Optical-OFDM VLC System: Peak-to-Average Power Ratio Enhancement and Performance Evaluation.

Visible Light Communication (VLC) systems are favoured for numerous applications due to their extensive bandwidth and resilience to electromagnetic interference. This study delineates various constructions of Optical Orthogonal Frequency Division Multiplexing (O-OFDM) approaches employed in VLC systems. Various factors are elaborated within this context to ascertain a more effective O-OFDM approach, including constellation size, data arrangement and spectral efficiency, power efficiency, computational complexity, bit error rate (BER), and peak-to-average power ratio (PAPR). This paper seeks to assess these approaches' BER and PAPR performance across varying modulation orders. Regrettably, in VLC systems based on OFDM methodology, the superposition of multiple subcarriers results in a high PAPR. Therefore, this study aims to diminish the PAPR in VLC systems, enhancing system performance. We propose a non-distorting PAPR reduction technique, namely the Vandermonde-Like Matrix (VLM) precoding technique. The suggested technique is implemented across various O-OFDM approaches, including DCO-OFDM, ADO-OFDM, ACO-OFDM, FLIP-OFDM, ASCO-OFDM, and LACO-OFDM. Notably, this method does not affect the system's data rate because it does not require the mandatory transmission of side information. Furthermore, this technique can decrease the PAPR without impacting the system's BER performance. This study compares the proposed PAPR reduction technique against established methods documented in the literature to evaluate their efficacy and validity rigorously.

A Novel Waveform Optimization Method for Orthogonal-Frequency Multiple-Input Multiple-Output Radar Based on Dual-Channel Neural Networks.

The orthogonal frequency-division multiplexing (OFDM) mode with a linear frequency modulation (LFM) signal as the baseband waveform has been widely studied and applied in multiple-input multiple-output (MIMO) radar systems. However, its high sidelobe levels after pulse compression affect the target detection of radar systems. For this paper, theoretical analysis was performed, to investigate the causes of high sidelobe levels in OFDM-LFM waveforms, and a novel waveform optimization design method based on deep neural networks is proposed. This method utilizes the classic ResNeXt network to construct dual-channel neural networks, and a new loss function is employed to design the phase and bandwidth of the OFDM-LFM waveforms. Meanwhile, the optimization factor is exploited, to address the optimization problem of the peak sidelobe levels (PSLs) and integral sidelobe levels (ISLs). Our numerical results verified the correctness of the theoretical analysis and the effectiveness of the proposed method. The designed OFDM-LFM waveforms exhibited outstanding performance in pulse compression and improved the detection performance of the radar.

Flexible and Reconfigurable OFDM Implementation in DSP Platform for Various Purposes and Applications.

In the modern technological era of sophisticated applications and high-quality communications, a platform of clever strategy and quickly updated systems is needed. It should be capable of withstanding the fastest emerging problems like signal attenuation and hostile actions intended to harm the whole network. The main contributions of this work are the production of an OFDM system (with low cost) that can sustain high-speed communications and be easily adjusted with new integrated code while exhibiting the feasibility of implementing a transmitter-receiver system in the same DSP and demonstrating the holistic approach with the qualitative integration of such an architecture in a warfare scenario. Specifically, in this research, the point of view is toward three facts. The first is to show a method of quick self-checking the operational status of a digital signal processor (DSP) platform and then the pedagogical issues of how to fast check and implement an updated code inside DSPs through simple schematics. The second point is to present the prototype system that can easily be programmed using a graphical user interface (GUI) and can change its properties (such as the transmitted modulated sinusoids-orthogonal frequency division multiplexing subcarriers). Alongside the presentation, the measurements are presented and discussed. These were acquired with the use of an oscilloscope and spectrum analyzer. The third point is to qualitatively show the application of such a system inside a modern warfare environment and to recommend various potential system responses according to the development of such a platform of reconfigurable implemented OFDM systems. The implementation was performed for two types of systems: (1) transmitter and (2) transmitter-receiver system. Notably, the system acts quickly with a delay of about 1 msec in the case of transmitting and receiving in the same DSP, suggesting excellent future results under real conditions.

Performance Evaluation of Carrier-Frequency Offset as a Radiometric Fingerprint in Time-Varying Channels.

