DeepAI AI Chat
Log In Sign Up

Next-Generation URLLC with Massive Devices: A Unified Semi-Blind Detection Framework for Sourced and Unsourced Random Access

by   Malong Ke, et al.
Princeton University
Beijing Institute of Technology

This paper proposes a unified semi-blind detection framework for sourced and unsourced random access (RA), which enables next-generation ultra-reliable low-latency communications (URLLC) with massive devices. Specifically, the active devices transmit their uplink access signals in a grant-free manner to realize ultra-low access latency. Meanwhile, the base station aims to achieve ultra-reliable data detection under severe inter-device interference without exploiting explicit channel state information (CSI). We first propose an efficient transmitter design, where a small amount of reference information (RI) is embedded in the access signal to resolve the inherent ambiguities incurred by the unknown CSI. At the receiver, we further develop a successive interference cancellation-based semi-blind detection scheme, where a bilinear generalized approximate message passing algorithm is utilized for joint channel and signal estimation (JCSE), while the embedded RI is exploited for ambiguity elimination. Particularly, a rank selection approach and a RI-aided initialization strategy are incorporated to reduce the algorithmic computational complexity and to enhance the JCSE reliability, respectively. Besides, four enabling techniques are integrated to satisfy the stringent latency and reliability requirements of massive URLLC. Numerical results demonstrate that the proposed semi-blind detection framework offers a better scalability-latency-reliability tradeoff than the state-of-the-art detection schemes dedicated to sourced or unsourced RA.


page 3

page 5

page 6

page 26

page 28

page 32

page 39

page 41


Compressive Sensing Based Joint Activity and Data Detection for Grant-Free Massive Access

Massive machine-type communications (mMTC) are poised to provide ubiquit...

Interference Distribution Prediction for Link Adaptation in Ultra-Reliable Low-Latency Communications

The strict latency and reliability requirements of ultra-reliable low-la...

Blind Multi-user Detection for Autonomous Grant-free High-Overloading MA without Reference Signal

In this paper, a novel blind multi-user detection(MUD) framework for aut...

A GCICA Grant-Free Random Access Scheme for M2M Communications in Crowded Massive MIMO Systems

A high success rate of grant-free random access scheme is proposed to su...

Generalized Low-Rank Optimization for Topological Cooperation in Ultra-Dense Networks

Network densification is a natural way to support dense mobile applicati...

Code Design Principles for Ultra-Reliable Random Access with Preassigned Patterns

We study medium access control layer random access under the assumption ...

Massive MIMO for Ultra-reliable Communications with Constellations for Dual Coherent-noncoherent Detection

The stringent requirements of ultra-reliable low-latency communications ...