Source-linked AI summary
Non-Orthogonal Multiple Access for Visible Light Communications
Hanaa Marshoud, Vasileios M. Kapinas, George K. Karagiannidis, Sami Muhaidat
TL;DR
The paper addresses the need to boost spectral efficiency in VLC downlink systems. It proposes NOMA with channel-dependent GRPA and tunable LED transmission angles and receiver FOVs, finding improved BER capacity and context-dependent throughput benefits.
Problem
VLC downlink systems need an efficient and flexible multiple access protocol to boost spectral efficiency.
Method
The paper develops a multi-LED NOMA-VLC framework using gain ratio power allocation based on user channel gains and decoding order, with tunable LED angles and receiver FOVs.
Results
At BER = 10^-3, GRPA served 6 users compared with 4 under static power allocation; tuning angles and FOVs increased sum rate for small user counts.
Takeaways & Limitations
NOMA is a promising VLC downlink multiple access scheme, while tunable FOVs can significantly decrease handovers for moving users.
Takeaways & Limitations
GRPA is more sensitive to channel knowledge, and the simulations assume a noiseless RF uplink channel.
Abstract
from arXiv · showhide
The main limitation of visible light communication (VLC) is the narrow modulation bandwidth, which reduces the achievable data rates. In this paper, we apply the non-orthogonal multiple access (NOMA) scheme to enhance the achievable throughput in high-rate VLC downlink networks. We first propose a novel gain ratio power allocation (GRPA) strategy that takes into account the users' channel conditions to ensure efficient and fair power allocation. Our results indicate that GRPA significantly enhances system performance compared to the static power allocation. We also study the effect of tuning the transmission angles of the light emitting diodes (LEDs) and the field of views (FOVs) of the receivers, and demonstrate that these parameters can offer new degrees of freedom to boost NOMA performance. Simulation results reveal that NOMA is a promising multiple access scheme for the downlink of VLC networks.
I. INTRODUCTION
VLC’s narrow light-source modulation bandwidth limits achievable data rates, motivating NOMA as a flexible downlink multiple-access approach. The paper proposes GRPA and highlights channel conditions, CSI, SNR, and optical geometry as relevant to NOMA-VLC performance.
- Motivation: VLC’s narrow modulation bandwidth forms a barrier to achieving rival data rates.
- NOMA rationale: NOMA multiplexes users through superposition coding and SIC, allowing each user to exploit the entire bandwidth throughout the transmission.
- NOMA rationale: VLC’s mostly constant channel simplifies CSI requirements, with changes occurring mainly when users move.
- NOMA rationale: VLC links offer high SNRs because LEDs and photodetectors are closely separated and the line-of-sight path dominates.
- Contributions: Tuning LED transmission angles and receiver FOVs can increase channel-gain differences among users, which is critical for NOMA performance.
- Contributions: The paper proposes NOMA for VLC downlinks and develops GRPA, a channel-dependent power allocation strategy for multi-LED networks.
II. SYSTEM MODEL
The system model considers overlapping multi-LED VLC cells in which NOMA superposes user signals and SIC manages multi-user interference. Users may receive signals from multiple LEDs, with channel gains determined by optical geometry and receiver characteristics.
- Multi-LED scenario: Adjacent LED beams may overlap, allowing cell-boundary users to receive streams from two LEDs.U1 and U2 are associated with individual LEDs, while a boundary user can receive from both.
- NOMA transmission: NOMA transmits each LED’s user signals as a superposition, with separate power values assigned to each intended signal.LED1 sends x1 and x3, while LED2 sends x2 and x3 to their associated users.
- Signal and channel model: The received signal aggregates contributions from all LEDs and includes AWGN whose variance combines shot-noise and thermal-noise contributions.The received-signal model accounts for network-wide LED transmissions and receiver noise.
- Multi-LED scenario: A user can potentially obtain diversity gain by combining copies of the same symbol transmitted by two different LEDs.This applies to U3, which receives x3 from both LED1 and LED2.
- Signal and channel model: The line-of-sight channel gain depends on transmitter-receiver geometry, optical components, and the receiver FOV, with zero gain outside the FOV.The model includes distance, irradiance and incidence angles, filter gain, concentrator gain, and Lambertian emission.
- Interference handling: SIC decodes users in increasing channel-gain order, removing lower-order signals while treating higher-order interference as noise.The remaining interference comes from users with higher decoding order.
III. POWER ALLOCATION FOR NOMA-VLC NETWORKS
The proposed framework applies NOMA with gain ratio power allocation in a multi-LED VLC network. A central control unit uses users’ locations and channel gains, while the fixed VLC channel simplifies channel estimation.
