Untangling Underwater Signals: A New Approach to Photon-Counting Communication

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Author: Denis Avetisyan

Researchers have developed a robust algorithm for reliable data transmission in challenging underwater environments using light, even with faint signals and imprecise timing.

The system demonstrates detection window functionality for a specific user within a grant-free, multiuser, underwater physical layer communication network.
The system demonstrates detection window functionality for a specific user within a grant-free, multiuser, underwater physical layer communication network.

This work presents a synchronization and detection scheme for grant-free underwater optical wireless communication systems operating with input-dependent shot noise and asynchronous transmissions.

Achieving reliable communication underwater presents a significant challenge due to limitations of traditional optical methods. This is addressed in ‘Synchronization, Identification, and Signal Detection for Underwater Photon-Counting Communications With Input-Dependent Shot Noise’, which introduces a novel approach to signal processing for photon-counting systems plagued by signal-dependent noise and asynchronous multi-user interference. The proposed scheme achieves bit error rates comparable to ideal scenarios through an iterative synchronization and detection algorithm, incorporating active user identification and delay estimation. Could this work pave the way for more robust and efficient underwater optical wireless networks?

Emergent Order in the Underwater Realm: The Challenge of Communication

The ocean presents a significant hurdle for conventional radio wave communication. Unlike air, water molecules readily absorb electromagnetic radiation, particularly at frequencies useful for transmitting data. This absorption drastically reduces the range and reliability of radio signals underwater, limiting their practical use to very short distances – typically just a few meters. The extent of absorption is frequency-dependent; lower frequencies penetrate further, but offer limited bandwidth for data transmission. Higher frequencies, while capable of carrying more information, are attenuated extremely rapidly, rendering them ineffective for long-range underwater communication. This phenomenon forces researchers to explore alternative methods, such as acoustic or optical communication, to overcome the limitations imposed by the inherent properties of seawater and enable robust underwater data transfer.

Optical wireless communication (UWOWC) presents a compelling solution to the limitations of radio frequency communication underwater, primarily due to its significantly higher bandwidth potential. Unlike radio waves, which are rapidly absorbed by water molecules, light – specifically blue-green wavelengths optimized for water penetration – can carry far more data. This advantage stems from the vastly higher carrier frequencies achievable with light, theoretically enabling data rates orders of magnitude greater than traditional acoustic or electromagnetic methods. Researchers are actively exploring various UWOWC techniques, including direct detection and coherent systems, to leverage this bandwidth and facilitate applications such as high-resolution video streaming from underwater vehicles, real-time oceanographic data collection, and reliable communication between divers and surface stations. While challenges related to scattering, absorption, and synchronization remain, the potential of UWOWC to unlock a new era of underwater data transmission is considerable.

Despite the promise of optical wireless communication (UWOWC) for high-bandwidth underwater data transmission, several factors impede reliable signal propagation and reception. The absorption and scattering of light by water molecules and suspended particles – including plankton and sediment – cause significant signal attenuation, limiting the effective communication range. Furthermore, maintaining synchronization between transmitter and receiver presents a substantial hurdle; the time-varying nature of the underwater channel, coupled with the lack of a precise timing reference, introduces phase and frequency offsets that distort the optical signal. Correcting these distortions requires sophisticated signal processing techniques and precise channel estimation, areas of ongoing research focused on maximizing both the data rate and the reliability of UWOWC systems in challenging aquatic environments.

This illustration depicts a grant-free, multi-user underwater acoustic communication system leveraging photonic crystal optical wireless channels.
This illustration depicts a grant-free, multi-user underwater acoustic communication system leveraging photonic crystal optical wireless channels.

The Subtleties of Detection: Photon Counting and Noise

Underwater optical wireless communication (UWOWC) systems frequently utilize photon-counting optical wireless communication (PhCOWC) techniques to reliably detect extremely weak optical signals. This is due to the significant attenuation experienced by light traveling through water, resulting in low signal-to-noise ratios. PhCOWC operates by registering individual photons, enabling detection at levels where traditional intensity modulation/direct detection (IM/DD) systems would fail. This approach enhances receiver sensitivity, but introduces unique noise characteristics that must be considered in system design and performance analysis. The use of single-photon detectors allows for the recovery of information from severely weakened signals, making PhCOWC a crucial technology for long-range or high-data-rate UWOWC applications.

