End-to-End Energy Saving in Cell-Free Massive MIMO ISAC for Ultra-Reliable Target-Aware Actuation

TL;DR

This paper develops an energy-efficient joint power and blocklength allocation method for cell-free massive MIMO ISAC systems supporting multi-static sensing and URLLC, optimizing energy use while ensuring sensing and communication reliability.

Contribution

It introduces a novel optimization framework combining FPP-SCA, CCP, and fractional programming for E2E energy minimization in integrated sensing and communication systems.

Findings

Proposed algorithm reduces E2E energy consumption while maintaining performance.

Clutter-aware detectors achieve up to 40% energy savings compared to simpler detectors.

System performance is validated through comprehensive simulations under various conditions.

Abstract

Ultra-reliable target-aware actuation-where timely and accurate sensing information is used to trigger critical actions in emerging 6G sensing-based applications-demands tight integration of sensing and communication under stringent reliability and latency constraints. This paper investigates integrated sensing and communication(ISAC)in a downlink CF-mMIMO system supporting multi-static sensing and ultra-reliable low-latency communications (URLLC). We propose a joint power and blocklength allocation algorithm to minimize the E2E energy consumption while meeting communication and sensing requirements.E2E energy consumption includes transmission, sensing receivers, and processing for both sensing and communication. The non-convex optimization problem is solved using a combination of FPP-SCA, concave-convex programming (CCP), and fractional programming techniques. We consider two types of target detectors:clutter-aware and clutter-unaware, each with distinct complexity and performance trade-offs.A computational complexity analysis based on giga-operations per second (GOPS) is conducted to quantify the processing requirements of communication and sensing tasks. We perform a comprehensive performance evaluation under various communication and sensing requirements, and benchmark our approach against two alternatives: one minimizing only transmission energy for ISAC and one minimizing E2E energy only for URLLC without sensing integration. Simulation results demonstrate that the proposed algorithm achieves enhanced detection capability with less E2E energy consumption. Additionally, we examine the trade-offs between detector complexity, the number of antenna elements per access point(AP), and the number of sensing APs. Clutter-aware detectors, although more complex, require fewer antennas and sensing receive APs to meet detection requirements, thus yielding up to 40% energy savings.