The research, led by Babak Sadeghi and Seyed Mohammad Sajad Sadough of Shahid Beheshti University in Tehran together with Khadijeh Ali Mahmoodi of Université de Versailles Saint-Quentin-en-Yvelines, tackles pointing errors in VLC systems assisted by intelligent reflecting surfaces, or IRSs. These surfaces, sometimes called optical smart mirrors, consist of electronically controllable reflective elements that can steer an incoming light beam toward a receiver whose direct line of sight has been blocked. In a hospital ward, where beds, curtains, equipment carts, and people constantly interrupt the optical path between a ceiling LED and a photodetector, such NLoS capability is what turns VLC from a fragile novelty into a practical network layer.

The catch is geometry. A conventional line-of-sight VLC link has one beam, one transmitter, and one receiver, so misalignment comes from transmitter jitter and receiver orientation fluctuations. An IRS-assisted link is a cascaded transmitter-IRS-receiver chain, and every stage adds its own misalignment budget: the transmitter must accurately illuminate the designated IRS unit, the IRS controller must steer each mirror element with sufficient precision, the receiver’s position and orientation must be known, and the reflective elements themselves carry fabrication imperfections. Because the law of reflection doubles the angular deviation introduced at the surface, small controller errors translate into disproportionately large beam displacements at the photodetector.

To capture all of this in one tractable model, the team made a set of standard but consequential assumptions. Each angular error component is treated as an independent zero-mean Gaussian random variable, and because the horizontal displacement components along the two receiver-plane axes are then independent and identically distributed, the radial beam displacement follows a Rayleigh distribution. From this foundation the authors derived closed-form expressions for the composite pointing-error variance, the average received optical power, the electrical signal-to-noise ratio, and the outage probability, for both the direct and the reflected link. The received-power derivation exploits the circular symmetry of the photodetector aperture, transforming the two-dimensional surface integral into polar coordinates and evaluating it with the modified Bessel function of the first kind, which yields a compact power-loss factor that depends on the beam waist, the detector radius, and the displacement statistics.

The numerical results are striking. Under the study’s nominal parameters, which include a 5-watt LED transmitter, a 100-element IRS with 0.9 reflectivity, and a 10 dB SNR threshold, the composite pointing-error variance of the IRS-assisted link is roughly 3.5 to 4 times higher than that of the conventional LoS link. This translates into an SNR penalty of approximately 3 to 5 dB under practical conditions. In the direct link, receiver orientation fluctuations dominate the error budget, contributing nearly 64 percent of the total variance. In the IRS-assisted configuration the picture is more distributed: localization uncertainty alone accounts for about 40 percent, with IRS controller inaccuracies and fabrication imperfections adding noticeable further contributions.

The outage behavior is where the trade-off becomes most visible. Outage probability, defined as the chance that the instantaneous SNR falls below the threshold required for reliable communication, rises steeply with beam displacement in both configurations, but the slope is markedly steeper for the reflected path. For small radial displacements both links keep outage probabilities low, around 0.05. As displacement grows to an intermediate value, the LoS link reaches an outage probability of roughly 0.14 while the IRS-assisted link climbs to about 0.20. At larger displacements the gap widens further, to approximately 0.38 versus 0.55. The exponential dependence of outage on the ratio of displacement to beam width means that even modest increases in misalignment can sharply erode reliability, particularly on the cascaded path.

The authors validated their framework against Monte Carlo simulation with 100,000 independent realizations, and the analytical SNR curves track the simulated points closely across the entire range of radial displacements. Minor deviations at large displacements are attributed to the finite number of realizations and the heightened sensitivity of collected optical power under severe misalignment. This agreement matters, because it confirms that the Gaussian error model and the Rayleigh displacement statistics faithfully capture the behavior of practical IRS-assisted VLC links, giving system designers a closed-form tool rather than a purely simulation-based workflow.

What does this mean for hospitals? The study does not argue against IRS deployment; on the contrary, it frames the technology as essential for restoring connectivity whenever the direct optical path is obstructed, which in a busy ward is most of the time. Instead, the findings identify where engineering effort should be concentrated. Accurate user localization emerges as the single largest contributor to the IRS link’s error variance, followed by the precision of IRS beam steering and the manufacturing quality of the reflective elements. The authors conclude that these three factors, together with effective misalignment mitigation, are the primary determinants of link reliability in IRS-assisted VLC deployments.

