142 research outputs found
On the Convergence of Massive MIMO Systems
In this paper we examine convergence properties of massive MIMO systems with
the aim of determining the number of antennas required for massive MIMO gains.
We consider three characteristics of a channel matrix and study their
asymptotic behaviour. Furthermore, we derive ZF SNR and MF SINR for a scenario
of unequal receive powers. In our results we include the effects of spatial
correlation. We show that the rate of convergence of channel metrics is much
slower than that of the ZF/MF precoder properties.Comment: 6 pages, 6 figures, ICC 201
PAR-Aware Large-Scale Multi-User MIMO-OFDM Downlink
We investigate an orthogonal frequency-division multiplexing (OFDM)-based
downlink transmission scheme for large-scale multi-user (MU) multiple-input
multiple-output (MIMO) wireless systems. The use of OFDM causes a high
peak-to-average (power) ratio (PAR), which necessitates expensive and
power-inefficient radio-frequency (RF) components at the base station. In this
paper, we present a novel downlink transmission scheme, which exploits the
massive degrees-of-freedom available in large-scale MU-MIMO-OFDM systems to
achieve low PAR. Specifically, we propose to jointly perform MU precoding, OFDM
modulation, and PAR reduction by solving a convex optimization problem. We
develop a corresponding fast iterative truncation algorithm (FITRA) and show
numerical results to demonstrate tremendous PAR-reduction capabilities. The
significantly reduced linearity requirements eventually enable the use of
low-cost RF components for the large-scale MU-MIMO-OFDM downlink.Comment: To appear in IEEE Journal on Selected Areas in Communication
Asymptotic SEP Analysis and Optimization of Linear-Quantized Precoding in Massive MIMO Systems
A promising approach to deal with the high hardware cost and energy
consumption of massive MIMO transmitters is to use low-resolution
digital-to-analog converters (DACs) at each antenna element. This leads to a
transmission scheme where the transmitted signals are restricted to a finite
set of voltage levels. This paper is concerned with the analysis and
optimization of a low-cost quantized precoding strategy, referred to as
linear-quantized precoding, for a downlink massive MIMO system under Rayleigh
fading. In linear-quantized precoding, the signals are first processed by a
linear precoding matrix and subsequently quantized component-wise by the DAC.
In this paper, we analyze both the signal-to-interference-plus-noise ratio
(SINR) and the symbol error probability (SEP) performances of such
linear-quantized precoding schemes in an asymptotic framework where the number
of transmit antennas and the number of users grow large with a fixed ratio. Our
results provide a rigorous justification for the heuristic arguments based on
the Bussgang decomposition that are commonly used in prior works. Based on the
asymptotic analysis, we further derive the optimal precoder within a class of
linear-quantized precoders that includes several popular precoders as special
cases. Our numerical results demonstrate the excellent accuracy of the
asymptotic analysis for finite systems and the optimality of the derived
precoder.Comment: 58 pages, 8 figures, submitted for possible publicatio
Achieving "Massive MIMO" Spectral Efficiency with a Not-so-Large Number of Antennas
The main focus and contribution of this paper is a novel network-MIMO TDD
architecture that achieves spectral efficiencies comparable with "Massive
MIMO", with one order of magnitude fewer antennas per active user per cell. The
proposed architecture is based on a family of network-MIMO schemes defined by
small clusters of cooperating base stations, zero-forcing multiuser MIMO
precoding with suitable inter-cluster interference constraints, uplink pilot
signals reuse across cells, and frequency reuse. The key idea consists of
partitioning the users population into geographically determined "bins", such
that all users in the same bin are statistically equivalent, and use the
optimal network-MIMO architecture in the family for each bin. A scheduler takes
care of serving the different bins on the time-frequency slots, in order to
maximize a desired network utility function that captures some desired notion
of fairness. This results in a mixed-mode network-MIMO architecture, where
different schemes, each of which is optimized for the served user bin, are
multiplexed in time-frequency. In order to carry out the performance analysis
and the optimization of the proposed architecture in a clean and
computationally efficient way, we consider the large-system regime where the
number of users, the number of antennas, and the channel coherence block length
go to infinity with fixed ratios. The performance predicted by the large-system
asymptotic analysis matches very well the finite-dimensional simulations.
Overall, the system spectral efficiency obtained by the proposed architecture
is similar to that achieved by "Massive MIMO", with a 10-fold reduction in the
number of antennas at the base stations (roughly, from 500 to 50 antennas).Comment: Full version with appendice (proofs of theorems). A shortened version
without appendice was submitted to IEEE Trans. on Wireless Commun. Appendix B
was revised after submissio
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