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CR-Enabled NOMA Integrated Non-Terrestrial IoT Networks with Transmissive RIS

Wali Ullah Khan, Zain Ali, Asad Mahmood, Eva Lagunas, Syed Tariq Shah, Symeon Chatzinotas

TL;DR

This work tackles CR-enabled NOMA-integrated NTNs with a transmissive RIS, where a GEO primary network coexists with a LEO secondary IoT network. The objective is to maximize the secondary sum rate $R_k+R_j$ while ensuring $R_{ ext{min}}$ for LIoT and keeping interference to primary users below $I_{th}$ via an interference-temperature constraint $h_l P_t (p_k+p_j) \,\le\, I_{th}$. The authors propose a two-stage solution using successive convex approximation (SCA): first, NOMA power allocation given a fixed phase design using KKT conditions (with $p_j=1-p_k$ and $P_t^*$ determined by the interference constraint and power limit), and second, transmissive RIS phase-shift design via lifting to $oldsymbol{\Phi}=oldsymbol{ ilde{oldsymbol{oldsymbol{oldsymbol{}}}}oldsymbol{ ilde{oldsymbol{oldsymbol{oldsymbol{}}}}}^ op$, relaxing the rank-1 constraint, and solving a sequence of SDPs augmented with Taylor approximations; Gaussian randomization is used if needed. Numerical results show that increasing $M$ or $I_{th}$ boosts the sum rate, while convergence is achieved within about six iterations, confirming the framework’s effectiveness for CR-enabled NTNs. Overall, the paper provides a principled optimization path to enhance spectral efficiency in CR-enabled NOMA NTNs with T-RIS, enabling efficient spectrum reuse and robust protection of primary users.

Abstract

This work proposes a T-RIS-equipped LEO satellite communication in cognitive radio-enabled integrated NTNs. In the proposed system, a GEO satellite operates as a primary network, and a T-RIS-equipped LEO satellite operates as a secondary IoT network. The objective is to maximize the sum rate of T-RIS-equipped LEO satellite communication using downlink NOMA while ensuring the service quality of GEO cellular users. Our framework simultaneously optimizes the total transmit power of LEO, NOMA power allocation for LEO IoT (LIoT) and T-RIS phase shift design subject to the service quality of LIoT and interference temperature to the primary GEO network. To solve the non-convex sum rate maximization problem, we first adopt successive convex approximations to reduce the complexity of the formulated optimization. Then, we divide the problem into two parts, i.e., power allocation of LEO and phase shift design of T-RIS. The power allocation problem is solved using KKT conditions, while the phase shift problem is handled by Taylor approximation and semidefinite programming. Numerical results are provided to validate the proposed optimization framework.

CR-Enabled NOMA Integrated Non-Terrestrial IoT Networks with Transmissive RIS

TL;DR

This work tackles CR-enabled NOMA-integrated NTNs with a transmissive RIS, where a GEO primary network coexists with a LEO secondary IoT network. The objective is to maximize the secondary sum rate while ensuring for LIoT and keeping interference to primary users below via an interference-temperature constraint . The authors propose a two-stage solution using successive convex approximation (SCA): first, NOMA power allocation given a fixed phase design using KKT conditions (with and determined by the interference constraint and power limit), and second, transmissive RIS phase-shift design via lifting to , relaxing the rank-1 constraint, and solving a sequence of SDPs augmented with Taylor approximations; Gaussian randomization is used if needed. Numerical results show that increasing or boosts the sum rate, while convergence is achieved within about six iterations, confirming the framework’s effectiveness for CR-enabled NTNs. Overall, the paper provides a principled optimization path to enhance spectral efficiency in CR-enabled NOMA NTNs with T-RIS, enabling efficient spectrum reuse and robust protection of primary users.

Abstract

This work proposes a T-RIS-equipped LEO satellite communication in cognitive radio-enabled integrated NTNs. In the proposed system, a GEO satellite operates as a primary network, and a T-RIS-equipped LEO satellite operates as a secondary IoT network. The objective is to maximize the sum rate of T-RIS-equipped LEO satellite communication using downlink NOMA while ensuring the service quality of GEO cellular users. Our framework simultaneously optimizes the total transmit power of LEO, NOMA power allocation for LEO IoT (LIoT) and T-RIS phase shift design subject to the service quality of LIoT and interference temperature to the primary GEO network. To solve the non-convex sum rate maximization problem, we first adopt successive convex approximations to reduce the complexity of the formulated optimization. Then, we divide the problem into two parts, i.e., power allocation of LEO and phase shift design of T-RIS. The power allocation problem is solved using KKT conditions, while the phase shift problem is handled by Taylor approximation and semidefinite programming. Numerical results are provided to validate the proposed optimization framework.
Paper Structure (8 sections, 20 equations, 5 figures)

This paper contains 8 sections, 20 equations, 5 figures.

Table of Contents

  1. Introduction
  2. System Model
  3. Problem Formulation and Proposed Solution
  4. Problem Formulation
  5. NOMA Power Allocation
  6. T-RIS Phase Shift Design
  7. Numerical Results
  8. Conclusions

Figures (5)

  • Figure 1: System model
  • Figure 2: Impact of different $P_{max}$ and $M$ on the sum rate of the system.
  • Figure 3: Effect of varying $I_{th}$ of the primary network on the sum rate of the secondary network.
  • Figure 4: The figure illustrates the effect of increasing $P_{max}$ for different values of $R_{min}$.
  • Figure 5: The figure shows the convergence behaviour of the proposed framework.