Unsourced Random Access: A Comprehensive Survey

TL;DR

URA decouples user identification from data transmission by deploying a common codebook, enabling scalable massive connectivity for 6G and IoT. The paper provides a comprehensive taxonomy of URA solutions across GMAC, single-antenna fading, and MIMO fading channels, detailing slotting, CCS, random spreading, IDMA, ODMA, and Bayesian/pilot-based approaches, with energy-efficiency and complexity benchmarks. It highlights interference management, pilot/preamble collisions, and synchronization as core challenges, showing that ODMA and CCS-based schemes offer robust scalability under high user loads while preserving feasible complexity, especially when combined with massive MIMO. The survey also discusses extensions to asynchronous operation, robustness, ML augmentation, semantic/task-oriented URA, ISAC, RIS-aided designs, security, and standardization, outlining a practical roadmap for real-world URA deployments.

Abstract

Multiple access communication systems enable numerous users to share common communication resources, playing a crucial role in wireless networks. With the emergence of the sixth generation (6G) and beyond communication networks, supporting massive machine-type communications with sporadic activity patterns is expected to become a critical challenge. Unsourced random access (URA) has emerged as a promising paradigm to address this challenge by decoupling user identification from data transmission through the use of a common codebook. This survey offers a comprehensive overview of URA solutions, encompassing both theoretical foundations and practical applications. We present a systematic classification of URA solutions across three primary channel models: Gaussian multiple access channels (GMACs), single-antenna fading channels, and multiple-input multiple-output (MIMO) fading channels. For each category, we analyze and compare state-of-the-art solutions in terms of performance, complexity, and practical feasibility. Additionally, we discuss critical challenges such as interference management, computational complexity, and synchronization. The survey concludes with promising future research directions and potential methods to address existing limitations, providing a roadmap for researchers and practitioners in this rapidly evolving field.

Figures (20)

• Figure 1: Taxonomy of different MA techniques.
• Figure 2: Structure of the survey.
• Figure 3: An illustration of pure and slotted ALOHA. Red boxes show the collided packets, and green boxes are the successfully transmitted ones.
• Figure 4: An illustration of a system where a large number of potential users (devices) try to communicate with a receiver (access point), with only a small subset of them being active at each time frame.
• Figure 5: Performance comparison of conventional random access techniques with Polyanskiy's URA (random coding) achievability bound.