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

Linjie Yang, Pingzhi Fan, Zhiguo Ding, Jingqiu Gao

TL;DR

This work tackles unsourced random access in ultra-dense uplink scenarios by proposing an improved ALOHA-based URA that leverages index modulation in a MIMO setting. Each active user encodes information across a CS pilot for AUD/CE, a BPSK data stream, and an IM-driven channel-access pattern that selects sub-slots for codeword repetition, enabling compact codewords while maintaining robust channel estimation. The receiver combines a CS-based decoder, an ML-based superposed codeword decomposer, and an IM demodulator in a hard-decision framework, with a convex SDR-based SCD option to reduce complexity; throughput is analyzed via density evolution and validated by simulations. Results show substantial gains over sparse-graph URA approaches in terms of decodable user count and throughput, particularly under short coherence blocks relevant to IoT and fast-moving devices.

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.

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

TL;DR

This work tackles unsourced random access in ultra-dense uplink scenarios by proposing an improved ALOHA-based URA that leverages index modulation in a MIMO setting. Each active user encodes information across a CS pilot for AUD/CE, a BPSK data stream, and an IM-driven channel-access pattern that selects sub-slots for codeword repetition, enabling compact codewords while maintaining robust channel estimation. The receiver combines a CS-based decoder, an ML-based superposed codeword decomposer, and an IM demodulator in a hard-decision framework, with a convex SDR-based SCD option to reduce complexity; throughput is analyzed via density evolution and validated by simulations. Results show substantial gains over sparse-graph URA approaches in terms of decodable user count and throughput, particularly under short coherence blocks relevant to IoT and fast-moving devices.

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.
Paper Structure (19 sections, 44 equations, 12 figures, 1 table, 1 algorithm)

This paper contains 19 sections, 44 equations, 12 figures, 1 table, 1 algorithm.

Figures (12)

  • Figure 1: Illustration of the proposed hybrid encoding process with index modulation, where $N_{slot}=5, K = 2$.
  • Figure 2: The decoding process of the proposed scheme on the $n_{s}$-th sub-slot.
  • Figure 3: The collision scenario where two different active users select the same CS pilot, where $K=2$: (a) no overlap, (b) partial overlap, (c) complete overlap.
  • Figure 4: The tanner graph of the spreading step in Fig. \ref{['system_model']}.
  • Figure 5: The symbol number of the channel coherent duration, $N_{cd}$ versus velocity $v \rm (km/h)$.
  • ...and 7 more figures