Journal
AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS
Volume 89, Issue -, Pages 181-190Publisher
ELSEVIER GMBH
DOI: 10.1016/j.aeue.2018.03.038
Keywords
5G; Massive MIMO; BER; Low complexity; Sparsity; Inter-Cell Interference
Funding
- Hankuk University of Foreign Studies research fund
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Massive MIMO (multiple-input-multiple-output) is one of the key technologies of 5G mobile cellular networks, which can form a huge antenna array by providing a large number of antennas at the cell base station. It will greatly improve the channel capacity and spectrum utilization and has become a hotspot in the field of wireless communications in recent years Aiming at the high complexity of channel estimation algorithm for massive MIMO system, a sparse channel estimation algorithm with low complexity is proposed based on the inherent sparsity of wireless communication channel. The algorithm separates the channel taps from the noise space on the basis of the traditional discrete Fourier transform (DFT) channel estimation, so that the channel estimation only needs to calculate the part of the channel tap, so the computational complexity of the algorithm is greatly reduced. The simulation results show that the proposed algorithm can achieve near minimum mean square error (MMSE) performance while maintaining low complexity. Moreover, the Bit Error Rate and Inter-Cell Interference also indicates that the proposed improved algorithm shows better overall performance than the conventional algorithms which makes it suitable from practical perspective.
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