Name
Abstract | ||
|---|---|---|
The performance of centralized and distributed massive MIMO deployments are analyzed for indoor office scenarios. The distributed deployments use one of the following precoding methods: (1) local precoding with local channel state information (CSI) to the user equipments (UEs) that it serves; (2) large-scale MIMO with local CSI to all UEs in the network; (3) network MIMO with global CSI. For the distributed deployments (2) and (3), it is shown that using twice as many base station antennas as data streams provides many of the massive MIMO benefits in terms of spectral efficiency and fairness. This is in contrast to the centralized deployment and the distributed deployment (1) where more antennas are needed. Two of the main conclusions are that distributing base stations helps to overcome wall penetration loss; however, a backhaul is required to mitigate inter-cell interference. The effect of estimation errors on the performance is also quantified. |
Year | Venue | Field |
|---|---|---|
2018 | IEEE Transactions on Wireless Communications | Base station,Mathematical optimization,Data stream mining,Backhaul (telecommunications),Computer network,MIMO,Spectral efficiency,Interference (wave propagation),Precoding,Mathematics,Channel state information |
DocType | Volume | Citations |
Journal | abs/1801.02888 | 0 |
PageRank | References | Authors |
0.34 | 21 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefan Dierks | 1 | 19 | 2.66 |
| Gerhard Kramer | 2 | 445 | 34.21 |
| Berthold Panzner | 3 | 196 | 9.79 |
| Wolfgang Zirwas | 4 | 194 | 7.75 |