34 research outputs found
Optimal Linear Precoding in Multi-User MIMO Systems: A Large System Analysis
We consider the downlink of a single-cell multi-user MIMO system in which the
base station makes use of antennas to communicate with single-antenna
user equipments (UEs) randomly positioned in the coverage area. In particular,
we focus on the problem of designing the optimal linear precoding for
minimizing the total power consumption while satisfying a set of target
signal-to-interference-plus-noise ratios (SINRs). To gain insights into the
structure of the optimal solution and reduce the computational complexity for
its evaluation, we analyze the asymptotic regime where and grow large
with a given ratio and make use of recent results from large system analysis to
compute the asymptotic solution. Then, we concentrate on the asymptotically
design of heuristic linear precoding techniques. Interestingly, it turns out
that the regularized zero-forcing (RZF) precoder is equivalent to the optimal
one when the ratio between the SINR requirement and the average channel
attenuation is the same for all UEs. If this condition does not hold true but
only the same SINR constraint is imposed for all UEs, then the RZF can be
modified to still achieve optimality if statistical information of the UE
positions is available at the BS. Numerical results are used to evaluate the
performance gap in the finite system regime and to make comparisons among the
precoding techniques.Comment: 6 pages, 2 figures, IEEE Global Communications Conference (GLOBECOM),
Austin, Texas, Dec. 2014. An extended version of this work is available at
http://arxiv.org/abs/1406.598
Large System Analysis of Base Station Cooperation for Power Minimization
This work focuses on a large-scale multi-cell multi-user MIMO system in which
base stations (BSs) of antennas each communicate with
single-antenna user equipments. We consider the design of the linear precoder
that minimizes the total power consumption while ensuring target user rates.
Three configurations with different degrees of cooperation among BSs are
considered: the coordinated beamforming scheme (only channel state information
is shared among BSs), the coordinated multipoint MIMO processing technology or
network MIMO (channel state and data cooperation), and a single cell
beamforming scheme (only local channel state information is used for
beamforming while channel state cooperation is needed for power allocation).
The analysis is conducted assuming that and grow large with a non
trivial ratio and imperfect channel state information (modeled by the
generic Gauss-Markov formulation form) is available at the BSs. Tools of random
matrix theory are used to compute, in explicit form, deterministic
approximations for: (i) the parameters of the optimal precoder; (ii) the powers
needed to ensure target rates; and (iii) the total transmit power. These
results are instrumental to get further insight into the structure of the
optimal precoders and also to reduce the implementation complexity in
large-scale networks. Numerical results are used to validate the asymptotic
analysis in the finite system regime and to make comparisons among the
different configurations.Comment: 32 pages, 6 figures, to appear IEEE Trans. Wireless Commun. A
preliminary version of this paper was presented at the IEEE Global
Communication Conference, San Diego, USA, Dec. 201
Max-Min SINR in Large-Scale Single-Cell MU-MIMO: Asymptotic Analysis and Low Complexity Transceivers
This work focuses on the downlink and uplink of large-scale single-cell
MU-MIMO systems in which the base station (BS) endowed with antennas
communicates with single-antenna user equipments (UEs). Particularly, we
aim at reducing the complexity of the linear precoder and receiver that
maximize the minimum signal-to-interference-plus-noise ratio subject to a given
power constraint. To this end, we consider the asymptotic regime in which
and grow large with a given ratio. Tools from random matrix theory (RMT)
are then used to compute, in closed form, accurate approximations for the
parameters of the optimal precoder and receiver, when imperfect channel state
information (modeled by the generic Gauss-Markov formulation form) is available
at the BS. The asymptotic analysis allows us to derive the asymptotically
optimal linear precoder and receiver that are characterized by a lower
complexity (due to the dependence on the large scale components of the channel)
and, possibly, by a better resilience to imperfect channel state information.
