TY - JOUR
T1 - Frequency Reuse of Beam Allocation for Multiuser Massive MIMO Systems
AU - Wang, Junyuan
AU - Zhu, Huiling
AU - Gomes, Nathan J.
AU - Wang, Jiangzhou
PY - 2018/4/1
Y1 - 2018/4/1
N2 - Massive multiple-input-multiple-output (MIMO) has become a promising technique to provide high-data-rate communication in fifth-generation (5G) mobile systems, thanks to its ability to form narrow and high-gain beams. Among various massive MIMO beamforming techniques, the fixed-beam scheme has attracted considerable attention due to its simplicity. In this paper, we focus on a fixed-beam based multiuser massive MIMO system where each user is served by a beam allocated to it. To maximize the sum data rate, a greedy beam allocation algorithm is proposed under the practical condition that the number of radio frequency (RF) chains is smaller than the number of users. Simulation results show that our proposed greedy algorithm achieves nearly optimal sum data rate. As only the sum data rate is optimized, there are some “worst-case” users who could suffer from strong inter-beam interference and thus experience low data rate. To improve the individual data rates of the worst-case users while maintaining the sum data rate, an adaptive frequency reuse scheme is proposed. Simulation results corroborate that our proposed adaptive frequency reuse strategy can greatly improve the worst-case users’ data rates and the max-min fairness among served users without sacrificing the sum data rate.
AB - Massive multiple-input-multiple-output (MIMO) has become a promising technique to provide high-data-rate communication in fifth-generation (5G) mobile systems, thanks to its ability to form narrow and high-gain beams. Among various massive MIMO beamforming techniques, the fixed-beam scheme has attracted considerable attention due to its simplicity. In this paper, we focus on a fixed-beam based multiuser massive MIMO system where each user is served by a beam allocated to it. To maximize the sum data rate, a greedy beam allocation algorithm is proposed under the practical condition that the number of radio frequency (RF) chains is smaller than the number of users. Simulation results show that our proposed greedy algorithm achieves nearly optimal sum data rate. As only the sum data rate is optimized, there are some “worst-case” users who could suffer from strong inter-beam interference and thus experience low data rate. To improve the individual data rates of the worst-case users while maintaining the sum data rate, an adaptive frequency reuse scheme is proposed. Simulation results corroborate that our proposed adaptive frequency reuse strategy can greatly improve the worst-case users’ data rates and the max-min fairness among served users without sacrificing the sum data rate.
KW - Frequency reuse
KW - beam allocation
KW - achievable data rate
KW - worst-case users
KW - massive multiple-input-multiple-output (MIMO)
UR - http://www.scopus.com/inward/record.url?scp=85040917513&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85040917513&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/d14cd114-7c96-3e96-94f4-b2801dab9195/
U2 - 10.1109/TWC.2018.2793227
DO - 10.1109/TWC.2018.2793227
M3 - Article (journal)
SN - 1536-1276
VL - 17
SP - 2346
EP - 2359
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 4
ER -