Laser-Diode LiFi With Diffused-Beam Optics: System-Level Modeling and a Cross-Validated ns-3 Simulation Framework

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Laser-Diode LiFi With Diffused-Beam Optics: System-Level Modeling and a Cross-Validated ns-3 Simulation Framework

arXiv:2608.10950v1 [eess.SP] 11 Aug 2026

Hussain Ahmad, Syed Muhammad Talha Gillani, Toheed Omer, and Saleem Aslam

Abstract—Laser diodes (LDs) promise an order-of-magnitude bandwidth advantage over light-emitting diodes for indoor optical wireless access, but reported prototype studies frequently leave the gap between hardware demonstrations and system-level performance unquantified. This paper develops a complete, reproducible system model of a diffused-beam LD LiFi transceiver— a 500-mW laser source beam-shaped by a holographic diffuser, an intensity-modulation/ direct-detection (IM/DD) receiver, and adaptive M -QAM signaling—and embeds it in two crossvalidated simulators: an open ns-3 module providing full-stack network simulation (channel, PHY, ARQ MAC, NetDevice, IP/UDP/TCP) and a Python link-level engine used for MonteCarlo validation of all analytical error models. Starting from a hardware prototype that transferred data, real-time voice, and images over a 14-m line-of-sight link, we identify and close the technical gaps typical of prototype-class reports: serial-interface throughput ceilings misread as optical-link capacity, absent noise modeling, unmeasurable error floors, and unexamined beamwidth/coverage trade-offs. The framework shows that the same optical front end, freed of its 2-Mbaud UART bottleneck and driven at its 250-MHz electrical bandwidth, supports 930 Mb/s net at 14 m under a 3.8×10−3 HD-FEC threshold with 16-QAM, scales to 1.86 Gb/s at 5 m with 256-QAM, and sustains on-off keying to 23.3 m; a 20◦ diffuser covers a 4.2-m-radius cell of a standard room at desk height. Network simulations over the ns-3 stack yield saturation goodput within 7% of the PHY line rate and sub-0.11-ms 99th-percentile latency at 70% load. All models, code, and figures are released for reproduction. Index Terms—Visible light communication, LiFi, laser diode, holographic diffuser, intensity modulation, direct detection, ns3, network simulation, adaptive modulation, optical wireless communication.

I. I NTRODUCTION HE radio spectrum below 300 GHz is a congested, regulated and increasingly contested resource, while the optical spectrum offers roughly 104 times more bandwidth, is license-free, and is naturally confined by opaque boundaries— an attractive property for both spatial reuse and physical-layer security [1]–[3]. LiFi extends visible light communication (VLC) from a point-to-point physical layer into a networked, multi-user wireless access technology [3], [4]. Within optical wireless, the choice of emitter fundamentally constrains the achievable rate. Phosphor-converted white LEDs are inexpensive and eye-safe, but their 3-dB electrical bandwidth of a few to a few tens of MHz limits single-emitter rates

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H. Ahmad, S. M. T. Gillani, T. Omer, and S. Aslam are with the Department of Electrical Engineering, Bahria University, Islamabad, Pakistan (e-mail: hussainbuic@gmail.com). Simulation code (ns-3 module and Python link-level engine) is available with this article.

and forces heavy spectral-efficiency engineering [5]–[7]. Laser diodes (LDs), by contrast, exhibit modulation bandwidths in the hundreds of MHz to GHz range and much higher electricalto-optical conversion linearity at high current densities; GaN LDs have carried 9 Gb/s over a single 450-nm channel [8], white-light LD lamps have delivered multi-Gb/s illuminationgrade links [9], [10], and LD-based underwater links have reached 1.5 Gb/s over 20 m [11], [12]. The principal objections to LDs—speckle, eye safety, and narrow beams— are addressed by diffusive beam shaping: a holographic diffuser converts the coherent beam into an extended, eye-safer Lambertian-like source with a designer-chosen half-angle [13]. This paper builds on a working LD-LiFi hardware prototype developed by the authors: a 500-mW laser source switched by an N-channel MOSFET driver fed from a CH340 USB– TTL serial bridge, beam-shaped by a holographic diffuser, and received by a photodiode/laser-sensor front end, with modulation and demodulation performed in MATLAB. The prototype transferred arbitrary data, real-time voice, and 69 × 71-pixel images over a 14-m indoor line-of-sight (LOS) link. Such prototype-class studies—common in the LiFi literature— demonstrate feasibility but typically leave four technical gaps that prevent their results from being extrapolated or reproduced: 1) Interface-limited throughput is conflated with link capacity. A serial bridge capped at 2 Mbaud bounds goodput at 1.6 Mb/s regardless of the optics; timingbased rate estimates taken at the application layer can exceed this by orders of magnitude and must not be attributed to the optical channel. 2) No noise model. Without shot- and thermal-noise budgets, the observation of “error-free” operation at one distance carries no information about margins, achievable modulation orders, or scaling. 3) No error-rate methodology. Short qualitative tests cannot resolve bit-error rates (BERs) at or below forward-errorcorrection (FEC) thresholds; a BER-versus-distance characterization requires either long measurements or a validated model. 4) Unexplored design space. The diffuser half-angle trades peak SNR against coverage; transmit power trades range against eye safety; modulation order trades rate against reach. None of these trade-offs can be quantified from a single hardware operating point.

