Electronic Thesis and Dissertation Repository

Thesis Format

Monograph

Degree

Doctor of Philosophy

Program

Electrical and Computer Engineering

Supervisor

Wang, Xianbin

Abstract

The unprecedented proliferation of wireless infrastructures and their ongoing convergence with diverse industrial Internet of Things (IoT) applications introduce new demands for upcoming wireless networks. In response to such diversity of demands, envisioned future wireless networks must have multiple beyond communication capabilities, such as localization and sensing. To efficiently utilize, allocate, and manage these capabilities, the integration of localization, sensing, and communication (ILSAC) within a unified wireless system structure is of utmost importance. However, the seamless integration of ILSAC into intricate network infrastructures is encumbered by critical challenges, including high-accuracy localization/sensing algorithm, efficient resource management and allocation scheme, and robust optimization method under dynamic situations. Therefore, this thesis introduces a value-driven, multi-objective ILSAC system design mechanism.

Firstly, to extend the applicability of wireless localization into 3D environments targeting objects with six degrees of freedom, while simultaneously enhancing localization accuracy and extracting valuable environmental information from received signals, a rigid body joint localization and environment sensing scheme is proposed. Specifically, a two-step hierarchical compressive sensing algorithm is proposed to extract the angular and distance information of the line-of-sight (LOS) (if available) and single-bounce specular reflections. Then a particle swarm optimization (PSO) based method is derived to recover the posture of the rigid body and the location of reflection points. The simulation results demonstrate that the proposed scheme can achieve high accuracy in rigid body localization and locate the reflection points around the rigid body even under obstructed line-of-sight (OLOS) conditions in an indoor scene.

Secondly, to address the challenge of integrative resource allocation among coexisting functions and services within an integrated system, a service-oriented ILAC system is presented to allocate radio resources for diverse service provisioning under both static and dynamic environments. A novel concept, termed Value of Service (VoS), is coined to maximize the unified performance of the ILAC system for diverse service provisioning including localization accuracy and communication data rate. In the static scenario, the bandwidth and temporal resource allocation problem is formulated as a mixed-integer nonlinear problem for ILAC to maximize its VoS. In a dynamic scenario, a deep-reinforcement learning (DRL) based adaptive resource allocation update algorithm is developed for long-term system gain maximization. Simulation results demonstrate the significant superiority of our proposed VoS evaluation metric and resource allocation method in the ILAC system under both static and dynamic scenarios.

Thirdly, to tackle the dual challenge of the environment-dependent and resource-intensive nature of wireless sensing, along with managing the varied resource requirements of multiple users, we introduce a VoS-driven resource allocation scheme for cooperative service provisioning in a multi-user ISAC system. We formulate the multi-user resource allocation problem as a bargaining game-based model and address it using an iterative algorithm to attain the Nash equilibrium solution. In each iteration, power and bandwidth resources are allocated by solving the Lagrangian dual problem. Numerical simulations are performed under varying resource conditions, service demands, and channel states. The results highlight the superiority of our proposed scheme over non-collaborative alternatives and the other two benchmark schemes.

Summary for Lay Audience

The rapid proliferation of intelligent devices, further driven by the emergence of next-generation vertical applications, including augmented reality (AR), smart factories, and autonomous robotics, has brought explosively growing demands for wireless networks to possess capabilities beyond the traditional role of data transmission. Among these capabilities, integrated localization, sensing, and communication (ILSAC) will greatly empower applications that require environmental understanding and perception alongside communication. Nonetheless, integrating localization and sensing services into existing communication systems significantly increases the complexity of system design and affects the efficiency of resource allocation. To address these challenges, this thesis developed a series of value-oriented mechanisms to guide the ILSAC system design, resource allocation and localization/sensing state recovery. Firstly, to extend the applicability of wireless localization into 3D environments targeting objects with six degrees of freedom, while simultaneously enhancing localization accuracy and extracting valuable environmental information from received signals, a rigid body joint localization and environment sensing scheme is proposed. Secondly, to address the challenge of integrative resource allocation among coexisting functions and services within an integrated system, a Value of Service (VoS) guided ILAC system is presented to allocate radio resources for diverse service provisioning under both static and dynamic environments. Thirdly, to tackle the dual challenge of the resource-intensive and environment-dependent nature of sensing, along with managing the varied resource requirements of multiple users, we introduce a VoS-driven resource allocation scheme for cooperative service provisioning in a multi-user ISAC system.

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