- Framework: The GRPA-based NOMA-VLC framework targets maximum throughput in a realistic multi-LED indoor scenario.The framework assumes a central control unit coordinating network information.
- Framework: The central control unit collects users’ locations and associated channel gains for network operation.The VLC channel remains constant for a fixed receiver location because of its deterministic nature.
A. Users Association and Handover
User association exploits spatial location to determine LED connectivity, including dual association in overlapping regions. Transmission-angle tuning is investigated to reduce inter-beam interference and adjust coverage.
- Users Association and Handover: Users are associated with LEDs according to their spatial position, with overlap regions enabling association to both adjacent LEDs.This association can provide diversity gain for cell-edge users.
- Users Association and Handover: An RF uplink can be assumed for obtaining channel state information.The stated assumption is that this uplink is used to support CSI acquisition.
- Users Association and Handover: Transmission-angle tuning is used to reduce inter-beam interference and can adjust cell size without changing LED transmitted power.The paper relates this approach to cell zooming based on modifying transmission angles.
B. Decoding Order
SIC decoding order is determined by user channel gain, which depends on distance and receiver FOV. With fixed FOVs, users can be ordered by decreasing distance, while boundary users are placed last.
- Decoding Order: The SIC decoding order among users connected to an LED is decided from their channel gains.The channel-gain expression assumes fixed LED-PD height and vertical alignment.
- Decoding Order: Channel gain depends on the distance between LED and receiver and the receiver’s FOV.These two parameters determine the ordering inputs.
- Decoding Order: With fixed FOVs, users are sorted by decreasing distance, and cell-boundary users are moved to the end of the decoding order.This allows boundary users to decode after subtracting signal components intended for users in both cells.
1) Fixed FOVs:
With fixed PD FOVs, SIC ordering follows users’ distances from the associated LED, while cell-boundary users are placed last to support cross-cell signal decoding.
- 1) Fixed FOVs:: The decoding order lists cell-centre users first, followed by cell-edge users, each ordered by decreasing distance.
- 1) Fixed FOVs:: Reducing a PD’s FOV increases its optical-concentrator gain, but an excessively small FOV can block the required LED beam.
2) Tunable FOVs:
Tunable FOVs use user location to improve channel separation and reception, while also supporting fewer handovers during movement.
- 2) Tunable FOVs:: Cell-edge users use the lowest FOV that still receives the nearest LED, reducing beam overlap and enhancing spectral efficiency.
- 2) Tunable FOVs:: Cell-centre users use the lowest FOV setting to enhance channel gain.
- 2) Tunable FOVs:: Moving users can widen their FOV near the associated LED to remain connected and reduce handovers.
C. Gain Ratio Power Allocation (GRPA)
GRPA allocates NOMA power according to users’ relative channel gains and decoding order, decreasing power for stronger channels while accounting for fairness.
- C. Gain Ratio Power Allocation (GRPA): GRPA allocates each LED’s total transmitting power among users according to their channel gains.
- C. Gain Ratio Power Allocation (GRPA): GRPA power allocation depends on each user’s gain relative to the first sorted user and on decoding order i.
- C. Gain Ratio Power Allocation (GRPA): Assigned power decreases as channel gain h_li increases because stronger users need less power after interference cancellation.
- C. Gain Ratio Power Allocation (GRPA): The gain ratio h_l1/h_li is raised to decoding order i so lower-order users receive more power under larger interference.
IV. SIMULATION RESULTS AND DISCUSSION
Simulations evaluate a two-LED indoor NOMA-VLC network, comparing GRPA with static allocation and testing transmission-angle and FOV tuning. GRPA improves BER capacity, while FOV tuning offers the strongest throughput and fewer handovers.
- IV. SIMULATION RESULTS AND DISCUSSION: The simulations use a 6 × 6 × 3 m3 room with two transmitting LEDs and fixed or tunable transmission angles and PD FOVs.
- IV. SIMULATION RESULTS AND DISCUSSION: At BER = 10^-3, GRPA serves 6 users, whereas static power allocation accommodates 4 users.
- IV. SIMULATION RESULTS AND DISCUSSION: GRPA is more sensitive to channel knowledge, and the simulations assume a noiseless RF uplink channel.
- IV. SIMULATION RESULTS AND DISCUSSION: For small user counts, transmission-angle and FOV tuning increase sum rate by completely eliminating interference between the two beams.
- IV. SIMULATION RESULTS AND DISCUSSION: As user counts grow, transmission-angle tuning degrades throughput because cell-edge users cannot receive from both LEDs, whereas FOV tuning performs best.
- IV. SIMULATION RESULTS AND DISCUSSION: Tunable FOVs significantly decrease handovers compared with fixed FOVs when moving users widen their FOV near associated LEDs.