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A. Contributions We close these gaps by lifting the prototype into a complete, validated system model and simulation framework: • Link model. A closed-form IM/DD link budget for diffused-beam LD LiFi: generalized-Lambertian LOS channel parameterized by the diffuser semi-angle, optical filtering and non-imaging concentration, shot plus TIA thermal noise, and Gray-mapped M -QAM/OOK error models against a 7%-overhead hard-decision FEC threshold (Sections IV–V). • An open ns-3 module. lifi implements the channel, PHY, stop-and-wait ARQ MAC, and NetDevice abstractions so that unmodified IPv4/UDP/TCP stacks, applications, and FlowMonitor instrumentation run over the optical link; mobility-model-driven geometry makes coverage and mobility studies native (Section VI). • Cross-validation. A Python link-level engine implements the identical equations and validates every analytical BER curve by Monte-Carlo simulation; the ns-3 test suite asserts numerical agreement between the two implementations to 0.1% (Section VI). • Quantified design space. BER/SNR/rate versus distance, power, and diffuser angle; room-scale coverage maps; image-transfer fidelity; and full-stack goodput/latency (Section VII). • Prototype forensics. A quantitative account of what the hardware prototype did and did not establish, including the UART ceiling analysis that reconciles applicationlayer rate estimates with the physical link (Section VIII). II. R ELATED W ORK Kahn and Barry’s treatment of indoor infrared links established the generalized-Lambertian LOS model and IM/DD noise analysis that underpin modern VLC link budgets [14]; Komine and Nakagawa adapted it to white-LED lighting [15], and Ghassemlooy et al. give a comprehensive modeling treatment [16]. Surveys position LiFi within optical wireless technologies [1], [2], [5], and IEEE 802.15.7 standardizes short-range optical PHY/MAC layers [17]. On the emitter side, LED links progressed from 3 Gb/s single µLED [6] to 10 Gb/s-class violet µLED OFDM [7], while LD links demonstrated 9 Gb/s QAM-OFDM at 450 nm [8], illumination-grade white lasing links [9], [10], real-time Gb/s LiFi transceivers [18], and long-reach underwater links [11], [12]. Zafar et al. argue the LD roadmap for gigabit-class VLC [13]. Ray-traced indoor studies quantify realistic mobile multi-gigabit environments [19], receiver-side innovations include µ-photodetectors [20] and organic detectors with neural equalization [21], and multi-user beam control has been demonstrated with compound-eye transmitters [22]. At the network level, ns-3 [23] is the reference discreteevent simulator for wireless protocol research, and VLC modules for LED links have been proposed [24]. To our knowledge, no published ns-3 module models laser-diode LiFi with diffuser-parameterized beam shaping, nor pairs the network simulator with an independently implemented, Monte-Carlovalidated link engine. This paper fills that gap and anchors the model to a physical prototype.