The work also fills a genuine gap in the literature. Previous studies of IRS-assisted VLC have concentrated on frequency-domain channel characterization, beam-steering design, resource allocation, and performance under idealized alignment, while the statistical characterization of pointing errors in cascaded optical links had received comparatively little attention. By jointly incorporating transmitter jitter, receiver orientation fluctuations, controller inaccuracies, localization uncertainty, and fabrication imperfections into a single statistical formulation, the framework offers the first unified closed-form treatment of the problem, according to the authors.

As hospitals move toward light-based wireless networks that promise interference-free operation alongside life-critical equipment, this study provides a sober calibration of expectations. The reflected beam that keeps a patient monitor connected when a nurse walks past is inherently more fragile than the direct beam it replaces, and the penalty is now quantified: a 3-to-5 dB SNR degradation and a variance three to four times higher, unless localization and steering precision keep pace. For a technology whose value proposition is reliability in the most demanding indoor environments, that arithmetic is not a deterrent but a design specification.

Subject of Research: Pointing error analysis in intelligent reflecting surface-assisted visible light communication systems for indoor hospital environments

Article Title: Pointing error evaluation in IRS-assisted VLC systems for indoor hospital environments: a comparative analytical study

Article References: Pointing error evaluation in IRS-assisted VLC systems for indoor hospital environments: a comparative analytical study. (n.d.). https://doi.org/10.3389/frcmn.2026.1908983

Image Credits: AI Generated

DOI: 10.3389/frcmn.2026.1908983

Keywords: visible light communication, intelligent reflecting surfaces, pointing error, outage probability, signal-to-noise ratio, hospital networks, non-line-of-sight, Rayleigh distribution, channel modeling, optical wireless communication, beam steering, indoor connectivity

Each of the four ingredients addresses a specific bottleneck of the ultra-massive machine-type communications scenario that is expected to define 6G. Intelligent reflecting surfaces, or IRS, are essentially walls of tiny, nearly passive elements that can be tuned to steer radio waves in chosen directions, boosting signal strength along useful paths and shielding receivers from interference. Because they involve no power-hungry amplifiers or radio chains, they offer a cheap way to reshape the propagation environment around energy-constrained Internet of Things devices. Simultaneous wireless information and power transfer, or SWIPT, exploits the same radio signals to deliver both data and energy, allowing a receiving device to split the incoming wave so that part of it is decoded as information and part is harvested as electrical power. For sensors that cannot easily be recharged or wired to the grid, this dual function can be transformative.

The other two technologies attack the problem from the network side. NOMA allows several users to share the same time, frequency and code resources by superimposing their signals at different power levels and separating them at the receiver through successive interference cancellation, dramatically improving spectral efficiency. Full-duplex transmission lets a node transmit and receive simultaneously on the same frequency, in principle doubling spectral efficiency, although it must contend with powerful self-interference from its own transmitter. Combining these elements, the proposed scheme creates a full-duplex NOMA system in which a base station serves a downlink user while, at the same time, energy-constrained uplink devices harvest power from the downlink signal, assisted by an IRS that strengthens both directions of the exchange. Earlier work by the same authors had demonstrated the promise of such a combination for 6G ultra-massive machine-type communications under ideal assumptions; the new study confronts the harder, more realistic case.

That harder case is imperfect channel state information, or CSI. Every intelligent beamforming and resource allocation decision in an IRS-assisted system depends on knowing precisely how signals travel from transmitter to surface and from surface to receiver. Yet IRS panels contain no active components, which means there is no easy way to insert pilots or measure the cascaded channels element by element. Estimating the channel of each individual reflecting element would impose a crushing signalling overhead, so practical systems must work with estimates that carry error. If a design assumes perfect CSI and reality deviates even slightly, the promised quality of service for the downlink user can quietly collapse, and the harvested energy that uplink devices count on may never arrive. Robust design, in which performance guarantees hold for the worst possible channel error within a bounded uncertainty set, is therefore not a luxury but a necessity for IRS-assisted networks.

