Experimental Study of User Selection for Dense Indoor Massive MIMO
| Autor: | Qing Wang, Cheng-Ming Chen, Sofie Pollin, Abdo Gaber, Andrea P. Guevara |
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| Rok vydání: | 2019 |
| Předmět: |
Computer science
Orthogonal frequency-division multiplexing Real-time computing MIMO 020206 networking & telecommunications 02 engineering and technology Scheduling (computing) Low complexity Base station Software deployment 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Minification Selection method |
| Zdroj: | INFOCOM Workshops IEEE INFOCOM 2019-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) |
| Popis: | Multi-user massive MIMO is capable of serving at least ten users simultaneously. However, when users are closely located, their high inter-user correlation is undesired; under this condition, these densely packed users must be separated by higher layer scheduling. In this paper, a low complexity greedy user selection method combined with the incremental inter-user-interference minimization criterion is proposed. The resulting algorithm is evaluated using system level simulations that rely on the measured indoor line-of-sight channel, with 64 antennas in the base station at 2.61GHz. Measurements are carried out using four different centralized and distributed base station antenna geometries, to evaluate the user selection performance for different indoor scenarios. Our evaluation shows that in a room with 64 densely deployed users, the proposed method increases the overall system sum rate, by up to 60%. Moreover, when applying this method, the distributed deployment outperforms the collocated scenario by 18% on average. |
| Databáze: | OpenAIRE |
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