The authentication of wireless devices through physical layer attributes has attracted a fair amount of attention recently. Recent work in this area has examined various features extracted from the wireless signal to either identify a uniqueness in the channel between the transmitter-receiver pair or more robustly identify certain transmitter behaviors unique to certain devices originating from imperfect hardware manufacturing processes. In particular, the carrier frequency offset (CFO), induced due to the local oscillator mismatch between the transmitter and receiver pair, has exhibited good detection capabilities in stationary and low-mobility transmission scenarios. It is still unclear, however, how the CFO detection capability would hold up in more dynamic time-varying channels where there is a higher mobility. This paper experimentally demonstrates the identification accuracy of CFO for wireless devices in time-varying channels. To this end, a software-defined radio (SDR) testbed is deployed to collect CFO values in real environments, where real transmission and reception are conducted in a vehicular setup. The collected CFO values are used to train machine-learning (ML) classifiers to be used for device identification. While CFO exhibits good detection performance (97% accuracy) for low-mobility scenarios, it is found that higher mobility (35 miles/h) degrades (72% accuracy) the effectiveness of CFO in distinguishing between legitimate and non-legitimate transmitters. This is due to the impact of the time-varying channel on the quality of the exchanged pilot signals used for CFO detection at the receivers.

Progressive Pattern Interleaver with Multi-Carrier Modulation Schemes and Iterative Multi-User Detection in IoT 6G Environments with Multipath Channels.

Sixth-generation (6G) wireless networks demand a more efficient implementation of non-orthogonal multiple access (NOMA) schemes for severe multipath fading environments to serve multiple users. Using non-orthogonal multiple access (NOMA) schemes in IoT 6G networks is a promising solution to allow multiple users to share the same spectral and temporal resource, increasing spectral efficiency and improving the network's capacity. In this work, we have evaluated the performance of a novel progressive pattern interleaver (PPI) employed to distinguish the users in interleaved division multiple access (IDMA) schemes, suggested by 3GPP guidelines as a NOMA scheme, with two multi-carrier modulation schemes known as single-carrier frequency-division multiple access (SC-FDMA) and orthogonal frequency-division multiplexing (OFDM), resulting in SC-FDMA-IDMA and OFDM-IDMA schemes. Both schemes are multi-carrier schemes with orthogonal sub-carriers to deal against inter-symbol interference (ISI) and orthogonal interleavers for the simultaneous access of multiple users. It has been suggested through simulation outcomes that PPI performance is adequate with SC-FDMA-IDMA and OFDM-IDMA schemes in terms of bit error rate (BER) under multipath channel conditions. Moreover, regarding bandwidth requirement and the implementation complexity of the transmitted interleaver structure, PPI is superior to the conventional random interleaver (RI).

Multi-Cluster Approaches to Radio Sensor Array Channel Modeling and Simulation.

In this paper, we explore the physical propagation environment of radio waves by describing it in terms of distant scattering clusters. Each cluster consists of numerous scattering objects that may exhibit certain statistical properties. By utilizing geometry-based methods, we can study the channel second-order statistics (CSOS), where each distant scattering cluster corresponds to a CSOS, contributes a portion to the Doppler spectrum, and is associated with a state-space multiple-input and multiple-output (MIMO) radio channel model. Consequently, the physical propagation environment of radio waves can be modeled by summing multiple state-space MIMO radio channel models. This approach offers three key advantages: simplicity, the ability to construct the entire Doppler power spectrum from multiple uncorrelated distant scattering clusters, and the capability to obtain the channels contributed by these clusters by summing the individual channels. This methodology enables the reconstruction of the radio wave propagation environment in a simulated manner and is crucial for developing massive MIMO channel models.

Time-Varying Channel Estimation Based on Distributed Compressed Sensing for OFDM Systems.

For orthogonal frequency division multiplexing (OFDM) systems in high-mobility scenarios, the estimation of time-varying multipath channels not only has a large error, which affects system performance, but also requires plenty of pilots, resulting in low spectral efficiency. To address these issues, we propose a time-varying multipath channel estimation method based on distributed compressed sensing and a multi-symbol complex exponential basis expansion model (MS-CE-BEM) by exploiting the temporal correlation and the joint delay sparsity of wideband wireless channels within the duration of multiple OFDM symbols. Furthermore, in the proposed method, a sparse pilot pattern with the self-cancellation of pilot intercarrier interference (ICI) is adopted to reduce the input parameter error of the MS-CE-BEM, and a symmetrical extension technique is introduced to reduce the modeling error. Simulation results show that, compared with existing methods, this proposed method has superior performances in channel estimation and spectrum utilization for sparse time-varying channels.

