27 research outputs found
Fundamental Asymptotic Behavior of (Two-User) Distributed Massive MIMO
This paper considers the uplink of a distributed Massive MIMO network where
base stations (BSs), each equipped with antennas, receive data from
users. We study the asymptotic spectral efficiency (as )
with spatial correlated channels, pilot contamination, and different degrees of
channel state information (CSI) and statistical knowledge at the BSs. By
considering a two-user setup, we can simply derive fundamental asymptotic
behaviors and provide novel insights into the structure of the optimal
combining schemes. In line with [1], when global CSI is available at all BSs,
the optimal minimum-mean squared error combining has an unbounded capacity as
, if the global channel covariance matrices of the users are
asymptotically linearly independent. This result is instrumental to derive a
suboptimal combining scheme that provides unbounded capacity as
using only local CSI and global channel statistics. The latter scheme is shown
to outperform a generalized matched filter scheme, which also achieves
asymptotic unbounded capacity by using only local CSI and global channel
statistics, but is derived following [2] on the basis of a more conservative
capacity bound.Comment: 6 pages, 2 figures, to be presented at GLOBECOM 2018, Abu Dhab
Self-Learning Detector for the Cell-Free Massive MIMO Uplink: The Line-of-Sight Case
The precoding in cell-free massive multiple-input multiple-output (MIMO)
technology relies on accurate knowledge of channel responses between users
(UEs) and access points (APs). Obtaining high-quality channel estimates in turn
requires the path losses between pairs of UEs and APs to be known. These path
losses may change rapidly especially in line-of-sight environments with moving
blocking objects. A difficulty in the estimation of path losses is pilot
contamination, that is, simultaneously transmitted pilots from different UEs
that may add up destructively or constructively by chance, seriously affecting
the estimation quality (and hence the eventual performance). A method for
estimation of path losses, along with an accompanying pilot transmission
scheme, is proposed that works for both Rayleigh fading and line-of-sight
channels and that significantly improves performance over baseline
state-of-the-art. The salient feature of the pilot transmission scheme is that
pilots are structurally phase-rotated over different coherence blocks
(according to a pre-determined function known to all parties), in order to
create an effective statistical distribution of the received pilot signal that
can be efficiently exploited by the proposed estimation algorithm.Comment: Paper accepted for presentation in IEEE SPAWC 2020 - 21st IEEE
International Workshop on Signal Processing Advances in Wireless
Communications. {\copyright} 2020 IEEE. Personal use of this material is
permitted. Permission from IEEE must be obtained for all other use
Downlink Power Control in Massive MIMO Networks with Distributed Antenna Arrays
In this paper, we investigate downlink power control in massive
multiple-input multiple-output (MIMO) networks with distributed antenna arrays.
The base station (BS) in each cell consists of multiple antenna arrays, which
are deployed in arbitrary locations within the cell. Due to the spatial
separation between antenna arrays, the large-scale propagation effect is
different from a user to different antenna arrays in a cell, which makes power
control a challenging problem as compared to conventional massive MIMO. We
assume that the BS in each cell obtains the channel estimates via uplink
pilots. Based on the channel estimates, the BSs perform maximum ratio
transmission for the downlink. We then derive a closed-form spectral efficiency
(SE) expression, where the channels are subject to correlated fading. Utilizing
the derived expression, we propose a max-min power control algorithm to ensure
that each user in the network receives a uniform quality of service. Numerical
results demonstrate that, for the network considered in this work, optimizing
for max-min SE through the max-min power control improves the sum SE of the
network as compared to equal power allocation.Comment: Accepted to appear in ICC 2018, Kansas City, M