Load Balanced ISAC Systems for URLLC Users

2026-01-23

AI Summary

This work addresses the energy efficiency optimization problem in cell-free massive MIMO integrated sensing and communication (ISAC) systems, aiming to jointly satisfy ultra-reliable low-latency communication (URLLC) quality-of-service requirements and sensing performance. To this end, a joint power allocation and access point load balancing (JPALB) algorithm is proposed. For the first time, a load balancing mechanism is incorporated into ISAC systems, leading to a mixed-integer nonconvex optimization model that accounts for both communication and sensing QoS constraints. An efficient iterative algorithm is developed by integrating maximum ratio transmission (MRT) and regularized zero-forcing (RZF) precoding. Simulation results demonstrate that JPALB reduces total system power consumption by approximately 33% compared to a baseline scheme without load balancing, while maintaining comparable communication and sensing performance.

Technology Category

Search and Optimization: Mixed Discrete/Continuous SearchPlanning, Routing, and Scheduling: Optimization of Spatio-temporal SystemsConstraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization

Application Category

Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environmentsUser Modeling, Personalization and Recommendation: Federated recommendation systems and personalizationSecurity and Privacy: Security and privacy of machine learning and AI applications

Abstract

This paper presents an energy-efficient downlink cell-free massive multiple-input multiple-output (CF-mMIMO) integrated sensing and communication (ISAC) network that serves ultra-reliable low-latency communication (URLLC) users while simultaneously detecting a target. We propose a load-balancing algorithm that minimizes the total network power consumption; including transmit power, fixed static power, and traffic-dependent fronthaul power at the access points (APs) without degrading system performance. To this end, we formulate a mixed-integer non-convex optimization problem and introduce an iterative joint power allocation and AP load balancing (JPALB) algorithm. The algorithm aims to reduce total power usage while meeting both the communication quality-of-service (QoS) requirements of URLLC users and the sensing QoS needed for target detection. Proposed JPALB algorithm for ISAC systems was simulated with maximum-ratio transmission (MRT) and regularized zero-forcing (RZF) precoders. Simulation results show approximately 33% reduction in power consumption, using JPALB algorithm compared to a baseline with no load balancing, without compromising communication and sensing QoS requirements.

Problem

• ISAC
• URLLC
• load balancing
• power consumption
• CF-mMIMO

Innovation

• load balancing
• ISAC
• CF-mMIMO
• URLLC
• energy efficiency