)\) are two data vectors with only odd-indexed data symbols from the original data stream, i.e., both vectors have zeros at all even indices as represented in (11) and (12). Also, \({X}_{{even}^{ }}(k)\) is a data vector with only even-indexed data symbols from the original data stream i.e., the even data vector has zeros at all odd indices, as represented in (13).

Also, Table 1 illustrates the data symbol structure in PE-ASCO OFDM with \(N\) =16 subcarriers as an example. Then, the data vectors \({X}_{odd i}\left(\mathrm{k}\right),\) \({X}_{odd j}(k)\), and \({X}_{{even}^{ }}(k)\) are applied to the IFFT block to get a real bipolar time domain signal. The arrangement of the data symbols carried on odd, and even subcarrier positions lead to an asymmetric signal around (n= \(\frac{N}{2})\) at the output of the IFFT block as shown in Fig. 6 and represented in (14) and a symmetric signal around (n = \(\frac{N}{2})\) at the output of the IFFT block as shown in Fig. 7 and represented in (15) respectively (Farid et al. (2022a, b). Moreover, this arrangement helps in recovering the clipped part of the signal at the receiver after the clipping process is applied to the transmitted signal at the transmitter to make the signal positive to be valid for transmission through a VLC channel as illustrated by Wu et al. (2015).

In Fig. 2 two IFFT blocks at the transmitter generate three frames. The first two frames\({x}_{odd i}(n)\),\({x}_{odd j}(n)\) are created from the first IFFT block. The transmitted bipolar asymmetric samples are then converted into positive samples by using a negative clipper block which outputs \(\overline{{x }_{odd i}(n) },\mathrm{ and }\overline{{x }_{odd j}(n)}\) signals as represented in (16), (17), and (18).

The second IFFT block generates the last frame \({x}_{{even}^{ }}\left(n\right).\)

Then, \({x}_{{even}^{ }}(n)\) is separated into two equal parts each of (\(N\)) samples \({x}_{even PC}(n)\), and \({x}_{even NC}(n)\). The \({x}_{even PC}(n)\) part is the absolute value of the negative frame resulting from applying positive clipping to \({x}_{even}(n)\) signal, and \({x}_{even NC}(n)\) is the negative clipping version of \({x}_{even}(n)\) as illustrated in (19) and (20) respectively. Then, the two transmitted OFDM symbols are \({x}_{i sum}(n)\) and \({x}_{j sum}(n)\) as in (21) and (22).

At the receiver, the received signal \(y(n)\) is separated into two parts \({y}_{A}(n)\) and \({y}_{B}(n)\) to make a special process on them to extract the data carried on the odd subcarriers. Then, by subtracting the odd signal \({y}_{i,j\mathrm{ odd}}(n)\) from the total received signal \(y(n)\), the data carried on the even subcarriers can be extracted. A detailed mathematical expression and description for these processes are illustrated in Farid et al. (2022a, b). Then, \({y}_{i,j\mathrm{ odd}}(n)\) and \(y_{{\begin{array}{*{20}l} {even} \hfill \\ {NC,PC} \hfill \\ \end{array} }} (n)\) signals are applied to the FFT block to convert them into \({Y}_{i,j odd}(k)\) and \({Y}_{even}(k)\) signals which are represented in the time domain. Finally, the extracted data symbols \({Y}_{i,j odd}(k)\), and \({Y}_{even}(k)\) are applied to a data symbol arrangement then the inverse precoding reduction technique (IPRT) to make the inverse of the precoding process occur at the transmitter side to get the actual transmitted data without any distortion. Also, the output from IPRT is applied to a de-mapper block that output the original data.

