Design of RIS-aided mMTC+ Networks for Rate Maximization under the Finite Blocklength Regime with Imperfect Channel Knowledge

Abstract

Within the context of massive machine-type communications+, reconfigurable intelligent surfaces (RISs) represent a promising technology to boost system performance in scenarios with poor channel conditions. Considering single-antenna sensors transmitting short data packets to a multiple-antenna collector node, we introduce and design an RIS to maximize the weighted sum rate (WSR) of the system working in the finite blocklength regime. Due to the large number of reflecting elements and their passive nature, channel estimation errors may occur. In this letter, we then propose a robust RIS optimization to combat such a detrimental issue. Based on concave bounds and approximations, the nonconvex WSR problem for the RIS response is addressed via successive convex optimization (SCO). Numerical experiments validate the performance and complexity of the SCO solutions.

arXiv commentThis work has been accepted for publication in IEEE Communications Letters. The final published version is available via IEEE Xplore

References in corpus (9)

• 6G Internet of Things: A Comprehensive Survey
• Near-Field Communications: A Tutorial Review
• Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems
• Energy Efficiency Optimization in Relay-Assisted MIMO Systems with Perfect and Statistical CSI
• Performance Analysis of Reconfigurable Holographic Surfaces in the Near-Field Scenario of Cell-Free Networks Under Hardware Impairments
• Reconfigurable Intelligent Surfaces-Assisted Multiuser MIMO Uplink Transmission with Partial CSI
• A Globally Optimal Energy-Efficient Power Control Framework and its Efficient Implementation in Wireless Interference Networks
• A Bilinear Equalizer for Massive MIMO Systems
• Rate Optimization for RIS-Aided mMTC Networks in the Finite Blocklength Regime