TY - GEN
T1 - Massive MIMO architecture for 5G networks
T2 - 2014 11th International Symposium on Wireless Communications Systems, ISWCS 2014
AU - Qiao, Deli
AU - Wu, Ye
AU - Chen, Yan
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/10/21
Y1 - 2014/10/21
N2 - Massive MIMO has been identified as one of the promising disruptive air interface technologies to address the massive capacity requirement demanded by 5G wireless communications. Most of the existing works showed different benefits of massive MIMO system but for the co-located deployment scenario. In this paper, we are interested to find out extra benefits that may be brought by distributing the massive number of antennas to different levels. Specifically, we compare the performance of co-located and distributed deployment scenarios in the framework of area spectrum efficiency (ASE) and area energy efficiency (AEE) tradeoff. Closed-form expressions are derived to help discover important design insights. For instance, it is interesting to see the distribution of the massive antennas always helps to improve ASE, but not the case for AEE. Moreover, with the large number of transmit antennas available and the practical cost of channel estimation considered, collaboration between cells is not always welcomed in each deployment scenario and the positive use cases depend on system parameters such as the number of antennas and the way they are distributed.
AB - Massive MIMO has been identified as one of the promising disruptive air interface technologies to address the massive capacity requirement demanded by 5G wireless communications. Most of the existing works showed different benefits of massive MIMO system but for the co-located deployment scenario. In this paper, we are interested to find out extra benefits that may be brought by distributing the massive number of antennas to different levels. Specifically, we compare the performance of co-located and distributed deployment scenarios in the framework of area spectrum efficiency (ASE) and area energy efficiency (AEE) tradeoff. Closed-form expressions are derived to help discover important design insights. For instance, it is interesting to see the distribution of the massive antennas always helps to improve ASE, but not the case for AEE. Moreover, with the large number of transmit antennas available and the practical cost of channel estimation considered, collaboration between cells is not always welcomed in each deployment scenario and the positive use cases depend on system parameters such as the number of antennas and the way they are distributed.
UR - https://www.scopus.com/pages/publications/84911975808
U2 - 10.1109/ISWCS.2014.6933345
DO - 10.1109/ISWCS.2014.6933345
M3 - 会议稿件
AN - SCOPUS:84911975808
T3 - 2014 11th International Symposium on Wireless Communications Systems, ISWCS 2014 - Proceedings
SP - 192
EP - 197
BT - 2014 11th International Symposium on Wireless Communications Systems, ISWCS 2014 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 26 August 2014 through 29 August 2014
ER -
