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Digital Fairness Algorithms for Satellite Uplink NOMA

Giorgio Taricco

TL;DR

This work tackles fairness in satellite uplink NOMA for IoT devices experiencing heterogeneous link budgets. It analyzes single-slot NOMA to identify the optimal SIC ordering (decode strongest-to-weakest) and proposes a power-moderation strategy to maximize the minimum user rate. It then extends to multi-slot scenarios with a rate-equalization algorithm and evaluates performance and complexity trade-offs through a Starlink-inspired beamspot simulation. The results indicate that appropriate SIC ordering and controlled power modulation can substantially improve max-min fairness, offering a practical approach for fair and efficient satellite IoT uplinks, while highlighting the need to balance fairness with receiver complexity and latency in real-time deployments.

Abstract

Achieving digital fairness by using NOMA is one of the more pressing issues in modern wireless communication systems for 5G/6G networks. This is particularly true in the case of satellite uplink systems supporting a population of IoT wireless devices scattered in a wide coverage area. In this scenario, the variability of the link budget across space and time increases the challenges of preventing a situation where only a subset of network users can transmit while others are left unable to do so. This work investigates the characteristics of an uplink NOMA system with the goal of equalizing the achievable rate of the IoT network subscribers. Within the context of single-slot NOMA, two key outcomes are achieved: the determination of the optimal SIC ordering at the receiver and the exploration of power moderation, coordinated by the receiver, to maximize the minimum user rate. In the context of multi-slot NOMA, which is particularly relevant to the satellite scenario under consideration, a user rate equalization algorithm is proposed and its performance is analyzed numerically. The trade-off between network performance, measured in terms of user rates, and complexity, determined by the number of SIC steps implemented at the receiver, is thoroughly evaluated for the satellite scenario under consideration.

Digital Fairness Algorithms for Satellite Uplink NOMA

TL;DR

This work tackles fairness in satellite uplink NOMA for IoT devices experiencing heterogeneous link budgets. It analyzes single-slot NOMA to identify the optimal SIC ordering (decode strongest-to-weakest) and proposes a power-moderation strategy to maximize the minimum user rate. It then extends to multi-slot scenarios with a rate-equalization algorithm and evaluates performance and complexity trade-offs through a Starlink-inspired beamspot simulation. The results indicate that appropriate SIC ordering and controlled power modulation can substantially improve max-min fairness, offering a practical approach for fair and efficient satellite IoT uplinks, while highlighting the need to balance fairness with receiver complexity and latency in real-time deployments.

Abstract

Achieving digital fairness by using NOMA is one of the more pressing issues in modern wireless communication systems for 5G/6G networks. This is particularly true in the case of satellite uplink systems supporting a population of IoT wireless devices scattered in a wide coverage area. In this scenario, the variability of the link budget across space and time increases the challenges of preventing a situation where only a subset of network users can transmit while others are left unable to do so. This work investigates the characteristics of an uplink NOMA system with the goal of equalizing the achievable rate of the IoT network subscribers. Within the context of single-slot NOMA, two key outcomes are achieved: the determination of the optimal SIC ordering at the receiver and the exploration of power moderation, coordinated by the receiver, to maximize the minimum user rate. In the context of multi-slot NOMA, which is particularly relevant to the satellite scenario under consideration, a user rate equalization algorithm is proposed and its performance is analyzed numerically. The trade-off between network performance, measured in terms of user rates, and complexity, determined by the number of SIC steps implemented at the receiver, is thoroughly evaluated for the satellite scenario under consideration.

Paper Structure

This paper contains 11 sections, 2 theorems, 19 equations, 4 figures, 2 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. Organization
  3. Satellite beamspot scenario
  4. Uplink NOMA
  5. Optimum SIC order (single slot)
  6. Optimization by power moderation (single slot)
  7. Multi-slot optimization
  8. Numerical Results
  9. Conclusions
  10. Proof of Proposition \ref{['th:SIC']}
  11. Proof of Proposition \ref{['th:reducepower']}

Key Result

Proposition 1

For a given set of SNRs, $\{\rho_1,\ldots,\rho_N\}$, the maximum minimum achievable rate is obtained when the SNR sequence is nonincreasing.

Figures (4)

  • Figure 1: SNR diagrams corresponding to user locations $(\lambda_0+i\delta_\mathsf{lat},\varphi_0+j\delta_\mathsf{lon})$ for $i,j\in\{-1,0,1\}$ in latitude/longitude coordinates. The light green area corresponds to the SNR range over the coverage area.
  • Figure 2: User achievable rates obtained by applying Algorithm \ref{['algo:1']} without power moderation in the scenario considered. The upper limit labeled "Normalized sum-rate" corresponds to $\frac{1}{T}\sum_t\log_2(1+\sum_n\rho_n[t])\cdot B$.
  • Figure 3: Same as Fig. \ref{['fig:rates_no_pow_mod']} but with power moderation.
  • Figure 4: Plot of the user achievable rate versus the SIC order $N_\mathsf{SIC}$ for the scenario considered.

Theorems & Definitions (3)

  • Proposition 1
  • Proposition 2
  • Remark 1