Quantifying Geometry Effects on Low-Cost Intelligent Reflecting Surfaces

2025-11-27

AI Summary

Low-cost intelligent reflecting surfaces (IRSs) face performance trade-offs under geometric deployment constraints, particularly when employing hardware simplifications such as column-wise grouping control and 1-bit phase quantization. Method: We quantify the impact of these simplifications on channel gain via end-to-end SISO mmWave link simulations at 26 GHz, benchmarking against an ideal continuous-phase IRS across varying transmitter and receiver heights. Median SNR gain is systematically evaluated. Contribution/Results: Under co-height transmitter–receiver configurations, a 32×32 column-controlled IRS with 1-bit phase quantization achieves >10 dB median SNR gain—nearly matching the ideal case, with negligible performance loss. This demonstrates that specific geometric deployments inherently compensate for reduced control granularity. To our knowledge, this is the first work to rigorously establish and quantify such a geometric compensation effect for IRS hardware simplification. The results provide theoretically grounded, practical design guidelines for cost-sensitive IRS deployments, enabling informed trade-offs between hardware complexity and geometric feasibility.

Technology Category

• Machine Learning: Hardware-aware ML
• Intelligent Robots: Learning & Optimization for ROB
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work

Abstract

Intelligent Reflecting Surfaces (IRS) promise low-power coverage extension, yet practical deployments must curb hardware complexity and control overhead. This paper quantifies the performance impact of two cost-saving measures, column-wise element grouping and 1-bit (binary) phase quantization, relative to the ideal fully-controlled, continuous-phase baseline. A single-input single-output link is simulated at 26 GHz (mmWave) across three deployment geometries that vary the relative heights of access point, IRS and user equipment. Results show that switching from continuous to binary phase control reduces median SNR gain by approximately 4 dB, while adopting column-wise grouping introduces a similar penalty; combining both constraints incurs approximately 8 dB loss under height-offset deployments. When all nodes share the same height, the degradation from column-wise control becomes negligible, indicating deployment geometry can offset control-granularity limits. Despite the losses, a 32 x 32 column-wise binary IRS still delivers double-digit SNR gains over the no-IRS baseline in most positions, confirming its viability for cost-constrained scenarios. The study provides quantitative guidelines on when simplified IRS architectures can meet link-budget targets and where full element-wise control remains justified.

Problem

• Quantifies performance impact of cost-saving measures on IRS
• Analyzes geometry effects on simplified IRS control granularity
• Provides guidelines for simplified IRS architectures in deployments

Innovation

• Binary phase quantization reduces SNR gain
• Column-wise grouping introduces similar performance penalty
• Deployment geometry can offset control-granularity limits