The numerical results of the PAPR and BER system performance corresponding to the proposed PE-ASCO OFDM using different PRT (e.g., DCT, DHT, DST, and VLM), and the conventional E-ASCO OFDM system are compared and simulated using MATLAB. Also, the numerical results were studied for different modulation techniques (i.e., 4, 16, 64, 256, 1024, and 4096-QAM) by Farid et al. (2022a, b) to analyze the effect of changing the modulation order on the PAPR and BER system performance. Moreover, the simulated channel is additive white Gaussian noise (AWGN) channel. This work is also associated with a high IFFT size (N = 1024) (i.e., extensive processing data). Table 2 summarized the simulation parameters which are used in consistent with previously published work such as Bai et al. (2017), Farid et al. (2019), Farid et al. (2020), Farid et al. (2022a, b), Hu et al. (2019), Mohammed et al. (2021), Vappangi et al. (2022).

The PAPR reduction effectiveness is measured by the PAPR CCDF (Mohammed et al. 2021). the values of \({\mathrm{PAPR}}_{\mathrm{o}}\) is calculated at CCDF= \({10}^{-3}\) same as in the literature. where, \({PAPR}_{o}\) is the instantaneous PAPR value at CCDF = \({10}^{-3}\). In addition, the two parameters \({PAPR}_{gain}\) and \({E}_{b}/{N}_{o diff}\) are introduced in this work for comparison purposes. At which \({PAPR}_{gain}\) is defined as the amount of reduction in \({PAPR}_{o}\) of the proposed technique compared to the conventional E-ASCO \({PAPR}_{o}\) which is mathematically calculated by subtracting the \({PAPR}_{o}\) of the proposed PE-ASCO OFDM from the E-ASCO OFDM \({PAPR}_{o}\) at CCDF = \({10}^{-3}\). The greater the \({PAPR}_{ gain}\), the more efficient the used PAPR reduction technique. while \({E}_{b}/{N}_{o diff}\) is defined as the difference between the conventional E-ASCO OFDM system \({E}_{b}/{N}_{o}\) and the required \({E}_{b}/{N}_{o}\) after applying the PAPR reduction technique as represented in (24). \({E}_{b}/{N}_{o diff}\) is mathematically calculated by subtracting the \({E}_{b}/{N}_{o}\) of the proposed PE-ASCO technique from the E-ASCO \({E}_{b}/{N}_{o}\) value at BER = \({10}^{-4}\). It is worth mentioning that, there are three instances for the \({E}_{b}/{N}_{o diff}\) value:

This section compares the specifications of the proposed work in this thesis to those of comparable works in the literature. However, this is the first time studying the PAPR concept in the E-ASCO OFDM systems. So, the comparison with the literature is limited to various optical modulation-based VLC systems such as ACO-OFDM, and DCO OFDM by comparing the amount of \({PAPR}_{ gain}\) and \({Eb/N\mathrm{o }}_{diff}\) for each system as shown in Table 5. The definition of main judgment factors is defined previously at the beginning of this section. So, the best technique is the one with the greatest amount of \({PAPR}_{ gain}\) while causing no degradation in system BER performance (i.e., \({Eb/N0 }_{diff}\)= 0).

Table 5 demonstrates that this proposed technique provided a significant advantage in reaching high calculated \({PAPR}_{ gain}\) without BER system degradation. This is done when applying VLM PRT in the PE-ASCO OFDM system.

In this paper different precoding techniques are proposed for the PE-ASCO OFDM VLC system for reducing the PAPR to get power efficient VLC system. The proposed PRT are evaluated and compared with each other in addition to the conventional E-ASCO OFDM system according to PAPR reduction capability and system BER performance to get the optimal PRT in reducing PAPR while keeping the system BER performance without degradation for the PE-ASCO OFDM system. Simulation results indicate that the proposed VLM pre-coding scheme outperforms the DHT, DCT, and DST pre-coding schemes by 0.82 dB, 0.71 dB, and 0.05 dB respectively, in the PE-ASCO OFDM system as it reduces the high PAPR of the PE-ASCO OFDM system by 2.7 dB without any degradation in system BER performance. This research increases the compatibility of the E-ASCO OFDM system with practical applications. A comparison with related literature is performed to validate and assure the innovation and performance of the suggested methods.