Iterative Receiver of Uplink Massive MIMO Unsourced Random Access

Liang, Zijie; Zheng, Jianping

doi:10.1109/iwcmc51323.2021.9498916

Cited by 4 publications

(3 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Each active user j selects a codeword v j ∈ C Ttot×1 (corresponding to a B-bit packet) from the common codebook V over T tot complex channel usages for transmission. Following [10]- [12], we assume that the channel vectors {h k } are constant over the T tot channel usages. Then the received signal y at the AP is modeled as…”

Section: A System Modelmentioning

confidence: 99%

“…The first coding scheme for MIMO URA is proposed in [7] based on the segmented tree code. Various optimizations on the tree code and related receiver design are further investigated in [8]- [10], and noticeable performance improvement has been observed. In [11], a joint sparse regression code (SPARC) and low density parity check (LDPC) coding scheme is proposed to achieve a better coding gain.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Receiver Design for MIMO Unsourced Random Access with SKP Coding

Han¹,

Yuan²,

Xu³

et al. 2022

Preprint

View full text Add to dashboard Cite

In this letter, we extend the sparse Kronecker-product (SKP) coding scheme, originally designed for the additive white Gaussian noise (AWGN) channel, to multiple input multiple output (MIMO) unsourced random access (URA). With the SKP coding adopted for MIMO transmission, we develop an efficient Bayesian iterative receiver design to solve the intended challenging trilinear factorization problem. Numerical results show that the proposed design outperforms the existing counterparts, and that it performs well in all simulated settings with various antenna sizes and active-user numbers.

show abstract

Section: A System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Receiver Design for MIMO Unsourced Random Access with SKP Coding

Han¹,

Yuan²,

Xu³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…In [10][11][12][13][14][15][16][17][18][19], schemes are presented that seek to separate user's signals and recover them using single-user coding techniques. These results are extended to multiple-input multiple-output (MIMO) scenarios in [20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Decoding Algorithm for Coded Compressed Sensing with Applications to Unsourced Random Access

Amalladinne

Chamberland

et al. 2022

Sensors

View full text Add to dashboard Cite

Unsourced random access (URA) has emerged as a pragmatic framework for next-generation distributed sensor networks. Within URA, concatenated coding structures are often employed to ensure that the central base station can accurately recover the set of sent codewords during a given transmission period. Many URA algorithms employ independent inner and outer decoders, which can help reduce computational complexity at the expense of a decay in performance. In this article, an enhanced decoding algorithm is presented for a concatenated coding structure consisting of a wide range of inner codes and an outer tree-based code. It is shown that this algorithmic enhancement has the potential to simultaneously improve error performance and decrease the computational complexity of the decoder. This enhanced decoding algorithm is applied to two existing URA algorithms, and the performance benefits of the algorithm are characterized. Findings are supported by numerical simulations.

show abstract

Receiver Design for MIMO Unsourced Random Access With Sparse Kronecker-Product Coding

Yuan

Wang

2023

IEEE Wireless Commun. Lett.

View full text Add to dashboard Cite

Iterative Receiver of Uplink Massive MIMO Unsourced Random Access

Cited by 4 publications

References 11 publications

Receiver Design for MIMO Unsourced Random Access with SKP Coding

Receiver Design for MIMO Unsourced Random Access with SKP Coding

An Enhanced Decoding Algorithm for Coded Compressed Sensing with Applications to Unsourced Random Access

Receiver Design for MIMO Unsourced Random Access With Sparse Kronecker-Product Coding

Contact Info

Product

Resources

About