However, the implementation of both is still challenging as it requires fast
inversions of large matrices in every coherence period. To overcome this issue,
we apply the truncated polynomial expansion (TPE) technique to the precoding
and receiving vector of each UE and make use of RMT to determine the optimal
weighting coefficients on a per-UE basis that asymptotically solve the max-min
SINR problem. Numerical results are used to validate the asymptotic analysis in
the finite system regime and to show that the proposed TPE transceivers
efficiently mimic the optimal ones, while requiring much lower computational
complexity.Comment: 13 pages, 4 figures, submitted to IEEE Transactions on Signal
Processin
Decentralized Multi-cell Beamforming Via Large System Analysis in Correlated Channels
Publication in the conference proceedings of EUSIPCO, Lisbon, Portugal, 201
Large System Analysis of the Energy Consumption Distribution in Multi-User MIMO Systems with Mobility
In this work, we consider the downlink of a single-cell multi-user MIMO
system in which the base station (BS) makes use of antennas to communicate
with single-antenna user equipments (UEs). The UEs move around in the cell
according to a random walk mobility model. We aim at determining the energy
consumption distribution when different linear precoding techniques are used at
the BS to guarantee target rates within a finite time interval . The
analysis is conducted in the asymptotic regime where and grow large
with fixed ratio under the assumption of perfect channel state information
(CSI). Both recent and standard results from large system analysis are used to
provide concise formulae for the asymptotic transmit powers and beamforming
vectors for all considered schemes. These results are eventually used to
provide a deterministic approximation of the energy consumption and to study
its fluctuations around this value in the form of a central limit theorem.
Closed-form expressions for the asymptotic means and variances are given.
Numerical results are used to validate the accuracy of the theoretical analysis
and to make comparisons. We show how the results can be used to approximate the
probability that a battery-powered BS runs out of energy and also to design the
cell radius for minimizing the energy consumption per unit area. The imperfect
CSI case is also briefly considered.Comment: 8 figures, 2 tables, to appear on IEEE Transactions on Wireless
Communication
Joint Distributed Precoding and Beamforming for RIS-aided Cell-Free Massive MIMO Systems
The amalgamation of cell-free networks and reconfigurable intelligent surface
(RIS) has become a prospective technique for future sixth-generation wireless
communication systems. In this paper, we focus on the precoding and beamforming
design for a downlink RIS-aided cell-free network. The design is formulated as
a non-convex optimization problem by jointly optimizing the combining vector,
active precoding, and passive RIS beamforming for minimizing the weighted sum
of users' mean square error. A novel joint distributed precoding and
beamforming framework is proposed to decentralize the alternating optimization
method for acquiring a suboptimal solution to the design problem. Finally,
numerical results validate the effectiveness of the proposed distributed
precoding and beamforming framework, showing its low-complexity and improved
scalability compared with the centralized method
Interference Management in 5G Reverse TDD HetNets with Wireless Backhaul: A Large System Analysis
This work analyzes a heterogeneous network (HetNet), which comprises a macro
base station (BS) equipped with a large number of antennas and an overlaid
dense tier of small cell access points (SCAs) using a wireless backhaul for
data traffic. The static and low mobility user equipment terminals (UEs) are
associated with the SCAs while those with medium-to-high mobility are served by
the macro BS. A reverse time division duplexing (TDD) protocol is used by the
two tiers, which allows the BS to locally estimate both the intra-tier and
inter-tier channels. This knowledge is then used at the BS either in the uplink
(UL) or in the downlink (DL) to simultaneously serve the macro UEs (MUEs) and
to provide the wireless backhaul to SCAs. A geographical separation of
co-channel SCAs is proposed to limit the interference coming from the UL
signals of MUEs. A concatenated linear precoding technique employing either
zero-forcing (ZF) or regularized ZF is used at the BS to simultaneously serve
MUEs and SCAs in DL while nulling interference toward those SCAs in UL. We
evaluate and characterize the performance of the system through the power
consumption of UL and DL transmissions under the assumption that target rates
must be satisfied and imperfect channel state information is available for
MUEs. The analysis is conducted in the asymptotic regime where the number of BS
antennas and the network size (MUEs and SCAs) grow large with fixed ratios.
Results from large system analysis are used to provide concise formulae for the
asymptotic UL and DL transmit powers and precoding vectors under the above
assumptions. Numerical results are used to validate the analysis in different
settings and to make comparisons with alternative network architectures.Comment: 14 pages, 12 figures. To appear IEEE J. Select. Areas Commun. --
Special Issue on HetNet
6G Enabled Advanced Transportation Systems
The 6th generation (6G) wireless communication network is envisaged to be
able to change our lives drastically, including transportation. In this paper,
two ways of interactions between 6G communication networks and transportation
are introduced. With the new usage scenarios and capabilities 6G is going to
support, passengers on all sorts of transportation systems will be able to get
data more easily, even in the most remote areas on the planet. The quality of
communication will also be improved significantly, thanks to the advanced
capabilities of 6G. On top of providing seamless and ubiquitous connectivity to
all forms of transportation, 6G will also transform the transportation systems
to make them more intelligent, more efficient, and safer. Based on the latest
research and standardization progresses, technical analysis on how 6G can
empower advanced transportation systems are provided, as well as challenges and
insights for a possible road ahead.Comment: Submitted to an open access journa