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III. S YSTEM A RCHITECTURE Fig. 1 shows the system. A data source feeds a digital modulator; the resulting intensity waveform switches the LD through a MOSFET driver. The coherent beam passes a holographic diffuser that (i) destroys spatial coherence, easing eye-safety constraints of the extended source [13], [25], and (ii) shapes the emission into an approximately Lambertian lobe of order m set by the semi-angle at half power Φ1/2 . At the receiver, a non-imaging concentrator and optical filter collect light onto a photodiode; a transimpedance amplifier (TIA) converts photocurrent to voltage; the demodulator recovers bits, protected by hard-decision FEC. The hardware prototype realized this chain at reduced scale: a CH340 USB–TTL bridge (maximum 2 Mbaud) drove the MOSFET gate, MATLAB performed (de)modulation offline, and a laser-sensor module served as receiver. The prototype verified end-to-end data, real-time voice, and image transfer at 14 m indoors. Section VIII quantifies exactly which performance claims that hardware can and cannot support. IV. O PTICAL C HANNEL AND R ECEIVER M ODEL A. LOS Channel Gain The diffused LD emission is modeled as a generalized Lambertian source of order ln 2 , (1) m=− ln cos Φ1/2 so that Φ1/2 = 60◦ gives m = 1 (ideal Lambertian) while Φ1/2 = 20◦ gives m = 11.14, concentrating power near boresight. For a receiver of physical area A at distance d, emission angle ϕ and incidence angle ψ, the DC channel gain is [14], [15]   (m + 1)A cosm ϕ T g(ψ) cos ψ, 0 ≤ ψ ≤ Ψ , s c 2πd2 H(0) =  0, ψ > Ψc , (2) where Ts is the optical filter transmission and the non-imaging concentrator of refractive index n and field-of-view semi-angle Ψc contributes g(ψ) =

n2 , sin2 Ψc

0 ≤ ψ ≤ Ψc .

(3)

The received optical power is Pr = H(0) Pt . B. Receiver Noise and SNR Direct detection converts Pr into photocurrent Iph = RPr with responsivity R. Over receiver bandwidth B, shot noise (including a background-light current Ibg ) and TIA thermal noise contribute 2 σsh = 2q (Iph + Ibg ) B, 4kB T 2 σth = B, Rf

(4) (5)

yielding the electrical SNR γ=

(RPr )2 2 + σ2 . σsh th

(6)

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Data / voice / image source

Modulation (OOK–256-QAM)

MOSFET LD driver

3

500-mW laser diode

Holographic diffuser Φ1/2

electrical

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electrical

Fig. 1. Diffused-beam LD LiFi transceiver architecture. In the hardware prototype the modulation/demodulation blocks run in MATLAB behind a CH340 USB–TTL bridge; in the simulation framework they are the LifiPhy abstraction driven at the LD’s full electrical bandwidth.

TABLE I S YSTEM PARAMETERS (P ROTOTYPE -D ERIVED D EFAULTS ) Meaning

Value

Pt Φ1/2 A R Ts n Ψc B Ibg T Rf FEC

transmit optical power diffuser semi-angle photodetector area responsivity filter transmission concentrator index receiver field of view electrical bandwidth background photocurrent receiver temperature TIA feedback resistance HD-FEC threshold / overhead

500 mW 20◦ –60◦ 1 cm2 0.6 A/W 0.9 1.5 70◦ 250 MHz 100 µA 298 K 10 kΩ 3.8 × 10−3 / 7%

Table I lists the parameter set, chosen to match the prototype’s components scaled to the LD’s full electrical bandwidth. With these values the link is background-shot-noise limited: at 14 m and Φ1/2 = 20◦ , Pr = 1.13 µW and γ = 17.3 dB. V. M ODULATION AND E RROR M ODELS The PHY supports OOK, BPSK, QPSK, and square 16/64-/256-QAM on an electrical subcarrier (DC-biased for unipolarity), all at symbol rate B. With Gray mapping, the standard electrical-domain error probabilities apply [16]: for √ √ OOK Pb = Q( γ), for BPSK Pb = Q( 2γb ), and for square M -QAM ! r  4  3γ 1 Pb ≈ . (7) 1 − √M Q log2 M M −1 A rate-(1 − ρ) hard-decision FEC with ρ = 7% overhead corrects any pre-FEC BER at or below 3.8×10−3 ; the net rate of modulation M is then Rnet = B log2 M (1−ρ) when Pb ≤ 3.8 × 10−3 and the link is in outage otherwise. The adaptiverate policy selects the highest-order modulation meeting the threshold. Every closed-form curve used in this paper is verified by Monte-Carlo simulation of at least 1.2 × 106 bits per point in the Python engine (Section VI); Fig. 2 overlays the MonteCarlo estimates (markers) on the analytical curves (lines).