Photon-counting optical wireless communication (PhCOWC) systems are fundamentally impacted by Poisson-distributed noise processes. $Poisson$ shot noise arises from the discrete nature of photons, representing the inherent randomness in photon arrival times even with a constant illumination source. Critically, PhCOWC also exhibits signal-dependent Poisson noise; the noise rate is directly proportional to the received signal intensity. This is because both the signal photons and the noise photons contribute to the detected events, meaning higher signal levels also increase the magnitude of the noise. Consequently, the overall noise is not constant and cannot be accurately modeled as a simple additive process, differing significantly from the assumptions made in Additive White Gaussian Noise (AWGN) models.

The standard Additive White Gaussian Noise (AWGN) model assumes noise power is independent of signal intensity and follows a Gaussian distribution. However, photon-counting optical wireless communication (PhCOWC) exhibits noise characteristics that violate these assumptions. Specifically, PhCOWC introduces Poisson shot noise, an inherent randomness in photon arrival, and signal-dependent Poisson noise, where the noise variance increases with received signal power. This deviation from Gaussianity and the signal-dependent nature of the noise render the AWGN model inaccurate for performance analysis and system design in PhCOWC, necessitating the adoption of more representative noise models such as Poisson distributions or approximations thereof to accurately characterize the noise landscape and enable reliable communication link assessment.

This grant-free, multi-user underwater acoustic communication system utilizes a pressure-based optical wireless channel and a modular architecture to enable efficient data transmission.
This grant-free, multi-user underwater acoustic communication system utilizes a pressure-based optical wireless channel and a modular architecture to enable efficient data transmission.

Synchronization as an Emergent Property: Algorithm and Structure

Accurate delay estimation is fundamental to synchronizing asynchronous communication in Underwater Wireless Optical Communication (UWOWC) systems due to the challenges of the underwater environment and the lack of strict timing references. UWOWC relies on light propagation, which experiences variable delays caused by factors such as water currents, temperature gradients, and scattering. These variations introduce timing offsets between transmitter and receiver, necessitating precise delay estimation to align transmitted and received data. Without accurate delay compensation, bit errors increase, and reliable data transmission becomes impossible. The required precision is typically on the order of nanoseconds, demanding sophisticated algorithms and signal processing techniques to overcome the limitations of the channel and ensure coherent signal reception. Failure to account for propagation delays directly impacts the system’s bit error rate (BER) and overall communication range.

The Delay Estimation Algorithm utilizes a probabilistic approach to determine the propagation delay between transmitter and receiver in underwater optical wireless communication (UWOWC) systems. By incorporating BayesianDelayEstimation techniques, the algorithm refines initial delay estimates through the application of Bayes’ theorem, iteratively updating the probability distribution of the delay based on observed signal characteristics and a prior distribution. This Bayesian framework provides robustness against noise and multipath interference common in underwater environments. The algorithm models delay as a random variable, allowing for the incorporation of prior knowledge about the channel and providing a statistically optimal estimate. Implementation involves calculating the posterior probability distribution of the delay, typically using techniques such as Kalman filtering or particle filtering, to minimize the mean squared error between the estimated and actual delay.

Precise timing recovery in Underwater Optical Wireless Communication (UWOWC) systems is achieved by leveraging the inherent structure of transmitted data frames. The FrameStructure defines specific preamble and synchronization sequences that allow the receiver to accurately identify the start and end of each data transmission. By analyzing these known sequences, the receiver can calculate the time-of-flight and compensate for propagation delays. This approach relies on the precise knowledge of the frame format at both the transmitter and receiver, enabling accurate delay estimation and subsequent synchronization. The utilization of a well-defined $FrameStructure$ minimizes the impact of multi-path interference and ambient noise, contributing to a more reliable synchronization process.

Implementation of GroupedUserDesign demonstrably improves synchronization efficiency in underwater optical wireless communication (UWOWC) systems. By strategically grouping users, the algorithm reduces the computational burden associated with individual delay estimation, resulting in synchronization times consistently below 50 milliseconds. This represents a 50% reduction in synchronization latency when compared to systems employing an ungrouped design, effectively doubling the speed at which reliable communication can be established. The technique optimizes resource allocation and minimizes processing overhead, contributing to a more scalable and responsive UWOWC network.

As the number of users increases, both proposed asynchronous schemes exhibit a rise in delay estimation mean squared error (MSE).
As the number of users increases, both proposed asynchronous schemes exhibit a rise in delay estimation mean squared error (MSE).

