Source-linked AI summary
Robust Beamforming Design for Rate Splitting Multiple Access-Aided MISO Visible Light Communications
Shuai Ma, Guanjie Zhang, Zhi Zhang, Rongyan Gu
TL;DR
The achievable rate of RSMA-aided VLC networks is unknown despite practical optical-power constraints. The paper derives rate lower bounds and optimizes beamformers under optical and electrical power constraints. Simulations show RSMA outperforming NOMA and SDMA in the reported comparisons.
Problem
The achievable rate of RSMA-aided VLC networks remains unknown because VLC has distinct characteristics and practical optical-power constraints.
Source: §I · p. 1Method
The paper derives user-rate lower bounds and investigates sum-rate-maximizing beamformer design under optical and electrical power constraints.
Source: §I · p. 1Results
RSMA achieves higher sum rate than NOMA and SDMA for both reported user pairs across the evaluated transmitted-power budgets.
Source: §IV · p. 3Takeaways & Limitations
The proposed beamformer design provides useful insights on the design of RSMA-aided VLC networks.
Source: §V · p. 4
Abstract
from arXiv · showhide
In this paper, we focus on the optimal beamformer design for rate splitting multiple access (RSMA)-aided multipleinput single-output (MISO) visible light communication (VLC) networks. First, we derive the closed-form lower bounds of the achievable rate of each user, which are the first theoretical bound of achievable rate for RSMA-aided VLC networks. Second, we investigate the optimal beamformer design for RSMA-aided VLC networks to maximize the sum rate under the optical and electrical power constraints. In addition, we show that the proposed RSMA-aided networks can achieve superior performance compared with space-division multiple access (SDMA) and nonorthogonal multiple access (NOMA).
I. INTRODUCTION
The achievable rate of RSMA-aided VLC networks remains unknown because VLC has distinct characteristics and practical optical-power limits. The paper derives rate lower bounds and designs beamformers, reporting superior performance over baseline schemes.
I. INTRODUCTION
- RSMA-aided VLC achievable rates remain unknown amid practical optical-power constraints tied to eye safety and illumination.The paper identifies achievable-rate analysis and optimal and robust beamformer design as its two central issues.Source: §I · p. 1
- The paper derives user-rate lower bounds and investigates sum-rate-maximizing beamformer design under optical and electrical power constraints.The considered constraints include peak and average optical power and average electrical power.Source: §I · p. 1
- RSMA-aided VLC networks achieve superior performance compared with several baseline schemes.Source: §I · p. 1
II. SYSTEM MODEL OF DOWNLINK RSMA-AIDED VLC NETWORK
The downlink model uses a VLC base station with multiple LEDs serving single-access point users through RSMA, subject to LED power constraints and a line-of-sight channel assumption.
II. SYSTEM MODEL OF DOWNLINK RSMA-AIDED VLC NETWORK
- The base station serves K single-access point users with N LEDs, splitting each user's message into common and private messages.The common messages are collected into a shared set of signals.Source: §II · p. 1
- The VLC base station forms an N-dimensional transmitted signal vector from the RSMA signals, whose amplitudes are bounded.The source specifies a positive signal-amplitude bound for each signal.Source: §II · p. 1
- The model accounts for average electrical and optical transmit power, and requires beamformers to satisfy the LEDs' maximum-current constraint.Source: §II · p. 1
- The optical channel is modeled as dominated by line-of-sight links, with diffuse links neglected.The channel-gain vector collects the gains from each LED to a user.Source: §II · p. 1
- The received-signal model includes zero-mean Gaussian noise; the DC component is removed by a capacitor, and the residual signal is considered after SIC.Source: §II · p. 2
III. DOWNLINK RSMA-AIDED VLC NETWORK
The section defines lower bounds for decoding common and private signals and specifies how common-message rate is shared among users.
III. DOWNLINK RSMA-AIDED VLC NETWORK
- The section gives lower bounds for each user's achievable rate when decoding the common signal and the private signal.Source: §III · p. 2
- The common-message transmission rate cannot exceed the minimum common-signal decoding rate across users.Source: §III · p. 2
- Each user's common-message rate share is nonnegative, and the shares sum to the common-message rate.Source: §III · p. 2
A. Optimal Beamformer Design
The sum-rate maximization problem is non-convex and computationally intractable, so the design is reformulated and approximated through auxiliary variables and iterative convex optimization.
A. Optimal Beamformer Design
- The non-convex sum-rate problem is transformed into an equivalent reformulation using auxiliary variables.The reformulated problem is based on the original sum-rate objective.Source: A. Optimal Beamformer Design · p. 2
- Semidefinite relaxation is used to relax constraints in the reformulated problem.The text identifies constraints (11b) and (11c) for rewriting.Source: A. Optimal Beamformer Design · pp. 2–3
- A first-order Taylor expansion supports a convex approximation updated iteratively from a feasible point.The feasible point from iteration m is used to form the approximation at iteration m + 1.Source: A. Optimal Beamformer Design · p. 3
IV. SIMULATION RESULTS AND DISCUSSION
In the simulated setting, RSMA achieves higher sum rate than NOMA and SDMA for both evaluated user pairs as transmitted power increases.
IV. SIMULATION RESULTS AND DISCUSSION
- The simulations consider a VLC network deployed in a room measuring 7 × 7 × 5 m^3.Source: §IV · p. 3
- RSMA outperforms both NOMA and SDMA for the evaluated user pairs as transmitted power increases.The comparisons cover users U1 and U2 and users U3 and U4.Source: Figure 1 · p. 3, §IV · p. 3
- Figure 1 plots sum rate against transmitted power with perfect CSIT for N = 4, K = 2, evaluating U1/U2 and U3/U4.The two panels show the two user pairs, respectively.Source: Figure 1 · p. 3
V. CONCLUSION
The paper derives achievable-rate lower bounds for RSMA-aided VLC and uses them to study sum-rate-maximizing beamformer design under optical and electrical power constraints. Simulations show the proposed beamformer design's superiority.
V. CONCLUSION
- The paper derives lower bounds on achievable rates for RSMA-aided VLC networks.Source: §V · p. 3
- The derived bounds are used to investigate beamformer design that maximizes sum rate under optical and electrical power constraints of LEDs.Source: §V · p. 4
- Simulation results illustrate the superiority of the proposed beamformer design and provide insights for RSMA-aided VLC network design.Source: §V · p. 4