 

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Fig. 2. BER versus Eb /N0 : analytical curves (lines) and Monte-Carlo validation (open markers, ≥ 1.2×106 bits/point). BPSK and QPSK coincide, as expected. The dashed line is the 3.8 × 10−3 HD-FEC threshold. Applications, IPv4/UDP/TCP, FlowMonitor (stock ns-3) LifiNetDevice LifiMac stop-and-wait ARQ lifi module LifiPhy SNR, BER→PER LifiChannel + LifiOpticalChannelModel

Mobility Models

Fig. 3. Architecture of the ns-3 lifi module. Geometry is read live from standard ns-3 mobility models, so coverage and mobility studies use stock ns-3 tooling.

PER = 1 − (1 − Pb )8L for an L-byte frame, and draws a Bernoulli outcome; overlapping receptions are treated as collisions. LifiMac implements stop-and-wait ARQ with bounded retries; LifiNetDevice exposes the link as a standard NetDevice, so IP stacks, traffic generators, and FlowMonitor run unmodified. Four example programs reproduce every scenario in this paper as CSV output.

VI. S IMULATION F RAMEWORK A. ns-3 Module

B. Cross-Validated Link Engine

Fig. 3 shows the module. LifiOpticalChannelModel evaluates (1)–(3) from the live positions and orientations of transmitter and receiver; LifiChannel delivers each frame to all attached PHYs with propagation delay d/c. LifiPhy computes (4)–(6) per reception, maps SNR to BER via the modulation catalogue, converts to packet error probability

An independent Python implementation of (1)–(7) provides Monte-Carlo BER validation, image-transfer experiments, and the network-level queueing model used for pre-study of the ns-3 scenarios. The ns-3 unit-test suite pins the C++ implementation to reference values exported from the Python engine (channel gain, Lambertian order, SNR, BER thresholds)

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Fig. 6. Pre-FEC BER versus distance for each modulation (Φ1/2 = 20◦ , B = 250 MHz). Crossings with the FEC threshold define maximum reaches: 8.0 m (256-QAM), 11.2 m (64-QAM), 15.9 m (16-QAM), and 23.3 m (OOK/QPSK).

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Fig. 4. Received optical power versus distance for four diffuser semi-angles (Pt = 500 mW). Narrower diffusion concentrates power near boresight: at 14 m, Φ1/2 = 20◦ delivers 1.13 µW versus 0.19 µW for 60◦ .



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Fig. 5. Electrical SNR versus distance at B = 250 MHz for the LD system (four diffuser angles) and a representative LED baseline (100 mW, 60◦ , 20 MHz). Dotted horizontals mark the SNRs required to reach the FEC threshold with OOK (8.5 dB) and 256-QAM (26.9 dB).

at 0.1% relative tolerance, guaranteeing that both simulators realize the same physics. This two-implementation strategy catches transcription errors that single-implementation studies cannot. VII. R ESULTS A. Link Budget Versus Distance and Beam Width Fig. 4 shows received power versus distance for Φ1/2 ∈ {20◦ , 30◦ , 40◦ , 60◦ }, and Fig. 5 the resulting SNR at full bandwidth. The 1/d2 LOS law and the (m + 1) cosm ϕ directivity together imply that halving the diffusion angle buys roughly 6–8 dB of boresight SNR: at 14 m the link clears the OOK FEC threshold by 8.8 dB with the 20◦ diffuser but falls 6.8 dB short with the 60◦ diffuser. The LED baseline— representative of a 100-mW, 20-MHz white-LED front end— remains usable only below 8 m even with adaptive signaling, quantifying the LD advantage at equal detector hardware.



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Fig. 7. Achievable rate versus distance: Shannon bound, adaptive M -QAM with 7% FEC overhead for the LD system and the LED baseline, and the hardware prototype’s UART-limited operating point (14 m, 1.6 Mb/s).

B. Error Rate and Achievable Rate Fig. 6 converts SNR to pre-FEC BER per modulation. The adaptive-rate staircase (Fig. 7) selects 256-QAM to 8.0 m (1.86 Gb/s net), 64-QAM to 11.2 m (1.40 Gb/s), 16-QAM to 15.9 m (930 Mb/s), QPSK to 23.3 m (465 Mb/s), and OOK as the long-reach floor (233 Mb/s). Two conclusions follow. First, the prototype’s 14-m demonstration sits comfortably inside the 16-QAM region: its optical front end, driven at full bandwidth, supports 930 Mb/s net at the demonstrated range—577× the UART-limited goodput actually measurable on the hardware. Second, the gap between the staircase and the Shannon bound (2.2–4.6 b/s/Hz at 5–20 m) bounds what higher-order constellations, OFDM bit-loading, or soft-decision FEC could still recover.

