Abstract-This paper proposes novel pilot optimization and channel estimation algorithm for the downlink multiuser mas sive multiple input multiple output (MIMO) system with K decentralized single antenna mobile stations (MSs), and time division duplex (TDD) channel estimation which is performed by utilizing N pilot symbols. The proposed algorithm is explained as follows. First, we formulate the channel estimation problem as a weighted sum mean square error (WSMSE) minimization problem containing pilot symbols and introduced variables. Second, for fixed pilot symbols, the introduced variables are optimized using minimum mean square error (MMSE) and  Multiple input multiple output (MIMO) system is a promis ing approach for exploiting the spectral efficiency of wireless channels [1]- [3] . The MIMO system could be either a single user MIMO or multiuser MIMO. The single user MIMO system requires expensive multi antenna terminals at both the transmitter and receiver sides. Furthermore, one may not achieve the mUltiplexing gain of the single user MIMO channel when the propagation environment is poorly scattered [4] . In a multiuser MIMO system, the base station (BS) will serve several decentralized mobile stations (MSs). For such a system, employing multi-antenna at the BS and very cheap single antenna terminals at each MS appears to be the most economical design approach. And, in practice, as the MSs are sufficiently far apart from each other, the multiplexing gain of a MIMO channel can be ensured for multiuser scenario. The multiuser MIMO system could be either in the uplink or downlink channel. For the downlink channel, it is recently shown in [5] that the full advantages of a MIMO system can be exploited using simple beamforming strategies such as maximum ratio transmission (MRT) or zero forcing (ZF), just by deploying very large number of antennas at the BS (i.e., Massive MIMO system) [4] . The basic idea is that when the number of BS antennas are large, the channel vector of any two MSs will be almost uncorrelated and the instantaneous channel gain of each MS can be well approximated (with high probability) from its second order statistics. However, to enjoy this benefit, the channel vector of each MS needs to be known (or estimated reliably) at the BS. For the downlink multiuser MIMO system, channel esti mation can be performed either in frequency division duplex (FDD) or time division duplex (TDD) approaches. In an FDD approach, first, the BS transmits a pilot sequence to all MSs. Then, each MS will estimate its own channel. Finally, the estimated channel is feedback to the BS via feedback channel. In a conventional channel estimation approach, the pilot sequences needs to be orthogonal [6] . To achieve this requirement, the BS requires N symbol periods (which is significant if N is very large). In the TDD system, first, each MSs transmits its own pilot symbols to the BS. Then, the BS will estimate the uplink channel and assign the conjugate of this estimated channel as its downlink version. Here also, the conventional orthogonal pilot design method requires K symbol periods. In a massive MIMO system, as K < < M, the TDD channel estimation method is the most reasonable approach [5] . However, when the number of MSs (K) is large, still allocating K symbol periods for pilot transmission may not be practically feasible. When N < K, one possible pilot design approach could be to reuse the pilots of the first N MSs for the extra K -N MSs. However, as will be seen later, such pilot reuse approach will create a so called pilot contamination. When there is a pilot contamination, the performance of the minimum mean square error (MMSE) channel estimator and downlink beam former degrades drastically [5] ' . To alleviate the effect of pilot contamination, the Eigenvalue decomposition (EVD) based channel estimation approach is proposed in [7] . However, the complexity of this channel estimator is large when M is very large which is the case in massive MIMO. In the current paper, we propose novel pilot optimization and channel estimation algorithm for the downlink multiuser massive MIMO system with K single antenna MSs and I We would like to mention here that the pilot contamination in [51 is justified in the context of multi-cell MIMO system. However, the basic idea of pilot contamination is similar to that of the current paper.
In REF , weighted-sum mean-square error minimization and Rayleigh quotient methods were used to determine pilot signals that reduce pilot contamination and improve channel estimation.
Pilot optimization and channel estimation for multiuser massive MIMO systems
2014 48th Annual Conference on Information Sciences and Systems (CISS)
2014 48th Annual Conference on Information Sciences and Systems (CISS)
Mathematics Computer Science