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Capacity-Maximizing Dynamic User Association in Double RIS-Aided Broadcast Networks

Alireza Vahid

TL;DR

The paper develops an information-theoretic framework for capacity-maximizing dynamic RIS-user association in a two-user, double RIS-aided broadcast network. By modeling the transmitter-to-receiver links as erasure channels whose success probabilities vary with a time-varying RIS-to-user association $\mathcal{A}^n$, it derives outer bounds on the capacity region for a given dynamic association and provides an achievable scheme that leverages phase-based RIS allocations and short ACK/NACK signaling. The results show that dynamic RIS-user association can outperform static configurations, with the dynamic scheme achieving the outer-bound region in a symmetric setting. This work offers a principled approach to RIS scheduling and beam steering for capacity optimization and lays groundwork for extending to more complex networks and interference scenarios.

Abstract

We introduce an information-theoretic framework to dynamically pair up different reconfigurable intelligent surfaces (RISs) with wireless users with goal of maximizing the fundamental network capacity. We focus on a double RIS-aided broadcast packet network with two users. We show using a dynamic RIS-user association and an opportunistic protocol, the network capacity could be significantly enhanced and superior to other benchmarks with static associations. The results include new outer-bounds on network capacity and their achievability. We discuss the optimal RIS-user association.

Capacity-Maximizing Dynamic User Association in Double RIS-Aided Broadcast Networks

TL;DR

The paper develops an information-theoretic framework for capacity-maximizing dynamic RIS-user association in a two-user, double RIS-aided broadcast network. By modeling the transmitter-to-receiver links as erasure channels whose success probabilities vary with a time-varying RIS-to-user association , it derives outer bounds on the capacity region for a given dynamic association and provides an achievable scheme that leverages phase-based RIS allocations and short ACK/NACK signaling. The results show that dynamic RIS-user association can outperform static configurations, with the dynamic scheme achieving the outer-bound region in a symmetric setting. This work offers a principled approach to RIS scheduling and beam steering for capacity optimization and lays groundwork for extending to more complex networks and interference scenarios.

Abstract

We introduce an information-theoretic framework to dynamically pair up different reconfigurable intelligent surfaces (RISs) with wireless users with goal of maximizing the fundamental network capacity. We focus on a double RIS-aided broadcast packet network with two users. We show using a dynamic RIS-user association and an opportunistic protocol, the network capacity could be significantly enhanced and superior to other benchmarks with static associations. The results include new outer-bounds on network capacity and their achievability. We discuss the optimal RIS-user association.
Paper Structure (6 sections, 2 theorems, 19 equations, 2 figures)

This paper contains 6 sections, 2 theorems, 19 equations, 2 figures.

Table of Contents

  1. Introduction
  2. System Setup
  3. Information-Theoretic Bounds
  4. Motivation, Analysis, and Comparisons
  5. Proof of Theorem \ref{['THM:RIS-BEC']}
  6. Conclusion

Key Result

Theorem 1

For the two-user double RIS-aided broadcast packet network described in Section Section:Setup and for the dynamic RIS-user association defined above, we have: where and

Figures (2)

  • Figure 1: The two-user double RIS-aided broadcast packet network: (a) impact of RIS association on channel quality measured in terms of erasure likelihood; (b) $\mathrm{RIS}_i$ assists the reception at $\mathsf{Rx}_i$, $i=1,2$; (c) both RISs are associated with $\mathsf{Rx}_1$ resulting in the lowest erasure probability (highest channel quality).
  • Figure 2: Comparing the achievable rates for different RIS-user associations.

Theorems & Definitions (3)

  • Theorem 1
  • Lemma 1
  • proof