Data-Aided Maximum Likelihood Joint Angle and Delay Estimator Over Orthogonal Frequency Division Multiplex Single-Input Multiple-Output Channels Based on New Gray Wolf Optimization Embedding Importance Sampling.

In this paper, we propose a new data-aided (DA) joint angle and delay (JADE) maximum likelihood (ML) estimator. The latter consists of a substantially modified and, hence, significantly improved gray wolf optimization (GWO) technique by fully integrating and embedding within it the powerful importance sampling (IS) concept. This new approach, referred to hereafter as GWOEIS (for "GWO embedding IS"), guarantees global optimality, and offers higher resolution capabilities over orthogonal frequency division multiplex (OFDM) (i.e., multi-carrier and multi-path) single-input multiple-output (SIMO) channels. The traditional GWO randomly initializes the wolfs' positions (angles and delays) and, hence, requires larger packs and longer hunting (iterations) to catch the prey, i.e., find the correct angles of arrival (AoAs) and time delays (TDs), thereby affecting its search efficiency, whereas GWOEIS ensures faster convergence by providing reliable initial estimates based on a simplified importance function. More importantly, and beyond simple initialization of GWO with IS (coined as IS-GWO hereafter), we modify and dynamically update the conventional simple expression for the convergence factor of the GWO algorithm that entirely drives its hunting and tracking mechanisms by accounting for new cumulative distribution functions (CDFs) derived from the IS technique. Simulations unequivocally confirm these significant benefits in terms of increased accuracy and speed Moreover, GWOEIS reaches the Cramér-Rao lower bound (CRLB), even at low SNR levels.

Passive Backscatter Communication Scheme for OFDM-IM with Dynamic Carrier Activation.

Multicarrier backscattering has been proposed to improve the communication rate, but the complex circuit structure of multicarrier backscattering devices requires more power consumption, resulting in devices far away from the radio frequency (RF) source without enough power to maintain communication, which greatly reduces the limited communication range in backscattering. To solve this problem, this paper introduces carrier index modulation (IM) into orthogonal frequency division multiplexing (OFDM) backscattering and proposes a dynamic subcarrier activated OFDM-IM uplink communication scheme suitable for passive backscattering devices. When the existing power collection level of the backscatter device is detected, only a subset of carrier modulation is activated using part of the circuit modules to reduce the power threshold required for device activation. The activated subcarriers are mapped by a block-wise combined index using the look-up table method, which can not only transmit information using traditional constellation modulation but also carry additional information through the frequency domain carrier index. Monte Carlo experiments show that this scheme can effectively increase the communication distance and improve the spectral efficiency of low-order modulation backscattering when the power of the transmitting source is limited.

Hardware-Based Architecture for DNN Wireless Communication Models.

Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO OFDM) is a key technology for wireless communication systems. However, because of the problem of a high peak-to-average power ratio (PAPR), OFDM symbols can be distorted at the MIMO OFDM transmitter. It degrades the signal detection and channel estimation performance at the MIMO OFDM receiver. In this paper, three deep neural network (DNN) models are proposed to solve the problem of non-linear distortions introduced by the power amplifier (PA) of the transmitters and replace the conventional digital signal processing (DSP) modules at the receivers in 2 × 2 MIMO OFDM and 4 × 4 MIMO OFDM systems. Proposed model type I uses the DNN model to de-map the signals at the receiver. Proposed model type II uses the DNN model to learn and filter out the channel noises at the receiver. Proposed model type III uses the DNN model to de-map and detect the signals at the receiver. All three model types attempt to solve the non-linear problem. The robust bit error rate (BER) performances of the proposed receivers are achieved through the software and hardware implementation results. In addition, we have also implemented appropriate hardware architectures for the proposed DNN models using special techniques, such as quantization and pipeline to check the feasibility in practice, which recent studies have not done. Our hardware architectures are successfully designed and implemented on the Virtex 7 vc709 FPGA board.

Maximal Ratio Combining Detection in OFDM Systems with Virtual Carriers Over V2V Channels.

