Low Complexity Iterative Parallel Interference Cancellation Detection Algorithms for Massive MIMO Systems

Bin SHEN; Shufeng ZHAO; Chun JIN

doi:10.11999/JEIT180111

Volume 40 Issue 12

Nov. 2018

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Bin SHEN, Shufeng ZHAO, Chun JIN. Low Complexity Iterative Parallel Interference Cancellation Detection Algorithms for Massive MIMO Systems[J]. Journal of Electronics & Information Technology, 2018, 40(12): 2970-2978. doi: 10.11999/JEIT180111

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Bin SHEN, Shufeng ZHAO, Chun JIN. Low Complexity Iterative Parallel Interference Cancellation Detection Algorithms for Massive MIMO Systems[J]. Journal of Electronics & Information Technology, 2018, 40(12): 2970-2978. doi: 10.11999/JEIT180111

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Low Complexity Iterative Parallel Interference Cancellation Detection Algorithms for Massive MIMO Systems

doi: 10.11999/JEIT180111

Chongqing Key Laboratory of Mobile Communications, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Funds: The Innovation Project of the Common Key Technology of Chongqing Science and Technology Industry (cstc2015zdcy-ztzx40008)

Received Date: 2018-01-25
Rev Recd Date: 2018-05-29

Available Online: 2018-08-14

Publish Date: 2018-12-01

Abstract

Abstract

Based on interference cancellation method, a low complexity Iterative Parallel Interference Cancellation (IPIC) algorithm is proposed for the uplink of massive MIMO systems. The proposed algorithm avoids the high complexity matrix inversion required by the linear detection algorithm, and hence the complexity is maintained only at $({\cal O}({K^2}))$ . Meanwhile, the noise prediction mechanism is introduced and the noise-prediction aided iterative parallel interference cancellation algorithm is proposed to improve further the detection performance. Considering the residual inter-antenna interference, a low-complexity soft output signal detection algorithm is proposed as well. The simulation results show that the complexity of all the proposed signal detection methods are better than that of the MMSE detection algorithm. With only a small number of iterations, the proposed algorithm achieves its performance quite close to or even surpassing that of the MMSE algorithm.
- Massive MIMO,
- Low-complexity,
- Iterative Parallel Interference Cancellation (IPIC),
- Noise-prediction,
- Soft output

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References

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