A low complexity iterative soft-decision feedback MMSE-PIC detection algorithm for massive MIMO

In MIMO applications, the minimum mean square error parallel interference cancellation (MMSE-PIC) based Soft-Input Soft-Output (SISO) detector has been widely adopted because of its low complexity and good bit error rate (BER) performance. In this paper, we firstly propose to use a Gaussian model ba...

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Veröffentlicht in:2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) S. 2939 - 2943
Hauptverfasser: Licai Fang, Lu Xu, Qinghua Guo, Defeng Huang, Nordholm, Sven
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.04.2015
Schlagworte:
Complexity theory
Decoding
MIMO
Modulation
Silicon
ISSN:1520-6149
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Zusammenfassung:In MIMO applications, the minimum mean square error parallel interference cancellation (MMSE-PIC) based Soft-Input Soft-Output (SISO) detector has been widely adopted because of its low complexity and good bit error rate (BER) performance. In this paper, we firstly propose to use a Gaussian model based MMSE detection algorithm to implement MMSE-PIC with low complexity. This algorithm, which can detect a length-N r received data block by a single Hermitian matrix (sized N t × N t ) inversion, is especially preferable in Massive MIMO up-link applications where the number of transmit antennas N t from each end terminal is much less than the number of receive antennas N r in the Base Station. Then we derive a new method to calculate the matrix inversion by a linear combination of two matrices, which reduces the complexity from O(N t 3 ) to O(N t 2 ). At last, in order to improve the system performance for the first pass when there is no a priori information available, a self-iteration method is proposed and thus a system performance gain of 1dB to 2dB is achieved at the cost of modest complexity increase.
ISSN:1520-6149
DOI:10.1109/ICASSP.2015.7178509