This paper examines the performance of orthogonal frequency division multiplexing (OFDM) systems for vehicle-to-vehicle (V2V) communication channels. More specifically, a doubly selective channel under high intercarrier interference (ICI) is considered. Current solutions involve complex detection and/or reduced spectral efficiency receivers. This paper proposes the use of virtual carriers (VC) in an OFDM system with a low-complexity maximal ratio combining (MRC) detector to improve the bit error rate (BER) performance. The results show that VC provides diversity in received data, resulting in a ≥5 dB gain compared to previous OFDM systems with conventional linear/nonlinear detectors used as a reference. The detector presented in this paper has linear complexity, making it a suitable solution for real-time V2V communication systems.

Inner-Frame Time Division Multiplexing Waveform Design of Integrated Sensing and Communication in 5G NR System.

The design of an integrated sensing and communication (ISAC) waveform compatible with the 5G new radio (NR) system is crucial in enabling ISAC by utilizing the hardware of existing base stations (BSs). In this paper, we design an inner-frame time division multiplexed sensing waveform in the frame structure of 5G NR to achieve ISAC. The designed waveform is computed by the simulated annealing algorithm on an optimization cost function of a constrained combination of the peak-to-sidelobe ratio (PSLR) and the integrated sidelobe ratio (ISLR) of the velocity ambiguity function. Specifically, the constraints are the 5G communication protocol and 5G NR frame structure. In addition, we conducted corresponding signal detection and estimation methods to illustrate the performance of the sensing waveform. Both theoretical analysis and simulation experiments show that the designed waveform can effectively achieve target detection and parameter estimation under low sensing cost conditions.

Efficiency Maximization for Battery-Powered OFDM Transmitter via Amplifier Operating Point Adjustment.

While Orthogonal Frequency Division Multiplexing (OFDM) is a dominating spectrum access technology in modern, wideband access networks, it is important to maximize its transmission efficiency considering the underlying radio front-end characteristics. A practical front-end contains nonlinear components, e.g., a Power Amplifier (PA), resulting in nonlinear distortion being injected into OFDM band deteriorating symbols detection. A PA operating point, defined here by Input Back-Off (IBO), can be adjusted to balance the wanted signal power and nonlinear distortion power. While it is the most common to maximize the spectral efficiency (SE), recently, energy efficiency (EE) maximization gained momentum. However, EE maximization requires, in addition to PA nonlinearity modeling, modeling of the power consumption of the PA and all other transmitter components. While it is commonly overlooked, if a battery is used to power the transmitter, its model should be considered as well. This paper derives mathematical expressions for EE and SE of an OFDM transmitter considering Rapp and soft-limiter models of PA nonlinearity, class A, class B, and perfect PA power consumption models, and two battery models: perfect and worst-case. While closed-form expressions cannot be obtained for most of the derived integrals, numerical methods have been used to obtain the optimal IBO value in each case. The numerical results show, in addition to optimal IBO values, the expected Signal-to-Noise and Distortion Ratios (SNDRs). It is shown that the optimal IBO value changes significantly with the wireless channel properties, utilized hardware architecture, or the utilized optimization goal. As such, the proposed optimization is an important topic for 5G and beyond transmitters.

Denoising Generalization Performance of Channel Estimation in Multipath Time-Varying OFDM Systems.

Although Orthogonal Frequency Division Multiplexing (OFDM) technology is still the key transmission waveform technology in 5G, traditional channel estimation algorithms are no longer sufficient for the high-speed multipath time-varying channels faced by both existing 5G and future 6G. In addition, the existing Deep Learning (DL) based OFDM channel estimators are only applicable to Signal-to-Noise Ratios (SNRs) in a small range, and the estimation performance of the existing algorithms is greatly limited when the channel model or the mobile speed at the receiver does not match. To solve this problem, this paper proposes a novel network model NDR-Net that can be used for channel estimation under unknown noise levels. NDR-Net consists of a Noise Level Estimate subnet (NLE), a Denoising Convolutional Neural Network subnet (DnCNN), and a Residual Learning cascade. Firstly, a rough channel estimation matrix value is obtained using the conventional channel estimation algorithm. Then it is modeled as an image and input to the NLE subnet for noise level estimation to obtain the noise interval. Then it is input to the DnCNN subnet together with the initial noisy channel image for noise reduction to obtain the pure noisy image. Finally, the residual learning is added to obtain the noiseless channel image. The simulation results show that NDR-Net can obtain better estimation results than traditional channel estimation, and it can be well adapted when the SNR, channel model, and movement speed do not match, which indicates its superior engineering practicability.

