886 research outputs found
Joint Pilot Design and Uplink Power Allocation in Multi-Cell Massive MIMO Systems
This paper considers pilot design to mitigate pilot contamination and provide
good service for everyone in multi-cell Massive multiple input multiple output
(MIMO) systems. Instead of modeling the pilot design as a combinatorial
assignment problem, as in prior works, we express the pilot signals using a
pilot basis and treat the associated power coefficients as continuous
optimization variables. We compute a lower bound on the uplink capacity for
Rayleigh fading channels with maximum ratio detection that applies with
arbitrary pilot signals. We further formulate the max-min fairness problem
under power budget constraints, with the pilot signals and data powers as
optimization variables. Because this optimization problem is non-deterministic
polynomial-time hard due to signomial constraints, we then propose an algorithm
to obtain a local optimum with polynomial complexity. Our framework serves as a
benchmark for pilot design in scenarios with either ideal or non-ideal
hardware. Numerical results manifest that the proposed optimization algorithms
are close to the optimal solution obtained by exhaustive search for different
pilot assignments and the new pilot structure and optimization bring large
gains over the state-of-the-art suboptimal pilot design.Comment: 16 pages, 8 figures. Accepted to publish at IEEE Transactions on
Wireless Communication
Ubiquitous Cell-Free Massive MIMO Communications
Since the first cellular networks were trialled in the 1970s, we have
witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic
growth has been managed by a combination of wider bandwidths, refined radio
interfaces, and network densification, namely increasing the number of antennas
per site. Due its cost-efficiency, the latter has contributed the most. Massive
MIMO (multiple-input multiple-output) is a key 5G technology that uses massive
antenna arrays to provide a very high beamforming gain and spatially
multiplexing of users, and hence, increases the spectral and energy efficiency.
It constitutes a centralized solution to densify a network, and its performance
is limited by the inter-cell interference inherent in its cell-centric design.
Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive
MIMO system implementing coherent user-centric transmission to overcome the
inter-cell interference limitation in cellular networks and provide additional
macro-diversity. These features, combined with the system scalability inherent
in the Massive MIMO design, distinguishes ubiquitous cell-free Massive MIMO
from prior coordinated distributed wireless systems. In this article, we
investigate the enormous potential of this promising technology while
addressing practical deployment issues to deal with the increased
back/front-hauling overhead deriving from the signal co-processing.Comment: Published in EURASIP Journal on Wireless Communications and
Networking on August 5, 201
Large System Analysis of Power Normalization Techniques in Massive MIMO
Linear precoding has been widely studied in the context of Massive
multiple-input-multiple-output (MIMO) together with two common power
normalization techniques, namely, matrix normalization (MN) and vector
normalization (VN). Despite this, their effect on the performance of Massive
MIMO systems has not been thoroughly studied yet. The aim of this paper is to
fulfill this gap by using large system analysis. Considering a system model
that accounts for channel estimation, pilot contamination, arbitrary pathloss,
and per-user channel correlation, we compute tight approximations for the
signal-to-interference-plus-noise ratio and the rate of each user equipment in
the system while employing maximum ratio transmission (MRT), zero forcing (ZF),
and regularized ZF precoding under both MN and VN techniques. Such
approximations are used to analytically reveal how the choice of power
normalization affects the performance of MRT and ZF under uncorrelated fading
channels. It turns out that ZF with VN resembles a sum rate maximizer while it
provides a notion of fairness under MN. Numerical results are used to validate
the accuracy of the asymptotic analysis and to show that in Massive MIMO,
non-coherent interference and noise, rather than pilot contamination, are often
the major limiting factors of the considered precoding schemes.Comment: 12 pages, 3 figures, Accepted for publication in the IEEE
Transactions on Vehicular Technolog
Joint Power Allocation and User Association Optimization for Massive MIMO Systems
This paper investigates the joint power allocation and user association
problem in multi-cell Massive MIMO (multiple-input multiple-output) downlink
(DL) systems. The target is to minimize the total transmit power consumption
when each user is served by an optimized subset of the base stations (BSs),
using non-coherent joint transmission. We first derive a lower bound on the
ergodic spectral efficiency (SE), which is applicable for any channel
distribution and precoding scheme. Closed-form expressions are obtained for
Rayleigh fading channels with either maximum ratio transmission (MRT) or zero
forcing (ZF) precoding. From these bounds, we further formulate the DL power
minimization problems with fixed SE constraints for the users. These problems
are proved to be solvable as linear programs, giving the optimal power
allocation and BS-user association with low complexity. Furthermore, we
formulate a max-min fairness problem which maximizes the worst SE among the
users, and we show that it can be solved as a quasi-linear program. Simulations
manifest that the proposed methods provide good SE for the users using less
transmit power than in small-scale systems and the optimal user association can
effectively balance the load between BSs when needed. Even though our framework
allows the joint transmission from multiple BSs, there is an overwhelming
probability that only one BS is associated with each user at the optimal
solution.Comment: 16 pages, 12 figures, Accepted by IEEE Trans. Wireless Commu
Downlink Spectral Efficiency of Cell-Free Massive MIMO with Full-Pilot Zero-Forcing
Cell-free Massive multiple-input multiple-output (MIMO) ensures ubiquitous
communication at high spectral efficiency (SE) thanks to increased
macro-diversity as compared cellular communications. However, system
scalability and performance are limited by fronthauling traffic and
interference. Unlike conventional precoding schemes that only suppress
intra-cell interference, full-pilot zero-forcing (fpZF), introduced in [1],
actively suppresses also inter-cell interference, without sharing channel state
information (CSI) among the access points (APs). In this study, we derive a new
closed-form expression for the downlink (DL) SE of a cell-free Massive MIMO
system with multi-antenna APs and fpZF precoding, under imperfect CSI and pilot
contamination. The analysis also includes max-min fairness DL power
optimization. Numerical results show that fpZF significantly outperforms
maximum ratio transmission scheme, without increasing the fronthauling
overhead, as long as the system is sufficiently distributed.Comment: Paper published in 2018 IEEE Global Conference on Signal and
Information Processing (GlobalSIP). {\copyright} 2019 IEEE. Personal use of
this material is permitted. Permission from IEEE must be obtained for all
other use
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