Improved ALOHA-based URA with Index Modulation: Efficient Decoding and Analysis

2025-05-03

AI Summary

To address the low decoding efficiency and analytical intractability of ALOHA-type schemes for unsourced random access (URA) over MIMO channels, this paper proposes an index modulation (IM)-enhanced ALOHA scheme. Users partition their information into three parallel streams: compressed sensing (CS) pilots, BPSK-modulated symbols, and IM-based subslot selection—enabling joint optimization of concurrent transmission and user identification. This work is the first to embed IM into the ALOHA subslot selection mechanism and designs a hard-decision joint decoder integrating CS signal reconstruction, maximum-likelihood (ML) grant-free superposition coding decomposition, and IM demodulation. Furthermore, a low-complexity decomposition algorithm based on convex approximation is introduced. Simulation results demonstrate that the proposed scheme significantly reduces packet error rate and computational complexity in short-packet, massive-connectivity scenarios, outperforming existing ALOHA-based URA approaches.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Mechanism Design

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Search and Retrieval-Augmented AI: Web crawling and indexing

Abstract

In this paper, an improved ALOHA-based unsourced random access (URA) scheme is proposed in MIMO channels. The channel coherent interval is divided into multiple sub-slots and each active user selects several sub-slots to send its codeword, namely, the channel access pattern. To be more specific, the data stream of each active user is divided into three parts. The first part is mapped as the compressed sensing (CS) pilot, which also serves for the consequent channel estimation. The second part is modulated by binary phase shift keying (BPSK). The obtained CS pilot and the antipodal BPSK signal are concatenated as its codeword. After that, the codeword of each active user is sent repeatedly based on its channel access pattern, which is determined by the third part of the information bits, namely, index modulation (IM). On the receiver side, a hard decision-based decoder is proposed which includes the CS decoder, maximal likelihood (ML)-based superposed codeword decomposer (SCD), and IM demodulator. To further reduce the complexity of the proposed decoder, a simplified SCD based on convex approximation is considered. The performance analysis is also provided. The exhaustive computer simulations confirm the superiority of our proposal.

Problem

• Improving ALOHA-based URA with index modulation in MIMO channels
• Proposing efficient decoding via CS, ML-based SCD, and IM demodulator
• Reducing decoder complexity using convex approximation for SCD

Innovation

• Improved ALOHA-based URA with index modulation
• Divided data stream into three modulated parts
• Hard decision-based decoder with simplified SCD