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Low-Complexity Near-Optimal Iterative Sequential Detection for Uplink Massive MIMO Systems
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DOI：10.1109/LCOMM.2016.2637366.png)
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A novel low-complexity iterative sequential detection algorithm is proposed for near-optimal detection in uplink massive multiple-input multiple-output systems. In every iteration of the proposed algorithm, symbol transmitted from each user is detected sequentially while nulling the interference from all the other users. In contrast with recently proposed methods such as polynomial expansion, dual band Newton iteration, and Jacobi iteration, the proposed algorithm performs superior in terms of precision and computational complexity, and achieves better performance when the number of users increases. Simulation results validate superiority of the proposed algorithm over the recently reported methods.
Keyword:
Massive MIMO
matrix inversion
Neumann series
bit error rate
computational complexity
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4.4
论文数:
1.3W
被引数:
2.2W
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