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Fig. 9. Simulated OOK eye diagrams after a first-order receiver of bandwidth B: (a) Rb = 0.5B leaves a fully open eye; (b) Rb = 2B closes it with intersymbol interference—the regime a bandlimited front end enters when pushed past its electrical bandwidth.

C. Signal Quality and Bandwidth–Rate Trade The Q-factor analysis (Fig. 8) reproduces the thesis’s distance/power sweeps under the validated noise model: at 14 m with the 20◦ diffuser, Q = 7.4, exceeding the Q = 6 (10−9 ) mark without FEC; the 60◦ diffuser requires either ∼4× the power or FEC assistance at the same range. Fig. 9 illustrates the bandwidth mechanism behind the rate–reach trade: driving a front end past its electrical bandwidth closes the eye through intersymbol interference, which is why the framework caps the symbol rate at B rather than extrapolating rate from timing measurements.

at 1.59 Mb/s (1500-B payloads) at 2 Mbaud. Applicationlayer estimates of the form R = N D/t—modulation-orderweighted payload over MATLAB-side elapsed time—can exceed this by orders of magnitude because t excludes serialization and buffering; the thesis’s reported 127 Mb/s is an estimate of this kind and should be read as a processing-rate figure, not link throughput. The framework replaces it with the defensible chain: measured 14-m error-free operation at UART rates ⇒ validated link model ⇒ 930 Mb/s net at 250-MHz bandwidth (Fig. 7). F. Image Transfer Fidelity

D. Coverage Fig. 10 maps SNR over the receiver plane of a standard room. The narrow diffuser produces a cell with > 40 dB SNR at the center—supporting 256-QAM—while the wide diffuser floods the room with 15–25 dB, supporting OOK/QPSK everywhere but higher orders only near the center. This is the quantitative form of the LiFi attocell design choice: dense high-rate cells versus uniform moderate-rate illumination [3], [22].

The thesis’s image experiment is reproduced bit-exactly (Figs. 12 and 13): the 69 × 71 test pattern is packed to bits, Gray-mapped, transmitted through the AWGN electrical channel, and reassembled. PSNR rises ∼5 dB per 4 dB of SNR until the error floor vanishes; with FEC, delivery is exact at every operating point on the adaptive staircase, which is how the framework turns the prototype’s qualitative ”image received” result into a quantitative fidelity specification. G. Full-Stack Network Performance

E. The Prototype’s Interface Ceiling Fig. 11 quantifies the serial bridge: 8N1 framing costs 20% of the line rate, protocol overhead the rest, capping goodput

Figs. 14 and 15 carry the link model to the transport level with 1500-B packets and stop-and-wait ARQ. Goodput saturates at 93–96% of the line rate (ACK overhead accounts

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Fig. 10. Desk-height (0.85 m) SNR maps of a 5 × 5 × 3-m room with a ceiling-mounted downward transmitter: (a) Φ1/2 = 20◦ yields a high-SNR cell with the OOK/FEC boundary (dashed) at ≈2.1-m radius; (b) Φ1/2 = 60◦ trades peak SNR for wall-to-wall moderate SNR.



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Fig. 11. Goodput of a CH340-class UART bridge versus payload size with 8N1 framing and 6 B/frame protocol overhead. At the prototype’s maximum 2 Mbaud, goodput saturates at 1.59 Mb/s for 1500-B payloads—the true ceiling of any measurement taken through this interface.

for the remainder), and 99th-percentile latency stays below 0.11 ms at 70% load at all demonstrated ranges—comfortably within the budgets of interactive and industrial-control traffic, and the property that makes the diffused-LD architecture interesting for low-latency optical access. The ns-3 example programs reproduce these scenarios over the full IPv4/UDP stack. VIII. W HAT THE P ROTOTYPE E STABLISHED , AND W HAT THE F RAMEWORK A DDS Table II summarizes the forensic accounting. We emphasize scope honestly: the hardware prototype established end-to-end













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Fig. 12. Reconstruction PSNR of the 69 × 71 test image versus SNR for three constellations (no FEC), simulated bit-exactly through the Gray-mapped QAM chain.