FDSS-Based DFT-s-OFDM for 6G Wireless Sensing.

Integrated sensing and communications (ISAC) is emerging as a key technology of 6G. Owing to the low peak-to-average power ratio (PAPR) property, discrete Fourier transform spread orthogonal frequency-division multiplexing (DFT-s-OFDM) is helpful to improve the sensing range and suitable for high-frequency transmission. However, compared to orthogonal frequency-division multiplexing (OFDM), the sensing accuracy of DFT-s-OFDM is relatively poor. In this paper, frequency-domain spectral shaping (FDSS) is adopted to enhance the performances of DFT-s-OFDM including sensing accuracy and PAPR by adjusting the correlation of signals. Specifically, we first establish a signal model for the ISAC system, followed by the description of performance indicators. Then, we analyze the influence of amplitude fluctuation of frequency domain signals on sensing performance, which shows the design idea of FDSS-enhanced DFT-s-OFDM. Further, a FDSS-enhanced DFT-s-OFDM framework is introduced for ISAC, where two types of FDSS filters including a pre-equalization filter and an isotropic orthogonal transform algorithm (IOTA) filter are designed. The simulation results show that the proposed scheme can obtain about 4 dB performance gain in terms of sensing accuracy over DFT-s-OFDM. In addition, FDSS-enhanced DFT-s-OFDM can significantly reduce PAPR and improve the power amplifier efficiency.

Efficient and Low-Complex Signal Detection with Iterative Feedback in Wireless MIMO-OFDM Systems.

To solve error propagation and exorbitant computational complexity of signal detection in wireless multiple-input multiple-output-orthogonal frequency division multiplexing (MIMO-OFDM) systems, a low-complex and efficient signal detection with iterative feedback is proposed via a constellation point feedback optimization of minimum mean square error-ordered successive interference cancellation (MMSE-OSIC) to approach the optimal detection. The candidate vectors are formed by selecting the candidate constellation points. Additionally, the vector most approaching received signals is chosen by the maximum likelihood (ML) criterion in formed candidate vectors to reduce the error propagation by previous erroneous decision, thus improving the detection performance. Under a large number of matrix inversion operations in the above iterative MMSE process, effective and fast signal detection is hard to be achieved. Then, a symmetric successive relaxation iterative algorithm is proposed to avoid the complex matrix inversion calculation process. The relaxation factor and initial iteration value are reasonably configured with low computational complexity to achieve good detection close to that of the MMSE with fewer iterations. Simultaneously, the error diffusion and complexity accumulation caused by the successive detection of the subsequent OSIC scheme are also improved. In addition, a method via a parallel coarse and fine detection deals with several layers to both reduce iterations and improve performance. Therefore, the proposed scheme significantly promotes the MIMO-OFDM performance and thus plays an irreplaceable role in the future sixth generation (6G) mobile communications and wireless sensor networks, and so on.

Heterogeneous Network Switching Strategy Based on Communication Blind Area Dwell Time.

The limitation of indoor visible light coverage and the attenuation of its signal when propagating in line-of-sight has seriously affected the stable communication of receiving devices when users move randomly and also aggravated the power consumption of visible light networking systems. According to the above situation, on the basis of the heterogeneous networking of visible light communication (VLC) and RF communication integration, this article proposes a horizontal-vertical collaborative handover strategy based on the communication blind area dwell time (CBD-HVHO). Combining asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) technology with networking handover technology, ACO-OFDM is used to determine the indoor communication blind area by calculating the bit error rate (BER) value at the signal receiver while reducing the multipath interference generated by visible light signals during channel transmission. To achieve this, set the communication blind channel interruption time as the threshold time, compare the communication blind area dwell time with the threshold time, and finally combine the horizontal and vertical collaborative handover strategies based on the communication blind area dwell time. The simulation results show that the handover probability is 0.009, the average number of handovers is 1.006, and the average network throughput is 195.2826 Mbps. Compared with the previously proposed immediate vertical handover (I-VHO) scheme and the dwell vertical handover (D-VHO) scheme, the communication stability is significantly improved, and the power consumption of the network system is reduced to a certain extent.

