Spatially resolved equalization and forward error correction for multimode fiber links

Recently, the demand for reliable and high-speed wireless communication has rapidly increased. Orthogonal frequency division multiplexing (OFDM) is a modulation scheme that is the newest competitor against other modulation schemes used for this purpose. OFDM is mostly used for wireless data transfer, although it may also be used for cable and fiber optic connections. However, in many applications, OFDM suffers from burst errors and high bit error rates. This paper presents the utilization of a helical interleaver with OFDM systems to efficiently handle burst channel errors and allow for Bit Error Rate (BER) reduction. The paper also presents a new interleaver, FRF, the initial letters of the authors’ names, for the same purpose. This newly proposed interleaver summarizes our previous experience with many recent interleavers. Fast Fourier transform OFDM (FFT-OFDM) and Discrete Wavelet Transform OFDM (DWT-OFDM) systems are used to test the efficiency of the suggested scheme in terms of burst channel error removal and BER reduction. Finally, the general complexity of the FRF interleaver is different from that of the helical interleaver in terms of hardware requirements. The performance of the proposed scheme was studied over different channel models. The obtained simulation results show a noticeable performance improvement over the conventional FFT-OFDM and the FFT-OFDM systems with the helical interleaver. Finally, the disadvantage of the proposed FRF interleaver is that it is more complex than the helical interleaver.

Effect of the incident angle of a transmitting laser light on the coverage of a NLOS-FSO network

Reinforcement learning-based automated modulation switching algorithm for an enhanced underwater acoustic communication

The rapid growth of user density and heterogeneous service requirements in 5G and emerging 6G networks has intensified multi-user interference, particularly in power-domain non-orthogonal multiple access (PD-NOMA) systems. Conventional successive interference cancellation (SIC) techniques suffer from error propagation and performance degradation under imperfect channel conditions, limiting their reliability in practical deployments. This paper proposes a deep learning–based interference cancellation framework that combines Convolutional Neural Networks (CNNs) and Bidirectional Long Short-Term Memory (BiLSTM) networks for end-to-end signal detection in downlink NOMA systems. The proposed model exploits CNN layers to extract spatial interference features from complex-valued received signals, while BiLSTM layers capture bidirectional temporal dependencies caused by channel fading and symbol correlation. Unlike traditional SIC-based receivers, DL-NOMA-CancelNet directly reconstructs user signals without explicit channel estimation or manual interference subtraction. Simulation results obtained using MATLAB under Rayleigh fading and AWGN conditions demonstrate that our framework significantly outperforms conventional Least Squares (LS), Minimum Mean Square Error (MMSE), and single-network deep learning detectors. Specifically, this method achieves up to an 8–10× reduction in bit error rate (BER) across a wide signal-to-noise ratio (SNR) range, while maintaining low inference latency and moderate model complexity. These results confirm that our work provides a robust and scalable solution for interference mitigation in future 5G/6G downlink NOMA systems, particularly for ultra-reliable low-latency communications (URLLC) and massive machine-type communications (mMTC).

Modern cellular systems rely on high-capacity and low-latency optical networks to meet ever-increasing data demands. Centralized Radio Access Network (C-RAN) architectures offer a cost-effective approach for deploying mobile infrastructures. In this work, we propose a flexible and cost-efficient fronthaul topology that combines Wavelength Division Multiplexing (WDM) passive optical networks (PONs) with free-space optical (FSO) links. To enhance overall system performance, we introduce Low-Density Parity Check (LDPC) decoding, which provides robust error-correction capabilities against atmospheric turbulence and noise. Our system transmits 20 Gbps, 16-QAM intensity-modulated orthogonal frequency-division multiplexing (OFDM) signals, achieving a substantial reduction in bit error rate (BER). Numerical results show that the proposed WDM-PON-FSO architecture, augmented with LDPC decoding, maintains reliable transmission over 2 km under strong turbulence conditions.