feasibility of the diffused-LD architecture at 14 m, including voice and image payloads; it could not establish multiMb/s throughput, error floors, or coverage. All higher-rate figures in this paper are model-based predictions from a link budget whose every component is standard [14]–[16], whose parameters are prototype-derived, and whose implementations are open and mutually validating. Experimental confirmation at full bandwidth—a wideband driver and receiver replacing the UART path—is the natural next step and is enabled, not replaced, by this framework. Two modeling limitations bound the claims. First, the channel is LOS only; diffuse multipath adds a floor of delayed power that matters for wide-FoV receivers near walls [14],

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TABLE II P ROTOTYPE G APS AND T HEIR R ESOLUTION IN T HIS W ORK

d P4$00EV d P4$00EV d P4$00EV

 

Gap in the prototype study

Resolution

127-Mb/s rate estimate from MATLAB timing

UART ceiling analysis (Fig. 11); rate claims re-derived from the validated link budget (Fig. 7) Noise-based BER-vs-distance curves (Fig. 6); at UART rates the model predicts BER < 10−12 at 14 m, consistent with observing zero errors Shot + thermal budget (4)–(6), validated by Monte-Carlo and pinned by unit tests Full design-space sweeps: distance, power, beam width, modulation, coverage (Figs. 4– 10) Diffused extended-source operation discussed against IEC 60825-1 [25]; power– range trade quantified (Fig. 8b) ns-3 full-stack simulations (Figs. 14–15)

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Fig. 14. Goodput versus offered load over the stop-and-wait ARQ link at three distances (adaptive modulation; post-FEC residual BER 10−9 ). Saturation reaches 93–96% of the PHY line rate; the shortfall is ACK serialization.

Eye safety qualitatively

asserted

No network-level evidence No reproducibility

Open ns-3 module + Python engine, crossvalidated to 0.1%

 carrier chain assumes ideal DC bias and linear LD response; nonlinearity and clipping studies (as in DCO-/ACO-OFDM analyses [4], [26]) are orthogonal and composable with the framework.

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Fig. 15. Packet-latency CDFs at 70% load. 99th-percentile latency is 51 µs at 5 m, 68 µs at 10 m, and 102 µs at 14 m, tracking the PHY rate selected by the adaptive policy.

[19] and will be added as an impulse-response extension of LifiOpticalChannelModel. Second, the M-QAM sub-

We transformed a working but interface-limited LD-LiFi prototype into a complete, reproducible system study. A diffuser-parameterized Lambertian link model with a full noise budget, validated by Monte-Carlo simulation and pinned across two independent implementations, shows that the prototype’s optical front end supports 930 Mb/s net at its demonstrated 14-m range and 1.86 Gb/s at short range under a standard HD-FEC threshold, while OOK persists to 23 m. Coverage maps quantify the diffuser’s rate-versus-coverage dial, and full-stack ns-3 simulations demonstrate near-line-rate goodput with sub-0.11-ms tail latency. The open lifi ns3 module makes laser-based LiFi accessible to network-layer research—multi-cell interference, handover, hybrid RF/optical scheduling—on a physically validated foundation. Future work

