Pilot Optimization in Multicell Massive MIMO

Teeti, M. A.1; Wang, Rui1; Liu, Yingzhuang2; Ni, Qiang3

10.1109/ICCS.2016.7833554

2016

978-1-5090-3424-6

2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS (ICCS)

1-6

14-16 Dec. 2016

Shenzhen, China

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

In this paper we consider pilot contamination problem in the uplink of a multi-cell massive MIMO. Each base station (BS) is equipped with M (unlimited) antennas serving K (large but finite) users. Further, we let t (pilot length) be an arbitrary but small value. As such, pilot optimization is formulated as a multi-objective optimization problem (MOP). It is shown that, when power control is enabled, maximally spaced sequences solve a worst-case signal-to-interference (SIR) problem only under a special channel case, whereas the general channel case doesn't admit a simple solution. Motivated by the epsilon-constraint technique in MOP, we propose a low-complexity algorithm for optimizing pilots of different users from a fixed orthonormal basis in an iterative manner. For only a few iterations, the algorithm shows good convergence property, which is supposed to converge to a Pareto-optimal solution. The numerical results show that the algorithm gives rise to a significant improvement of the cell throughput as well as the per-user mean SIR and per-user mean rate.

pilot contamination massive MIMO multi-objective optimization epsilon-constraint technique

第一 ; 通讯

英语

CPCI-S ; EI

EU FP7 CROWN Project[PIRSES-GA-2013-610524]

Telecommunications

Telecommunications

WOS:000401807600005

20170903398381

Computational complexity ; Iterative methods ; Pareto principle ; Power control

Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory:721.1 ; Specific Variables Control:731.3 ; Optimization Techniques:921.5 ; Numerical Methods:921.6

Web of Science

1.Southern Univ Sci & Technol China, Dept Elect & Elect Engn, Shenzhen, Guangdong, Peoples R China
2.Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan, Hubei, Peoples R China
3.Univ Lancaster, Sch Comp & Commun, Lancaster, Lancs, England

Teeti, M. A.,Wang, Rui,Liu, Yingzhuang,et al. Pilot Optimization in Multicell Massive MIMO[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2016:1-6.