Digital Video Broadcasting-Terrestrial second generation (DVB-T2) systems are increasingly deployed for high quality terrestrial broadcasting. However, low Signal-to-Noise Ratio (SNR) conditions in urban and fringe coverage areas pose significant challenges, resulting in elevated Bit Error Rates (BER) and degraded service reliability. Forward Error Correction (FEC) techniques, particularly Low-Density Parity-Check (LDPC) and Bose Chaudhuri Hocquenghem (BCH) codes, play a crucial role in mitigating transmission errors and ensuring robust communication. This study investigates a systematic approach to optimizing LDPC and BCH FEC schemes to enhance transmission reliability and minimize BER under low-SNR conditions in DVB-T2 networks. Using simulation-based analyses, the study evaluates multiple LDPC code rates (e.g., 1/2, 2/3, 3/4) in combination with BCH codeword lengths and error-correcting capabilities. Results indicate that an optimized LDPC (64800, 32400) configuration combined with a BCH (255, 239) code significantly reduces BER, achieving approximately 10⁻⁵ at an SNR of 2 dB, compared to a BER of 10⁻³ using standard DVB-T2 FEC configurations. Additionally, iterative decoding algorithms for LDPC were fine-tuned to balance convergence speed and error correction performance, demonstrating a 25% reduction in decoding iterations without compromising reliability. The analysis also explores trade-offs between redundancy, throughput and latency, highlighting the practical considerations for real-world deployment. The findings underscore that strategic optimization of LDPC/BCH FEC parameters is critical for maintaining broadcast quality in low-SNR scenarios. By enhancing error resilience and reducing BER, the proposed approach improves signal integrity, supports consistent reception in fringe areas and maximizes spectrum efficiency. This work provides a foundation for adaptive FEC strategies in future DVB T2 systems, enabling broadcasters to deliver reliable high-definition content even under challenging channel conditions.

Multi-Gb/s high-speed links face significant challenges in keeping up with the increase in desired data rates. In the evaluation of achievable data rates, it is necessary to include both link-specific noise sources and implementation driven constraints. We construct models of these noise sources and constraints in order to estimate the theoretical limits of typical high-speed link channels. In order to estimate the data rates of practical baseband architectures, we solve the power constrained optimal linear precoding problem and formulate a bit-error rate (BER) driven optimization, including all link-specific noise sources. The problem is shown to be quasiconcave, hence, a globally optimal solution is guaranteed. Using this optimization framework, we show that practical data rates are mainly limited by inter-symbol interference (ISI) due to complexity constraints on the number of precoder and equalizer taps. After these constraints are removed, we further show that slicer resolution and sampling jitter are limiting the higher bandwidth utilization provided by multi-level modulations. Better circuits are needed to improve the bandwidth utilization to more than 2bits/dimension in baseband.

In optical fiber communication, recent advances in multiple-input and multiple-output (MIMO) systems using space-division multiplexing have helped achieve higher spectral efficiency and data rates. Propagating higher-order modulation formats over MIMO systems further strengthens the capacity of the transmission link. In the optical-MIMO system, the dispersion impairments originating from a 1.4 km long multi-mode fiber (MMF) are mitigated using the proposed joint-transceiver equalization technique. A numerical convex optimization algorithm is used to compute and optimize the pre- and post-equalization (PPE) coefficients jointly restricted by cost and power budgets. The potential of the proposed joint-PPE technique is tested on an MMF link, which is severely degraded by dispersion compared to a single-mode fiber channel. From the experimental results, the average optical received power gain necessary to reach 10−4 bit-error rate is improved by nearly 2.5 dB using the joint-PPE compared to the post-equalization only based on the minimum mean-squared error principle. When the efficiency of the conventional zero-forcing (ZF) principle-based PPE and the joint-PPE is compared, the joint-PPE scheme outperforms the ZF-PPE by approximately 1.5 dB. The enhancement in the transmission quality is observed with experimentally measured eye diagrams using the joint-PPE scheme. Under the analyzed scenarios, computer simulation also confirms the hypothesis, which establishes the effectiveness of the proposed joint-transceiver equalization over the conventional ZF-PPE scheme. Moreover, the simulated performance benefits of the joint-PPE are evaluated using the singular value decomposition (SVD) technique. Improvement of ≈3.86 dB in the average optical received power gain required to reach 10−4 bit-error rate is witnessed with the PAM-4 format. Overall, the joint-transceiver equalization technique is proven to be beneficial in optical MIMO systems.