Wideband and Channel Switchable Mode Division Multiplexing (MDM) Optical Power Divider Supporting 7.682 Tbit/s for On-Chip Optical Interconnects.

Silicon photonics (SiPh) are considered a promising technology for increasing interconnect speed and capacity while decreasing power consumption. Mode division multiplexing (MDM) enables signals to be transmitted in different orthogonal modes in a single waveguide core. Wideband MDM components simultaneously supporting wavelength division multiplexing (WDM) and orthogonal frequency-division multiplexing (OFDM) can significantly increase the transmission capacity for optical interconnects. In this work, we propose, fabricate and demonstrate a wideband and channel switchable MDM optical power divider on an SOI platform, supporting single, dual and triple modes. The switchable MDM power divider consists of two parts. The first part is a cascaded Mach-Zehnder interferometer (MZI) for switching the data from their original TE0, TE1 and TE2 modes to different modes among themselves. After the target modes are identified, mode up-conversion and Y-branch are utilized in the second part for the MDM power division. Here, 48 WDM wavelength channels carrying OFDM data are successfully switched and power divided. An aggregated capacity of 7.682 Tbit/s is achieved, satisfying the pre-forward error correction (pre-FEC) threshold (bit-error-rate, BER = 3.8 × 10-3). Although up to three MDM modes are presented in the proof-of-concept demonstration here, the proposed scheme can be scaled to higher order modes operation.

A Novel Low Complexity Two-Stage Tone Reservation Scheme for PAPR Reduction in OFDM Systems.

Orthogonal frequency division multiplexing (OFDM) has the characteristics of high spectrum efficiency and excellent anti-multipath interference ability. It is the most popular and mature technology currently in wireless communication. However, OFDM is a multi-carrier system, which inevitably has the problem of a high peak-to-average power ratio (PAPR), and s signal with too high PAPR is prone to distortion when passing through an amplifier due to nonlinearity. To address the troubles caused by high PAPR, we proposed an improved tone reservation (I-TR) algorithm to alleviate the above native phenomenon, which will pay some modest pre-calculations to estimate the rough proportion of peak reduction tone (PRT) to determine the appropriate output power allocation threshold then utilize a few iterations to converge to the near-optimal PAPR. Furthermore, our proposed scheme significantly outperforms previous works in terms of PAPR performance and computational complexity, such as selective mapping (SLM), partial transmission sequence (PTS), TR, tone injection (TI), etc. The simulation results show that in our proposed scheme, the PAPR is appreciably reduced by about 6.44 dB compared with the original OFDM technique at complementary cumulative distribution function (CCDF) equal to 10-3, and the complexity of I-TR has reduced by approximately 96% compared to TR. Besides, as for bit error rate (BER), our proposed method always outperforms the original OFDM without any sacrifice.

Highly Sensitive SPAD-Based Receiver for Dimming Control in LiFi Networks.

Visible light communication (VLC) is an emerging mode of wireless communication that supports both illumination and communication. One essential function of VLC systems is the dimming control, which requires a sensitive receiver for low-light conditions. The use of an array of single-photon avalanche diodes (SPADs) is one promising approach to enhancing receivers' sensitivity in a VLC system. However, because of the non-linear effects brought on by the SPAD dead time, an increase in the brightness of the light might degrade its performance. In this paper, an adaptive SPAD receiver is proposed for VLC systems to ensure reliable operation under various dimming levels. In the proposed receiver, a variable optical attenuator (VOA) is used to adaptively control the SPAD's incident photon rate according to the instantaneous received optical power so that SPAD operates in its optimal conditions. The application of the proposed receiver in systems with various modulation schemes is investigated. When binary on-off keying (OOK) modulation is employed due to its good power efficiency, two dimming control methods of the IEEE 802.15.7 standard based on analogue and digital dimming are considered. We also investigate the application of the proposed receiver in the spectral efficient VLC systems with multi-carrier modulation schemes, i.e., direct current (DCO) and asymmetrically clipped optical (ACO) orthogonal frequency division multiplexing (OFDM). Through extensive numerical results, it is demonstrated that the suggested adaptive receiver outperforms the conventional PIN PD and SPAD array receivers in terms of bit error rate (BER) and achievable data rate.