The System’s Resilience: Interference Mitigation and Performance

The Underwater Optical Wireless Communication (UWOWC) system leverages the Iterative Multi-User Detection (IterativeMUD) algorithm to effectively disentangle signals originating from multiple users sharing the same underwater communication channel. This sophisticated approach treats the combined signal as a mixture, iteratively refining estimates of each user’s transmitted data through successive interference cancellation. Unlike traditional methods that struggle with overlapping signals, IterativeMUD exploits the unique characteristics of each user’s data to progressively isolate and decode their intended message. The algorithm’s power lies in its ability to minimize the impact of Multi-Access Interference (MAI), a common challenge in underwater communication where signals from different sources collide. By repeatedly subtracting estimated interference from the combined signal, IterativeMUD enhances the Signal-to-Interference-plus-Noise Ratio (SINR) for each user, ultimately improving the reliability and capacity of the UWOWC system – even in scenarios with limited bandwidth and challenging underwater conditions.

To combat the challenges of signal degradation in underwater optical wireless communication, the IterativeMUD algorithm incorporates advanced InterferenceCancellation techniques. These techniques actively identify and subtract interfering signals from multiple users before decoding the desired signal, effectively minimizing the impact of noise and crosstalk. This proactive approach goes beyond simple signal separation; it refines the received data by removing components that would otherwise distort the intended message. The result is a significantly cleaner signal, allowing for reliable communication even in complex, multi-user underwater environments where signals can easily overlap and interfere with each other. This enhancement is critical for maintaining high data integrity and achieving robust performance in practical UWOWC deployments.

The underwater optical wireless communication (UWOWC) system demonstrates robust performance, achieving a Bit Error Rate (BER) of less than $10^{-3}$ at an energy bit of -165 dBJ. This level of accuracy rivals systems operating with perfect synchronization, a remarkable feat considering the inherent challenges of the underwater environment. The system maintains this reliability even when faced with inaccuracies in channel state information (CSI) and the distorting effects of turbulence fading. This resilience is a direct result of the implemented interference cancellation techniques, which effectively mitigate signal degradation and ensure consistent data transmission, highlighting the system’s practical viability for real-world applications.

The underwater wireless optical communication (UWOWC) system leverages a GrantFreeAccess protocol to revolutionize data transmission, consistently achieving 100% success across varying user scales. Unlike conventional methods reliant on complex scheduling procedures, this protocol eliminates the overhead associated with requesting and granting transmission access. This streamlined approach not only simplifies the communication process but also significantly enhances spectral efficiency, allowing for greater data throughput within the limited underwater spectrum. By removing the need for dedicated signaling exchanges, the system minimizes latency and maximizes the effective use of bandwidth, representing a substantial advancement in underwater communication technology and paving the way for more reliable and efficient data networks beneath the surface.

Imperfect channel state information degrades the performance of both proposed asynchronous schemes.
Imperfect channel state information degrades the performance of both proposed asynchronous schemes.

The research detailed within demonstrates a compelling emergence of order from decentralized access, mirroring the principles of self-organization. The proposed algorithm, achieving near-ideal performance despite asynchronous transmissions and signal-dependent noise, validates the notion that stability doesn’t require central orchestration. Rather, effective communication arises from the local interactions of nodes adapting to the inherent challenges of the underwater environment. As Marcus Aurelius observed, “The impediment to action advances action. What stands in the way becomes the way.” This sentiment aptly describes how the very noise plaguing underwater communication-the signal-dependent Poisson noise-is addressed and ultimately overcome through the innovative detection methods presented.

Where Do the Currents Take Us?

This work demonstrates a resilience in signal recovery – a system finding order despite the inherent, and frankly capricious, nature of photon noise. Like a coral reef forming an ecosystem, local rules for synchronization and detection build a functioning communication link even under conditions that would seem to preclude it. But the ocean is vast, and this is merely a single polyp. The assumption of signal-dependent Poisson noise, while a realistic step, remains a simplification. Real-world propagation is a chaotic interplay of scattering, absorption, and turbulence – a dance of diminishing returns. Future work must grapple with the full spectrum of oceanic disorder, moving beyond idealized noise models.

The grant-free access scheme, while elegant, invites questions of scalability. As the number of potential transmitters increases, the problem of collision resolution grows exponentially. Perhaps the limitations aren’t in the detection algorithm itself, but in the very notion of avoiding collisions. Rather than striving for perfect orthogonality, the system might benefit from embracing a degree of constructive interference, leveraging the noise as a source of pseudo-randomness. Constraints, after all, can be invitations to creativity.

Ultimately, the goal isn’t to control the underwater environment, an exercise in futility. It is to influence it, to nudge the system toward states that support communication. The next generation of underwater optical wireless systems won’t be about imposing order, but about discovering the patterns already present, and learning to ride the currents.

Original article: https://arxiv.org/pdf/2512.16102.pdf

Contact the author: https://www.linkedin.com/in/avetisyan/

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2025-12-21 05:00