In this article, we explore the use of neural networks (NNs) to enhance the performance evaluation of Universal Filtered Multi-Carrier (UFMC) systems, a key technology for modern communication networks such as 5G and beyond. Traditional methods of evaluating the Bit Error Rate (BER) and system efficiency in UFMC system can be computationally intensive and less accurate under dynamic conditions. To address these challenges, we propose a NN based approach that not only improves the accuracy of BER prediction but also significantly optimizes the system's overall efficiency. Channel state estimation (CSE) plays a major role for UFMC system to address the phenomenon of multipath channel fading. In order to achieve a high data rate using UFMC technology, it is necessary to have an effective CSE and very accurate signal detection. Recently, there has been significant interest in utilizing deep learning (DL) to enhance channel estimations. This article introduces a new method for channel estimation (CE) in UFMC system. The suggested approach utilizes DL models to improve the CE. For the UFMC system, we propose a detector based on bidirectional long short-term memory (Bi-LSTM). To identify the transmitted symbols, the suggested detector uses DL training data directly. Currently, a significant drawback of UFMC systems is the presence of a high peak-to-average power ratio (PAPR). The approach aims to reduce the BER and enhances the efficiency of the UFMC system. This is achieved by dynamically setting the constellation mapping and symbol damping on each subcarrier and sub-symbol. The results illustrate that the proposed model can accurately and efficiently recognize UFMC signals. The suggested model is being compared to Least Square (LS), LSTM, and Minimum Mean Square Error (MMSE) channel estimators. Through extensive simulations, our results demonstrate that the NN model reduces BER and enhances efficiency. The proposed model gives more effective performance in terms of enhanced efficiency and reduction of BER. The findings offer valuable insights for the design and optimization of next-generation communication systems, where accurate and efficient performance evaluation is critical.

This work details the design of a plastic fiber link in 28-nm CMOS, operating in two adjacent bands centered on 117.5 and 152.5 GHz. Each band supports multilevel (PAM-4) intensity-modulated signaling, which can be detected noncoherently, obviating the need for carrier recovery and phase alignment. A rectification-based detector is proposed to support linear noncoherent demodulation. A manifold diplexer is designed on-chip to increase the level of integration. The dual-band link achieves data rates up to 100 Gb/s over a fiber length of 3 m at a power consumption of 574 mW and a bit error rate (BER) better than 2.2e-4, corresponding to the standardized KP4 forward error correction (FEC) threshold. With only the low-band (LB) circuitry active, the link reaches up to 50 Gb/s over a distance of 7 m at a degraded BER of 2.2e-3 and up to 10 Gb/s over 11 m at a BER of 1e-6, representing the highest reported data rates for these link lengths. An energy efficiency reaching as low as 0.8 pJ/bit/m is reported for the 7-m case.

An adaptive optics correction arising from the sum of tilt, focus, astigmatism and coma components is applied to the bit error rate (BER) of M-ary pulse-position-modulated (PPM) oceanic optical wireless communication systems. The percentage reduction in BER is evaluated versus the oceanic turbulence parameters of the ratio of temperature to salinity contributions to the refractive index spectrum, the rate of dissipation of mean-squared temperature and that of kinetic energy per unit mass of fluid under different data bit rates, avalanche photodiode (APD) average current gains and the M values of the M-ary PPM. Our findings indicate that the percentage reduction in BER becomes larger when the ratio of temperature to salinity contributions to the refractive index spectrum or the rate of dissipation of mean-squared temperature or the data bit rate or the M value of the M-ary PPM is smaller, and when the rate of dissipation of kinetic energy per unit mass of fluid or the APD average current gain is larger.

