Name
Title | ||
|---|---|---|
Massive MIMO with Transceiver Hardware Impairments: Performance Analysis and Phase Noise Error Minimization. |
Abstract | ||
|---|---|---|
In this paper, we investigate the impact of hardware impairments (HWIs) on the performance of a downlink massive MIMO system. We consider a single-cell system with maximum ratio transmission (MRT) as precoding scheme, and with all the HWIs characteristics such as phase noise, distortion noise, and amplified thermal noise. Based on the system model, we derive closed-form expressions for a typical user data rate under two scenarios: when a common local oscillator (CLO) is used at the base station and when separated oscillators (SLOs) are used. We also derive closed-form expressions for the downlink transmit power required for some desired per-user data rate under each scenario. Compared to the conventional system with ideal transceiver hardware, our results show that impairments of hardware make a finite upper limit on the user's downlink channel capacity; and as the number of base station antennas grows large, it is only the hardware impairments at the users that mainly limit the capacity. Our results also show that SLOs configuration provides higher data rate than CLO at the price of higher power consumption. An approach to minimize the effect of the hardware impairments on the system performance is also proposed in the paper. In our approach, we show that by reducing the cell size, the effect of accumulated phase noise during channel estimation time is minimized and hence the user capacity is increased, and the downlink transmit power is decreased. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3837/tiis.2019.05.007 | KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS |
Keywords | DocType | Volume |
Massive MIMO,transceiver hardware impairments,channel estimation,cell size,system performance | Journal | 13 |
Issue | ISSN | Citations |
5 | 1976-7277 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| parfait i tebe | 1 | 1 | 1.37 |
| Guangjun Wen | 2 | 52 | 13.05 |
| Jian Li | 3 | 162 | 44.60 |
| Yongjun Huang | 4 | 0 | 0.68 |
| Affum E. Ampoma | 5 | 0 | 0.34 |
| Kwame Oteng Gyasi | 6 | 0 | 0.34 |