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adds measured wideband hardware, diffuse multipath, LD nonlinearity, and OFDM bit-loading. R EFERENCES [1] M. Z. Chowdhury, M. T. Hossan, A. Islam, and Y. M. Jang, “A comparative survey of optical wireless technologies: Architectures and applications,” IEEE Access, vol. 6, pp. 9819–9840, 2018. [2] P. H. Pathak, X. Feng, P. Hu, and P. Mohapatra, “Visible light communication, networking, and sensing: A survey, potential and challenges,” IEEE Communications Surveys & Tutorials, vol. 17, no. 4, pp. 2047– 2077, 2015. [3] H. Haas, L. Yin, Y. Wang, and C. Chen, “What is LiFi?” Journal of Lightwave Technology, vol. 34, no. 6, pp. 1533–1544, 2016. [4] M. S. Islim and H. Haas, “Modulation techniques for Li-Fi,” ZTE Communications, vol. 14, no. 2, pp. 29–40, 2016. [5] D. Karunatilaka, F. Zafar, V. Kalavally, and R. Parthiban, “LED based indoor visible light communications: State of the art,” IEEE Communications Surveys & Tutorials, vol. 17, no. 3, pp. 1649–1678, 2015. [6] D. Tsonev, H. Chun, S. Rajbhandari, J. J. D. McKendry, S. Videv, E. Gu, M. Haji, S. Watson, A. E. Kelly, G. Faulkner, M. D. Dawson, H. Haas, and D. O’Brien, “A 3-Gb/s single-LED OFDM-based wireless VLC link using a gallium nitride µLED,” IEEE Photonics Technology Letters, vol. 26, no. 7, pp. 637–640, 2014. [7] M. S. Islim, R. X. Ferreira, X. He, E. Xie, S. Videv, S. Viola, S. Watson, N. Bamiedakis, R. V. Penty, I. H. White, A. E. Kelly, E. Gu, H. Haas, and M. D. Dawson, “Towards 10 Gb/s orthogonal frequency division multiplexing-based visible light communication using a GaN violet micro-LED,” Photonics Research, vol. 5, no. 2, pp. A35–A43, 2017. [8] Y.-C. Chi, D.-H. Hsieh, C.-T. Tsai, H.-Y. Chen, H.-C. Kuo, and G.R. Lin, “450-nm GaN laser diode enables high-speed visible light communication with 9-Gbps QAM-OFDM,” Optics Express, vol. 23, no. 10, pp. 13 051–13 059, 2015. [9] T.-C. Wu, Y.-C. Chi, H.-Y. Wang, C.-T. Tsai, Y.-F. Huang, and G.-R. Lin, “White-lighting communication with a Lu3 Al5 O12 :Ce3+ /CaAlSiN3 :Eu2+ glass covered 450-nm InGaN laser diode,” Journal of Lightwave Technology, vol. 36, no. 9, pp. 1634–1643, 2018. [10] Y.-C. Chi, Y.-F. Huang, T.-C. Wu, C.-T. Tsai, L.-Y. Chen, H.-C. Kuo, and G.-R. Lin, “Violet laser diode enables lighting communication,” Scientific Reports, vol. 7, no. 1, p. 10469, 2017. [11] C. Shen, Y. Guo, H. M. Oubei, T. K. Ng, G. Liu, K.-H. Park, K.-T. Ho, M.-S. Alouini, and B. S. Ooi, “20-meter underwater wireless optical communication link with 1.5 Gbps data rate,” Optics Express, vol. 24, no. 22, pp. 25 502–25 509, 2016. [12] C. Shen, Y. Guo, X. Sun, G. Liu, K.-T. Ho, T. K. Ng, M.-S. Alouini, and B. S. Ooi, “Going beyond 10-meter, Gbit/s underwater optical wireless communication links based on visible lasers,” in Proc. OptoElectronics and Communications Conference (OECC) and Photonics Global Conference (PGC), 2017. [13] F. Zafar, M. Bakaul, and R. Parthiban, “Laser-diode-based visible light communication: Toward gigabit class communication,” IEEE Communications Magazine, vol. 55, no. 2, pp. 144–151, 2017. [14] J. M. Kahn and J. R. Barry, “Wireless infrared communications,” Proceedings of the IEEE, vol. 85, no. 2, pp. 265–298, 1997. [15] T. Komine and M. Nakagawa, “Fundamental analysis for visible-light communication system using LED lights,” IEEE Transactions on Consumer Electronics, vol. 50, no. 1, pp. 100–107, 2004. [16] Z. Ghassemlooy, W. Popoola, and S. Rajbhandari, Optical Wireless Communications: System and Channel Modelling with MATLAB, 2nd ed. CRC Press, 2019. [17] IEEE, “IEEE standard for local and metropolitan area networks—part 15.7: Short-range optical wireless communications,” IEEE Std 802.15.72018, 2018. [18] Y.-L. Gao, Z.-Y. Wu, Z.-K. Wang, and J. Wang, “A 1.34-Gb/s realtime Li-Fi transceiver with DFT-spread-based PAPR mitigation,” IEEE Photonics Technology Letters, vol. 30, no. 16, pp. 1447–1450, 2018. [19] A. T. Hussein and J. M. H. Elmirghani, “Mobile multi-gigabit visible light communication system in realistic indoor environment,” Journal of Lightwave Technology, vol. 33, no. 15, pp. 3293–3307, 2015. [20] K.-T. Ho, R. Chen, G. Liu, C. Shen, J. Holguin-Lerma, A. A. Al-Saggaf, T. K. Ng, M.-S. Alouini, J.-H. He, and B. S. Ooi, “3.2 gigabit-persecond visible light communication link with InGaN/GaN MQW microphotodetector,” Optics Express, vol. 26, no. 3, pp. 3037–3045, 2018.

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