The downlink communication channel from high-altitude platform (HAP) to high-speed train (HST) in the Ka-band is a slowly time-varying Rician distributed flat fading channel with 10-25 dB Rician K factor. In this respect, the received signal is mainly affected by the Doppler shift of the line-of-sight (LOS) link. In order to increase receiver performance, we propose to firstly compensate the Doppler shift of the received signal before least-squares (LS) adaptive filtering is pursued. Implementing the proposed method requires a priori knowledge of the time-varying phase of the LOS component. This is justified since signalling between the train and the controller exists such that the train velocity and location are predictable. Implementing the proposed method to the recursive LS (RLS) received beamforming algorithm shows reduction of mean square error (MSE) and bit error rate (BER).

The performance of forward error correction (FEC) based on Reed-Solomon coding is analyzed experimentally for a burst-mode upstream channel within a passive optical network (PON) testbed. During this analysis, the upstream FEC performance is impaired by inducing correlated and localized errors within the burst through the injection of optical transients. These transients emulate the optical signal variation associated with the add-and-drop events of wavelength channels within a long-reach optical link based on a chain of erbium doped fiber amplifiers (EDFAs). The robustness of the FEC has been analyzed by measuring the post-FEC bit error rate (BER) as a function of the amplitude of the emulated transients and their delay with respect to the transmitted bursts. A margin of approximately 4dB is demonstrated for the transient amplitude before the FEC degradation. Furthermore, while the post-FEC BER is strongly degraded by the emulated transients, the pre-FEC BER stays below the FEC threshold, demonstrating the importance of measuring the post-FEC BER in order to correctly characterize the FEC performance in PON upstream channels affected by optical transients.

Non Orthogonal Multiple Access (NOMA) is the scheme that will change the course of resource allocation strategy in the Fifth generation (5G) technology which is knocking at the door steps. Increase in data rate is need of the hour and different multiple access schemes are being used by the foregoing generations for providing resources to the users. Bandwidth saving can be the probable solution to increase the data rate and the Fourth generation (4G) employing Orthogonal Frequency Division Multiple Access (OFDMA) with orthogonal subcarriers being given to different subscribers serve the proposal leading to enormous usage of applications involving very high data rates such as High definition video conferencing, online gaming etc. The need of further increase in data rates has led to development of more spectral efficient systems through which the scarce resource can be saved and thus will be utilized for increase in per unit spectrum leading to high capacity. This possibility can be fulfilled by allocating the same resource to multiple subscribers at the same time but with different power levels which rely on successive interference cancelation (SIC). This scheme is called NOMA which is very well suited for 5G. As the bandwidth is same for multiple users, the data rate offered by each user has to be well confined within the channel capacity. Outage results if the channel capacity is less than the data rate. This paper provides an overview of NOMA and the outage probabilities in both Uplink and Downlink scenarios.

The expanding capacity of today's memory cards and increasing speed of processors have created demands for high data rate interfaces between memory cards and processors. Compared to conventional contact pins, wireless interfaces have received tremendous interest for reasons of more convenience, higher reliability, and higher data rate. Two major types of near-field wireless communication techniques using capacitive coupling and inductive coupling channels have been investigated. Tens of Gb/s/ch is achieved using both methods with a communication distance of tens of microns in TCI (thru-chip-interface) applications [1–2]. However, when the communication distance denters the mm range in such applications as non-contact memory cards, the sizes of capacitors or inductors must be up scaled to detect enough electrical flux or magnetic flux, whose magnitude decay as 1/dn (n>1). As a result, the self-resonance frequency f SR is reduced significantly, which becomes the dominant limiting factor for the achievable data rate, since the maximum data rate is usually chosen as 1/2 or 1/3 of f SR in order to avoid signal peaking [3]. Although multi-channel solutions are viable to increase the total data rate, complex systems are required to address the skew issues in synchronization, and low area efficiency is resulted to reduce crosstalk interferences as shown in Fig. 28.3.1.