The researchers formulated the core problem as a worst-case uplink sum rate maximization: the goal is to maximize the total data rate achieved by the uplink NOMA devices in the most pessimistic allowable channel condition, subject to the constraint that the downlink user’s quality of service is always satisfied. This is a notoriously difficult non-convex optimization problem, made harder by the coupling between the beamforming vectors at the base station, the phase shifts applied by the IRS elements, and the power-splitting ratios that divide each received signal between energy harvesting and information decoding. Solving it exactly is mathematically intractable, so the authors constructed an alternating optimization algorithm that breaks the problem into manageable pieces, optimizing one set of variables at a time while holding the others fixed and iterating until convergence.

Each iteration relies on an arsenal of modern optimization techniques. The S-Procedure converts infinitely many worst-case constraints, one for every possible channel error, into tractable matrix inequalities. The penalty convex-concave procedure and successive convex approximation linearize the non-convex pieces of the problem around the current solution, yielding a sequence of convex subproblems that can be solved efficiently with standard tools. The Schur complement rewrites determinant-based matrix inequalities into forms that standard solvers can handle, while Generalized Petersen’s Lemma helps convert products of uncertain channel terms into expressions where the uncertainty can be bounded cleanly. Together, these methods produce a solution that is not merely a good guess, but one with built-in protection: no matter how the true channels wander within the assumed error bounds, the quality of service and the harvested energy requirements are guaranteed to hold.

The numerical studies accompanying the paper show that this robustness pays measurable dividends. Compared with benchmark schemes, the proposed design achieves a higher worst-case uplink sum rate, demonstrating that the joint tuning of IRS phase shifts, transmit beamforming and power splitting extracts more from the same spectrum and the same radiated power. More importantly, the robust scheme provides more practical and dependable results than its non-robust counterpart. When channel errors are injected into the simulations, designs built on perfect-CSI assumptions suffer degraded performance and occasional violations of the downlink quality-of-service constraint, whereas the robust design keeps its guarantees intact. The gap between the two widens as the uncertainty grows, underscoring that the extra mathematical machinery is not academic hair-splitting but the difference between a system that works in the lab and one that works in the field.

The implications reach well beyond one particular algorithm. The ultra-massive machine-type communications scenario envisions connection densities and energy constraints far beyond what cellular networks have ever handled, and the study argues that no single technology can meet them alone. IRS supplies coverage and signal gain without adding active infrastructure, SWIPT turns the network’s own transmissions into a power grid for its sensors, NOMA squeezes many connections into scarce spectrum, and full-duplex operation doubles the utility of every radio resource. Stacking the four, and making the stack resilient to imperfect channel knowledge, sketches a plausible blueprint for the machine-centric fabric of 6G, in which thousands of self-powered devices communicate reliably through intelligently steered reflections.

There remain formidable engineering hurdles before such systems reach commercial deployment, from scalable channel estimation for large IRS panels to the hardware cost of full-duplex self-interference cancellation. But by formulating the problem with bounded channel errors from the outset and proving that a computationally feasible algorithm can still maximize worst-case throughput, the researchers have moved the field closer to designs that survive contact with reality. For a 6G vision built on trillions of devices, that kind of robustness may prove to be the most valuable specification of all.

Subject of Research: A robust IRS- and SWIPT-assisted full-duplex NOMA transmission scheme designed for 6G ultra-massive machine-type communications with imperfect channel state information.

Article Title: Robust IRS and SWIPT Assisted Full-Duplex NOMA for 6G Networks

Article References: Goktas, M. B., Al-Basit, S. M., & Ding, Z. (2026). Robust IRS and SWIPT Assisted Full-Duplex NOMA for 6G Networks. Journal of Network and Systems Management, 34(4), Article 131. https://doi.org/10.1007/s10922-026-10099-6

Image Credits: AI Generated

DOI: 10.1007/s10922-026-10099-6

Keywords: 6G, intelligent reflecting surface, SWIPT, full-duplex communications, NOMA, imperfect channel state information, Internet of Things, ultra-massive machine-type communications, beamforming optimization, wireless power transfer, convex optimization, sum rate maximization